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What does the future of technology look like?

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The world of work in 2050. If you're unlucky enough not to have retired by then, the working world will be a very different place to how it is today. The vision of the future for workers tends to scale from a nihilistic view of the robots taking our jobs (leaving us permanently trapped indoors, living entirely from Amazon Prime supplies), through to the utopia of the eradication of repetitive tasks using artificial intelligence. This will leave humans free to think, create and act (while never needing to leave your home...thanks to improved teleworking and those highly convenient Amazon delivery drones).

But what do the experts think it will really be like?

Robots have rights too
Predicted by: Ian Pearson. Ian has been a full-time futurologist for over 25 years, tracking and predicting developments across a wide range of technology, business, society, politics and the environment.
We see a picket line of robots in the city center. Their placards are plastered with slogans written in binary code. The widespread development of robots and artificial intelligence have necessitated the creation of a legal framework to protect them to regulate the rights of intelligent robots. Subsequently, this code is constantly updated and improved so robots have improving rights in our society.

Personal assistants for life
Predicted by: Alexey Malanov
Personal assistants (PAs) have rapidly developed throughout the 21st century. To begin with, they could only answer primitive questions: in 2019, voice assistants were as dumb as a box of rocks. But by 2025, they'd mastered the art of recognizing and transcribing speech (with punctuation marks too); they could understand the meaning of a text and recite it so realistically that it was almost indistinguishable from a human. This led to half of all office activities being automated: PAs began to take minutes, write post-meeting reports, summarize lengthy documents, and consciously digest and recapitulate the contents of messages. They also plan your day, schedule meetings and even order lunch.

Thanks to machine learning, PAs are fully adapted to their owners' personalities, increasingly penetrating every aspect of their lives. It all began with assisting with office work, and by the mid-2040s, PAs had become an integral part of everyday life by monitoring their owners' diets, planning trips abroad, buying gifts for friends and family, and more.

But it's not as rosy as it seems: the human-PA relationship has spawned a plethora of psychological issues and communication difficulties between real people. However, a specially trained AI psychologist is on hand to help us cope. Paradoxically, it's just another voice assistant.

The power is in your hands
Predicted by: Mersey Shelley is a pseudonym of Alexey Andreyev, writer and futurologist, who works for Kaspersky. This prediction is from his cyberpunk novel '2048' published in 2004.
In decades past, palms and fingers were scanned for identification. Now, hands with implanted sensors become the scanners themselves. These implants come in different models with two main variations: first, a simple scanner for daily use. It helps to read different tags and product codes, and to exchange digital business cards via the handshake ritual (you can use face recognition to identify a stranger but this is considered indecent; besides, many people use protection to prevent recognition. Hats with special veils are popular). Second, sophisticated scanners for technicians and other professionals. For example, a doctor's hand includes various medical sensors for diagnostics - even a portable endoscope with a direct video stream to the doctor's visual cortex.

A flexible workforce
Predicted by: Jacob Morgan is a best-selling author, speaker, futurist and founder of FutureOfWorkUniversity.com.
In the year 2050, technology will dominate the workplace with artificial intelligence and smart assistants being commonplace, while the use of augmented and virtual reality continues to increase. Everything will be 'smart' - connected and data-driven. The vast majority of us will continue working the same way we are today, but the jobs on offer will be ones that haven't yet been invented. Emotional intelligence and 'human' skills such as perpetual learning will be crucial for leaders to possess, as well as fluency with the latest technologies.

Work will increasingly become more fluid as some employees will be virtual, some will be full-time, some will be bots, and we will all be working non-fixed hours. As with any kind of change, there will be pros and cons. Those who work in routine jobs are likely to struggle to make sure they can stay relevant in the new world of work. The advantage is that this will give us more time to focus on the human aspects of work such as building relationships, being creative, deep thinking, and practicing skills like empathy and self-awareness. Technology will help us make organizations more personable. This also means that we need to get more comfortable with using technology such as bots and AI in our work, a cause of tension and fear for some.

And what about working hours? It depends if you're a knowledge worker or working in industries like retail. Flexible work arrangements are already being implemented at organizations around the world. The advantages are far-ranging, from improving employee satisfaction, productivity and tenure, to being able to attract and retain top talent. The potential disadvantages here are making sure that employees can stay accountable for delivering high-quality work while feeling like they're a part of the team, dealing with isolation, and ensuring effective communication and collaboration. I think the pros outstrip the cons: when managed effectively, flexible work arrangements can be a huge benefit to the organization and its people.

Focus on the user experience
Predicted by: Edney Souza, digital culture and business and technology teacher, speaker and entrepreneur, Brazil.
For sure, work will become more fun and those repetitive activities in our day-to-day life will be done by robots and artificial intelligence. Knowing programming logic will be as important as English and mathematics. User experience design (UX) will be more important than other technical components of a project to ensure its success with customers. Skills in solving problems and serving customers will continue to be competitive advantages for the work of the future.

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What will the future of work be like by 2050?

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Future tech Tags: SEO title: SEO description: SEO Tags: future of work Slug: Related articles: earth2050-cybersecurity future-it-jobs remote-flexible-working-benefits Header image: earth2050-robot-protestor Stand first / Page description: A flexible workforce? Therapy delivered by AI? Experts predict what the future of work will be like by 2050. Body: The world of work in 2050.

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O'Neill, S. (2020). What will the future of work be like by 2050? [web log]. https://www.kaspersky.com/blog/secure-futures-magazine/earth-2050-future-work/28219/#:~:text=In%20the%20year%202050%2C%20technology,%E2%80%93%20connected%20and%20data%2Ddriven.

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The world of work in 2050. If you're unlucky enough not to have retired by then, the working world will be a very different place to how it is today. The vision of the future for workers tends to scale from a nihilistic view of the robots taking our jobs (leaving us permanently trapped indoors, living entirely from Amazon Prime supplies), through to the utopia of the eradication of repetitive tasks using artificial intelligence. This will leave humans free to think, create and act (while never needing to leave your home...thanks to improved teleworking and those highly convenient Amazon delivery drones).

But what do the experts think it will really be like?

Robots have rights too
Predicted by: Ian Pearson. Ian has been a full-time futurologist for over 25 years, tracking and predicting developments across a wide range of technology, business, society, politics and the environment.
We see a picket line of robots in the city center. Their placards are plastered with slogans written in binary code. The widespread development of robots and artificial intelligence have necessitated the creation of a legal framework to protect them to regulate the rights of intelligent robots. Subsequently, this code is constantly updated and improved so robots have improving rights in our society.

Personal assistants for life
Predicted by: Alexey Malanov
Personal assistants (PAs) have rapidly developed throughout the 21st century. To begin with, they could only answer primitive questions: in 2019, voice assistants were as dumb as a box of rocks. But by 2025, they'd mastered the art of recognizing and transcribing speech (with punctuation marks too); they could understand the meaning of a text and recite it so realistically that it was almost indistinguishable from a human. This led to half of all office activities being automated: PAs began to take minutes, write post-meeting reports, summarize lengthy documents, and consciously digest and recapitulate the contents of messages. They also plan your day, schedule meetings and even order lunch.

Thanks to machine learning, PAs are fully adapted to their owners' personalities, increasingly penetrating every aspect of their lives. It all began with assisting with office work, and by the mid-2040s, PAs had become an integral part of everyday life by monitoring their owners' diets, planning trips abroad, buying gifts for friends and family, and more.

But it's not as rosy as it seems: the human-PA relationship has spawned a plethora of psychological issues and communication difficulties between real people. However, a specially trained AI psychologist is on hand to help us cope. Paradoxically, it's just another voice assistant.

The power is in your hands
Predicted by: Mersey Shelley is a pseudonym of Alexey Andreyev, writer and futurologist, who works for Kaspersky. This prediction is from his cyberpunk novel '2048' published in 2004.
In decades past, palms and fingers were scanned for identification. Now, hands with implanted sensors become the scanners themselves. These implants come in different models with two main variations: first, a simple scanner for daily use. It helps to read different tags and product codes, and to exchange digital business cards via the handshake ritual (you can use face recognition to identify a stranger but this is considered indecent; besides, many people use protection to prevent recognition. Hats with special veils are popular). Second, sophisticated scanners for technicians and other professionals. For example, a doctor's hand includes various medical sensors for diagnostics - even a portable endoscope with a direct video stream to the doctor's visual cortex.

A flexible workforce
Predicted by: Jacob Morgan is a best-selling author, speaker, futurist and founder of FutureOfWorkUniversity.com.
In the year 2050, technology will dominate the workplace with artificial intelligence and smart assistants being commonplace, while the use of augmented and virtual reality continues to increase. Everything will be 'smart' - connected and data-driven. The vast majority of us will continue working the same way we are today, but the jobs on offer will be ones that haven't yet been invented. Emotional intelligence and 'human' skills such as perpetual learning will be crucial for leaders to possess, as well as fluency with the latest technologies.

Work will increasingly become more fluid as some employees will be virtual, some will be full-time, some will be bots, and we will all be working non-fixed hours. As with any kind of change, there will be pros and cons. Those who work in routine jobs are likely to struggle to make sure they can stay relevant in the new world of work. The advantage is that this will give us more time to focus on the human aspects of work such as building relationships, being creative, deep thinking, and practicing skills like empathy and self-awareness. Technology will help us make organizations more personable. This also means that we need to get more comfortable with using technology such as bots and AI in our work, a cause of tension and fear for some.

And what about working hours? It depends if you're a knowledge worker or working in industries like retail. Flexible work arrangements are already being implemented at organizations around the world. The advantages are far-ranging, from improving employee satisfaction, productivity and tenure, to being able to attract and retain top talent. The potential disadvantages here are making sure that employees can stay accountable for delivering high-quality work while feeling like they're a part of the team, dealing with isolation, and ensuring effective communication and collaboration. I think the pros outstrip the cons: when managed effectively, flexible work arrangements can be a huge benefit to the organization and its people.

Focus on the user experience
Predicted by: Edney Souza, digital culture and business and technology teacher, speaker and entrepreneur, Brazil.
For sure, work will become more fun and those repetitive activities in our day-to-day life will be done by robots and artificial intelligence. Knowing programming logic will be as important as English and mathematics. User experience design (UX) will be more important than other technical components of a project to ensure its success with customers. Skills in solving problems and serving customers will continue to be competitive advantages for the work of the future.

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What will the future of work be like by 2050?

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Future tech Tags: SEO title: SEO description: SEO Tags: future of work Slug: Related articles: earth2050-cybersecurity future-it-jobs remote-flexible-working-benefits Header image: earth2050-robot-protestor Stand first / Page description: A flexible workforce? Therapy delivered by AI? Experts predict what the future of work will be like by 2050. Body: The world of work in 2050.

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Researchers have been working to create new methods of testing to help fight covid-19 and other viruses.

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A new viral screening test could not only diagnose COVID-19 in a matter of minutes, but new research suggests it could simultaneously test for other viruses that might be mistaken for COVID-19, according to the study authors. In addition, the test can sequence the virus, providing information on the spread of COVID-19 variants.

The test, called nanopore sequencing of isothermal rapid viral amplification for near real-time analysis (NIRVANA), was described by a team of researchers in the journal Med. According to a press release, one of the test's major benefits is its small, pocket-sized portability.

"This is a virus detection and surveillance method that doesn't require an expensive infrastructure like other approaches," said co-corresponding author Juan Carlos Izpisua, in the press release. "We can accomplish with 1 portable test the same thing that others are using 2 or 3 different tests, with different machines, to do."

The current standard approach for COVID-19 testing is to use a nasal swab and run a polymerase chain reaction (PCR) test to detect genetic material from the SARS-CoV-2 virus. If the sample is negative, however, the researchers said clinicians have no information on what could be causing the patient's symptoms, unless they run separate PCR tests for other viruses. On the other hand, if the sample is positive for SARS-CoV-2, clinicians still do not know which COVID-19 variant a patient is infected with.

To address these problems, researchers at King Abdullah University of Science and Technology in Saudi Arabia developed an isothermal recombinase polymerase amplification (RPA) testing approach and combined it with real-time nanopore sequencing. The resulting test is faster, cheaper, and more portable than the current COVID-19 testing approach, according to the press release.

Unlike PCR tests, which cycle through lower and higher temperatures to separate DNA strands and copy them, RPA uses proteins to accomplish the same thing in just 20 minutes. The technology allows researchers to copy longer stretches of DNA and probe for multiple genes at the same time.

"We quickly realized that we could use this technique to not only detect SARS-CoV-2, but other viruses at the same time," said developer Mo Li, an assistant professor of bioscience at King Abdullah University of Science and Technology, in a press release.

The investigators designed NIRVANA to simultaneously test samples for COVID-19, influenza A, human adenovirus, and non-SARS-CoV-2 human coronavirus, according to the press release. In their article, the researchers said the device begins to report positive and negative results in just 15 minutes, and it finalized results on all 96 samples within 3 hours. This includes the sequencing of 5 regions of SARS-CoV-2 that are particularly prone to accumulate mutations leading to new variants, according to the press release.

Researchers tested NIRVANA on 10 samples known to be positive for SARS-CoV-2, 60 samples of unknown SARS-CoV-2 status, and samples of municipal wastewater harboring the SARS-CoV-2 virus and others. In all cases, the assay correctly identified which viruses were present, according to the press release. The data also allowed the investigators to narrow down the origin of SARS-CoV-2 in positive samples, such as differentiating strains from China and Europe.

"The design of this assay is really flexible, so it's not just limited to the examples we've shown," Li said in the press release. "We can easily adapt it to tackle another pathogen, even something new and emergent."

Based on their findings and considering the small size and portability of the test, the investigators said it could be used for fast virus detection in schools, airports, or ports, and it could also be used to monitor wastewater or streams for the presence of new viruses.

"The pandemic has provided 2 important lessons: first, test widely and quickly, and second, know your variants," explained Izpisua Belmonte, a researcher at Salk, in the press release. "Our NIRVANA method provides a promising solution to these 2 challenges not only for the current pandemic, but also for possible future ones."
REFERENCE
Fast, Portable Test Can Diagnose COVID-19 and Track Variants [news release]. Salk; March 31, 2021. https://www.salk.edu/news-release/fast-portable-test-can-diagnose-covid-19-and-track-variants/. Accessed April 5, 2021.

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Rapid, Portable COVID-19 Test Could Help Track Variants

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A new viral screening test could not only diagnose COVID-19 in a matter of minutes, but new research suggests it could simultaneously test for other viruses that might be mistaken for COVID-19, according to the study authors. In addition, the test can sequence the virus, providing information on the spread of COVID-19 variants.

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Antrim, A. (2021, April 8). Rapid, portable COVID-19 test could help Track Variants. Retrieved April 09, 2021, from https://www.pharmacytimes.com/view/rapid-portable-covid-19-test-could-help-track-variants

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A new viral screening test could not only diagnose COVID-19 in a matter of minutes, but new research suggests it could simultaneously test for other viruses that might be mistaken for COVID-19, according to the study authors. In addition, the test can sequence the virus, providing information on the spread of COVID-19 variants.

The test, called nanopore sequencing of isothermal rapid viral amplification for near real-time analysis (NIRVANA), was described by a team of researchers in the journal Med. According to a press release, one of the test's major benefits is its small, pocket-sized portability.

"This is a virus detection and surveillance method that doesn't require an expensive infrastructure like other approaches," said co-corresponding author Juan Carlos Izpisua, in the press release. "We can accomplish with 1 portable test the same thing that others are using 2 or 3 different tests, with different machines, to do."

The current standard approach for COVID-19 testing is to use a nasal swab and run a polymerase chain reaction (PCR) test to detect genetic material from the SARS-CoV-2 virus. If the sample is negative, however, the researchers said clinicians have no information on what could be causing the patient's symptoms, unless they run separate PCR tests for other viruses. On the other hand, if the sample is positive for SARS-CoV-2, clinicians still do not know which COVID-19 variant a patient is infected with.

To address these problems, researchers at King Abdullah University of Science and Technology in Saudi Arabia developed an isothermal recombinase polymerase amplification (RPA) testing approach and combined it with real-time nanopore sequencing. The resulting test is faster, cheaper, and more portable than the current COVID-19 testing approach, according to the press release.

Unlike PCR tests, which cycle through lower and higher temperatures to separate DNA strands and copy them, RPA uses proteins to accomplish the same thing in just 20 minutes. The technology allows researchers to copy longer stretches of DNA and probe for multiple genes at the same time.

"We quickly realized that we could use this technique to not only detect SARS-CoV-2, but other viruses at the same time," said developer Mo Li, an assistant professor of bioscience at King Abdullah University of Science and Technology, in a press release.

The investigators designed NIRVANA to simultaneously test samples for COVID-19, influenza A, human adenovirus, and non-SARS-CoV-2 human coronavirus, according to the press release. In their article, the researchers said the device begins to report positive and negative results in just 15 minutes, and it finalized results on all 96 samples within 3 hours. This includes the sequencing of 5 regions of SARS-CoV-2 that are particularly prone to accumulate mutations leading to new variants, according to the press release.

Researchers tested NIRVANA on 10 samples known to be positive for SARS-CoV-2, 60 samples of unknown SARS-CoV-2 status, and samples of municipal wastewater harboring the SARS-CoV-2 virus and others. In all cases, the assay correctly identified which viruses were present, according to the press release. The data also allowed the investigators to narrow down the origin of SARS-CoV-2 in positive samples, such as differentiating strains from China and Europe.

"The design of this assay is really flexible, so it's not just limited to the examples we've shown," Li said in the press release. "We can easily adapt it to tackle another pathogen, even something new and emergent."

Based on their findings and considering the small size and portability of the test, the investigators said it could be used for fast virus detection in schools, airports, or ports, and it could also be used to monitor wastewater or streams for the presence of new viruses.

"The pandemic has provided 2 important lessons: first, test widely and quickly, and second, know your variants," explained Izpisua Belmonte, a researcher at Salk, in the press release. "Our NIRVANA method provides a promising solution to these 2 challenges not only for the current pandemic, but also for possible future ones."
REFERENCE
Fast, Portable Test Can Diagnose COVID-19 and Track Variants [news release]. Salk; March 31, 2021. https://www.salk.edu/news-release/fast-portable-test-can-diagnose-covid-19-and-track-variants/. Accessed April 5, 2021.

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Rapid, Portable COVID-19 Test Could Help Track Variants

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A new viral screening test could not only diagnose COVID-19 in a matter of minutes, but new research suggests it could simultaneously test for other viruses that might be mistaken for COVID-19, according to the study authors. In addition, the test can sequence the virus, providing information on the spread of COVID-19 variants.

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Due to lack of production, America had to import supplies that were in high demand. Depending on importing supplies made America unstable and scrabbling for a solution.

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Why was the United States left scrambling for critical medical equipment as the coronavirus swept the country? With the Associated Press and Global Reporting Centre, FRONTLINE investigates the fragmented global medical supply chain and its deadly consequences.

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Klein, P., Brandt, C., Linderman, J., Mendoza, M., & McCormick, K. (Producers). (2020, October 6). America's medical supply crisis [Video file]. Retrieved April 8, 2021, from https://www.pbs.org/wgbh/frontline/film/americas-medical-supply-crisis/

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Why was the United States left scrambling for critical medical equipment as the coronavirus swept the country? With the Associated Press and Global Reporting Centre, FRONTLINE investigates the fragmented global medical supply chain and its deadly consequences.

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Not all jobs will have the same exposure to AI.

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Everywhere you turn today is some unbelievable technological advancement on a variety of fronts. In our everyday lives, we hear or experience things about autonomous vehicles, warehouse robots, chatbots, Alexa, Siri, Uber, automated email responses, robotic surgeries, Netflix recommendation systems, smart factories, smart buildings and search retargeting. Technology giants are becoming the most valuable companies on the planet, and we see our lives shifting from what we thought was kids and their smartphone addictions and gaming to encroaching on our daily lives across the board. They are typically revolving around a variety of enabling technology layers, namely, cloud computing, computational systems, networks and sensors, robotics, material sciences, digital manufacturing and artificial intelligence. However, at the center of it, is AI that permeates many of the other advances in some shape or form in creating intelligent systems on top of advances in core products or technologies.

"Computers, intelligent machines and robots seem like the workforce of the future. And as more and more jobs are replaced by technology, people will have less work to do and ultimately will be sustained by payments from the government," predicts Elon Musk, the cofounder and CEO of Tesla. This is a scary proposition in some sense, in that what will we do if all the work is done by AI or robots? Isn't life tough enough? Don't we have enough economic disparity and can barely make ends meet today? To add insult to injury, many of the analyses seem to center on displacing the low wage workers. As if they didn't have enough disadvantages already, their entire economic class will be wiped out is the feeling we get from the news cycle. This is evidenced by robotic warehouses and chatbots or automated customer service and we can really feel the changes all around us.

Innovation and technology are certainly changing; skills and jobs as we know them today will need to change. Our frame of reference is being disrupted like never before, the guideposts and rules are changing, and this causes discomfort, uncertainty and worry. How can we chart the course if we are uncertain that the traditional methods (hard work, educational degrees, etc.) do not necessarily guarantee a certain quality of life? News flash, it is changing rapidly and therefore uncertain. We need to all become comfortable with being uncomfortable, with adapting to change, continuing education and reskilling. Some reports predict that millennials will change their jobs 17 times, but that might be a low number when you really factor in the gig economy.

According to various reports, the warnings suggest that AI could lead to the loss of tens of millions of jobs. It begs the question, when or what is the time horizon of the adoption of AI and the job loss a reality? Many reports suggest of job displacement or the very nature of jobs shifting. Automation and technology have shifted work in pursuit of lowering costs, increasing efficiency and production. The automobile "displaced" work that was done via horse and buggy, electricity or fluorescent lighting displaced gas lamps and gas replaced coal in many instances. Jobs have been displaced in the past, but in today's case the rate at which these exponential technologies are growing is moving faster than the rate of human adaptation. That speed at which we are experiencing technological and societal change is only the beginning as many futurists, such as Peter Diamandis, prophesize.

Bloomberg reports that "more than 120 million workers globally will need retraining in the next three years due to artificial intelligence's impact on jobs, according to an IBM survey." That report and interpretations of it seem to suggest that adoption of AI may result in massive job losses and requires massive retraining. This paints a doomsday scenario, creates uncertainty and worry. The interpretation is AI equals job loss; we would argue that the interpretation should be interpreted as AI and technology advancements will require job retraining and job reskilling. The reports also seem to suggest that our educational system is preparing for jobs of today, when we see that the jobs of the future will be quite different, with different resources and tools at our disposal. This further creates panic in that we see nothing but chaos and the inability to control our destiny for ourselves and our children.

The report was MIT-IBM Watson Lab research that shed light on the reorganization of tasks within occupations by analyzing 170 million online job postings in the U.S. between 2010-17. There is no question that AI and related technologies will affect all jobs; what the report did shed light on was the fact how the nature of work is changing, how tasks are changing and tried to link the implications for employment and wages. There were some key findings in the report, that tasks are shifting between people and machines (or AI), but the change has been small (Figure 1).

Automation or AI is disappearing from job requirements, shifting in the way work gets done; as technology reduces the cost of some tasks, the value of remaining tasks increases, particularly soft skills such as creativity, common sense, judgment and communication skills.

This type of analysis is what experts refer to as the "future of work" and how the work is shifting, job requirements are changing, and automation and AI are displacing certain sectors of the labor market. It also informs policymakers of where to focus attention and resources in order to best prepare for the future. Many of the takeaways and political talk seem to focus on "the vulnerable will be the most vulnerable" as a key takeaway, and that better-educated workers will fare out alright as AI/automation spreads. As a McKinsey report forecasted 800 million global workers could be replaced by robots by 2030, they further stated that blue-collar jobs, such as machine operating, warehouse workers and fast food are particularly susceptible to disruption.

But a new study published by the Brookings institution states that might not be the case. The report looked at thousands of AI patents and job descriptions and that educated, well-paid workers may be affected even more by the spread of AI. Most consider robotics and software as impacting the physical and routine work of traditionally blue-collar jobs. The report goes on to state that workers with a bachelor's degree, for example, would be exposed to AI over five times more than those with only a high school degree. That is due to the fact AI is very strong at completing tasks that require planning, learning, reasoning, problem-solving and predicting - most of which are skills we think of as white-collar jobs.

This analysis of patent data and tasks and exposure to risk on a sampling of various occupations in Table 2.
Author bios:
AI's impact on the workplace, the future of work, sectors of the economy and global domination are hard to assess. Most forecasts are rooted in well-established, well-understood technologies such as robotics and extrapolated across of a range of tasks, functions and jobs. The nature of AI being new and poorly understood, nonetheless unsuccessfully implemented across all industries, makes it even more difficult to understand. There is no shared agreement on the tasks, nor the expected impacts on the workforce or economy. The best scholars concede to the limitations of their economic or forecasts for the future. What we do know is that the nature of work will change, as it has through the centuries with innovation. We do know that disruption will occur in sectors of the economy, and we should brace for that change and try to harness that change for good. Perhaps AI can see patterns in deadly diseases, fight climate change and explore the universe. We should be as excited as nervous about change, and try to the best of our abilities to shape our society for that coming change.

Manjeet Rege is an associate professor of Graduate Programs in Software and Data Science and Director of Center for Applied Artificial Intelligence at the University of St. Thomas. Dr. Rege is an author, mentor, thought leader, and a frequent public speaker on big data, machine learning and artificial intelligence technologies. He is also the co-host of the "All Things Data" podcast that brings together leading data scientists, technologists, business model experts and futurists to discuss strategies to utilize, harness and deploy data science, data-driven strategies and enable digital transformation. Apart from being engaged in research, Dr. Rege regularly consults with various organizations to provide expert guidance for building big data and AI practice, and applying innovative data science approaches. He has published in various peer-reviewed reputed venues such as IEEE Transactions on Knowledge and Data Engineering, Data Mining & Knowledge Discovery Journal, IEEE International Conference on Data Mining, and the World Wide Web Conference. He is on the editorial review board of Journal of Computer Information Systems and regularly serves on the program committees of various international conferences.

Dan Yarmoluk is an adjunct faculty at Graduate Programs in Software at the University of St. Thomas. He has been involved in analytics, embedded design and components of mobile products for over a decade. He has focused on creating and driving IoT automation, condition monitoring and predictive maintenance programs with technology, analytics and business models that intersect to drive added value and digital transformation. Industries he has served include: oil and gas, refining, chemical, precision agriculture, food, pulp and paper, mining, transportation, filtration, field services and distribution. He publishes his thoughts frequently and co-hosts a popular podcast "All Things Data" with Dr. Manjeet Rege of the University of St. Thomas.

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Artificial Intelligence and Its Impact on Jobs - Newsroom | University of St. Thomas

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In this Tommie Experts piece, Manjeet Rege and Dan Yarmoluk weigh in on AI's impact on the future of work.

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Rege, M., & Yarmoluk, D. (2020, November 19). Artificial intelligence and its impact on jobs. Retrieved March 21, 2021, from https://news.stthomas.edu/artificial-intelligence-and-its-impact-on-jobs/

# data[].attributes.attachment_link.readable_text
Everywhere you turn today is some unbelievable technological advancement on a variety of fronts. In our everyday lives, we hear or experience things about autonomous vehicles, warehouse robots, chatbots, Alexa, Siri, Uber, automated email responses, robotic surgeries, Netflix recommendation systems, smart factories, smart buildings and search retargeting. Technology giants are becoming the most valuable companies on the planet, and we see our lives shifting from what we thought was kids and their smartphone addictions and gaming to encroaching on our daily lives across the board. They are typically revolving around a variety of enabling technology layers, namely, cloud computing, computational systems, networks and sensors, robotics, material sciences, digital manufacturing and artificial intelligence. However, at the center of it, is AI that permeates many of the other advances in some shape or form in creating intelligent systems on top of advances in core products or technologies.

"Computers, intelligent machines and robots seem like the workforce of the future. And as more and more jobs are replaced by technology, people will have less work to do and ultimately will be sustained by payments from the government," predicts Elon Musk, the cofounder and CEO of Tesla. This is a scary proposition in some sense, in that what will we do if all the work is done by AI or robots? Isn't life tough enough? Don't we have enough economic disparity and can barely make ends meet today? To add insult to injury, many of the analyses seem to center on displacing the low wage workers. As if they didn't have enough disadvantages already, their entire economic class will be wiped out is the feeling we get from the news cycle. This is evidenced by robotic warehouses and chatbots or automated customer service and we can really feel the changes all around us.

Innovation and technology are certainly changing; skills and jobs as we know them today will need to change. Our frame of reference is being disrupted like never before, the guideposts and rules are changing, and this causes discomfort, uncertainty and worry. How can we chart the course if we are uncertain that the traditional methods (hard work, educational degrees, etc.) do not necessarily guarantee a certain quality of life? News flash, it is changing rapidly and therefore uncertain. We need to all become comfortable with being uncomfortable, with adapting to change, continuing education and reskilling. Some reports predict that millennials will change their jobs 17 times, but that might be a low number when you really factor in the gig economy.

According to various reports, the warnings suggest that AI could lead to the loss of tens of millions of jobs. It begs the question, when or what is the time horizon of the adoption of AI and the job loss a reality? Many reports suggest of job displacement or the very nature of jobs shifting. Automation and technology have shifted work in pursuit of lowering costs, increasing efficiency and production. The automobile "displaced" work that was done via horse and buggy, electricity or fluorescent lighting displaced gas lamps and gas replaced coal in many instances. Jobs have been displaced in the past, but in today's case the rate at which these exponential technologies are growing is moving faster than the rate of human adaptation. That speed at which we are experiencing technological and societal change is only the beginning as many futurists, such as Peter Diamandis, prophesize.

Bloomberg reports that "more than 120 million workers globally will need retraining in the next three years due to artificial intelligence's impact on jobs, according to an IBM survey." That report and interpretations of it seem to suggest that adoption of AI may result in massive job losses and requires massive retraining. This paints a doomsday scenario, creates uncertainty and worry. The interpretation is AI equals job loss; we would argue that the interpretation should be interpreted as AI and technology advancements will require job retraining and job reskilling. The reports also seem to suggest that our educational system is preparing for jobs of today, when we see that the jobs of the future will be quite different, with different resources and tools at our disposal. This further creates panic in that we see nothing but chaos and the inability to control our destiny for ourselves and our children.

The report was MIT-IBM Watson Lab research that shed light on the reorganization of tasks within occupations by analyzing 170 million online job postings in the U.S. between 2010-17. There is no question that AI and related technologies will affect all jobs; what the report did shed light on was the fact how the nature of work is changing, how tasks are changing and tried to link the implications for employment and wages. There were some key findings in the report, that tasks are shifting between people and machines (or AI), but the change has been small (Figure 1).

Automation or AI is disappearing from job requirements, shifting in the way work gets done; as technology reduces the cost of some tasks, the value of remaining tasks increases, particularly soft skills such as creativity, common sense, judgment and communication skills.

This type of analysis is what experts refer to as the "future of work" and how the work is shifting, job requirements are changing, and automation and AI are displacing certain sectors of the labor market. It also informs policymakers of where to focus attention and resources in order to best prepare for the future. Many of the takeaways and political talk seem to focus on "the vulnerable will be the most vulnerable" as a key takeaway, and that better-educated workers will fare out alright as AI/automation spreads. As a McKinsey report forecasted 800 million global workers could be replaced by robots by 2030, they further stated that blue-collar jobs, such as machine operating, warehouse workers and fast food are particularly susceptible to disruption.

But a new study published by the Brookings institution states that might not be the case. The report looked at thousands of AI patents and job descriptions and that educated, well-paid workers may be affected even more by the spread of AI. Most consider robotics and software as impacting the physical and routine work of traditionally blue-collar jobs. The report goes on to state that workers with a bachelor's degree, for example, would be exposed to AI over five times more than those with only a high school degree. That is due to the fact AI is very strong at completing tasks that require planning, learning, reasoning, problem-solving and predicting - most of which are skills we think of as white-collar jobs.

This analysis of patent data and tasks and exposure to risk on a sampling of various occupations in Table 2.
Author bios:
AI's impact on the workplace, the future of work, sectors of the economy and global domination are hard to assess. Most forecasts are rooted in well-established, well-understood technologies such as robotics and extrapolated across of a range of tasks, functions and jobs. The nature of AI being new and poorly understood, nonetheless unsuccessfully implemented across all industries, makes it even more difficult to understand. There is no shared agreement on the tasks, nor the expected impacts on the workforce or economy. The best scholars concede to the limitations of their economic or forecasts for the future. What we do know is that the nature of work will change, as it has through the centuries with innovation. We do know that disruption will occur in sectors of the economy, and we should brace for that change and try to harness that change for good. Perhaps AI can see patterns in deadly diseases, fight climate change and explore the universe. We should be as excited as nervous about change, and try to the best of our abilities to shape our society for that coming change.

Manjeet Rege is an associate professor of Graduate Programs in Software and Data Science and Director of Center for Applied Artificial Intelligence at the University of St. Thomas. Dr. Rege is an author, mentor, thought leader, and a frequent public speaker on big data, machine learning and artificial intelligence technologies. He is also the co-host of the "All Things Data" podcast that brings together leading data scientists, technologists, business model experts and futurists to discuss strategies to utilize, harness and deploy data science, data-driven strategies and enable digital transformation. Apart from being engaged in research, Dr. Rege regularly consults with various organizations to provide expert guidance for building big data and AI practice, and applying innovative data science approaches. He has published in various peer-reviewed reputed venues such as IEEE Transactions on Knowledge and Data Engineering, Data Mining & Knowledge Discovery Journal, IEEE International Conference on Data Mining, and the World Wide Web Conference. He is on the editorial review board of Journal of Computer Information Systems and regularly serves on the program committees of various international conferences.

Dan Yarmoluk is an adjunct faculty at Graduate Programs in Software at the University of St. Thomas. He has been involved in analytics, embedded design and components of mobile products for over a decade. He has focused on creating and driving IoT automation, condition monitoring and predictive maintenance programs with technology, analytics and business models that intersect to drive added value and digital transformation. Industries he has served include: oil and gas, refining, chemical, precision agriculture, food, pulp and paper, mining, transportation, filtration, field services and distribution. He publishes his thoughts frequently and co-hosts a popular podcast "All Things Data" with Dr. Manjeet Rege of the University of St. Thomas.

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Artificial Intelligence and Its Impact on Jobs - Newsroom | University of St. Thomas

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In this Tommie Experts piece, Manjeet Rege and Dan Yarmoluk weigh in on AI's impact on the future of work.

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Does AI create more jobs then it replaces?

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Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people."

The number of jobs which AI and machines will displace in the future has been the subject of numerous studies and surveys and op-eds and policy papers since 2013, when a pair of Oxford academics, Carl Benedikt Frey and Michael Osborne, estimated that 47% of American jobs are at high risk of automation by the mid-2030s. Here are a few more recent examples of what has become a popular number-crunching (automated, computerized, AI-driven) exercise:

McKinsey Global Institute: between 40 million and 160 million women worldwide may need to transition between occupations by 2030, often into higher-skilled roles. Clerical work, done by secretaries, schedulers and bookkeepers, is an area especially susceptible to automation, and 72% of those jobs in advanced economies are held by women.

Oxford Economics: up to 20 million manufacturing jobs worldwide will be lost to robots by 2030.

McKinsey Global Institute: at the high end of the displacement by automation spectrum are 512 US counties, home to 20.3 million people, where more than 25% of workers could be displaced. The vast majority (429 counties) are rural areas in the Americana and distressed Americana segments. In contrast, urban areas with more diversified economies and workers with higher educational attainment, such as Washington, DC, and Durham, NC, might feel somewhat less severe effects from automation; just over 20% of their workforces are likely to be displaced.

But other reports provide a more positive take:

World Economic Forum: automation will displace 75 million jobs but generate 133 million new ones worldwide by 2022.

Gartner: AI-related job creation will reach two million net-new jobs in 2025.

McKinsey Global Institute: worldwide, with sufficient economic growth, innovation, and investment, there can be enough new job creation to offset the impact of automation, although in some advanced economies additional investments will be needed to reduce the risk of job shortages. In the US, there will be net positive job growth through 2030.

By way of explaining the more positive take on the future of work, a recent Forrester report ( Future of Work) argues that "automation is not a singular trend," and that future scenarios are influenced by the varying fortunes of a number of trends such as the gig economy, the destruction of industry boundaries, and the increasing desire for privacy and transparency. "You can argue that automation will open the aperture to new, previously unthinkable business opportunities as well as be the necessary engine to execute on business strategy," says Forrester.

Dismissing "apocalyptic scenarios that endanger fear," Forrester outlines its recommendations in terms of government policy (understand faster technology's impact), economic planning (maximize opportunity while minimizing impact on local jobs), business planning (good-by graceful planning cycles, hello disruptive forces), and leadership planning (learn to manage humans and machines). Most important, for individuals: "As much as companies must become learning institutions, so must employees become learners - learning core skills, adapting to new working models, and understanding what it means to be ready and fit for the future, maximizing their Robotics Quotient."

Still, Forrester predicts job losses of 29% by 2030 with only 13% job creation to compensate. These kind of estimates indeed endanger fear as we can see in recent surveys of individuals and business executives. For example:

Boston Consulting Group: 67% of Chinese executives and 50% of US executives expect a reduction in the number of employees over the next 5 years due to advanced robotics (global survey of more than 1,300 executives and operations managers).

ZipRecruiter: One in five job seekers (one in three for those between the ages of 18 and 22) fear they will one day lose their job to AI (survey of more than 11,000 job seekers in the US).

A recent Gallup and Northeastern University online survey of 4,394 Americans, 3,049 Canadians and 3,208 U.K. adults found mixed attitudes towards AI, reflecting the mix of apocalyptic and human-friendly scenarios outlined above:

There is a general, pessimistic attitude about the impact of AI adoption on the overall economy, but adults in the U.S., U.K. and Canada remain optimistic about their own jobs.

Seven in ten Americans, six in ten Canadians, and six in ten U.K. residents believe the advent of artificial intelligence will eliminate more jobs than it creates.

When asked to assess the impact that artificial intelligence "will have on how people work and live in the next 10 years," large majorities said the consequences will be "very" or "mostly" positive (72% in Canada, 70% in U.K., 67% in U.S.).

When asked about the best skills to withstand artificial intelligence, six in 10 respondents in Canada and the U.K. believe teamwork, communication, creativity, and critical thinking are most important in the new era of automation; whereas Americans are split 50-50 between those "soft" skills and technical skills like math, science, coding, and working with data.

It may well be that in this, as well as in other surveys, many respondents did not understand or were not familiar with "AI." Says the Gallup/Northeastern report: "Despite frequent media reporting concerning AI in all three countries, adults in these nations are still confused about exactly what the technology is."

That human intelligence tends to fail where semantics and exact meanings are involved is a fact plaguing not just surveys but also number-crunching models, future scenarios, the media, and their audiences. The Economist reports that the above-mentioned Mr. Frey, whose 2013 paper has been cited in more than 4,000 other academic papers, now says that "'Lots of people actually think I believe that half of all jobs are going to be automated in a decade or two,'... leaving half the population unemployed. That is, Mr Frey stresses, 'definitely not what the paper says.'"

What does it say? Only that the 47% of American jobs that falls into the "high risk" category, compared with other professions, are the most vulnerable to automation. The Economist: "'We make no attempt to estimate how many jobs will actually be automated,' the authors write. That, they underscore, will depend on many other things, such as cost, regulatory concerns, political pressure and social resistance."

My very human intelligence fails to see the difference between a prediction that says that close to half of all jobs are high-risk and vulnerable to automation and a prediction that says that close to half of all jobs are actually going to be automated away.

This may or may not be a good example of people jumping to (the wrong) conclusions, but these highly intelligent academic nuances-and meaningless spreadsheet manipulation exercises ( The Economist reports that the classification of high-risk jobs was done by a machine learning model developed by Mr. Frey's, as if this gives it more credibility)-may explain why people have lost their confidence in higher education. The major conclusion of the Gallup/Northeastern survey is

Perhaps most surprisingly, most of the adults in all three countries would not look to higher education for the additional skills and training they would require in response to AI adoption. A majority of the public in all three countries believes large businesses and government are not "doing enough to address the need for career-long learning and training."

Only 3% in the United States, 10% in the U.K., and 12% in Canada "strongly agree" that universities in their countries are preparing graduates for success in the current workforce. And if their skills become outdated, then strong majorities in all three countries would prefer to be educated by an employer rather than by a university, according to the Gallup/Northeastern survey.

Amazon (and other employers) to the rescue?

In the meantime, while we get trained in future-friendly skills and learn to understand better "AI" (and hopefully take apocalyptic scenarios, on any subject, with a grain of salt-or a better understanding of statistics, sampling, and model development and assumptions), here's what happening today:

A December 2018 Dun & Bradstreet survey of AI World Conference and Expo attendees found that 40% percent of respondents' organizations are adding more jobs as a result of deploying AI within their business and only 8% are cutting jobs due to AI implementation.

Mining data from more than 50 million job postings, ZipRecruiter found that AI created three times as many jobs as it destroyed in 2018. The fastest growing jobs AI has created from 2017 to 2018 include Senior Data Scientist with an annual growth of 340% (resulting in average salaries of $257,000 according to Burtch Works), Mobile Application Developer (186%) and SEO Specialist (180%). AI is creating "a surge in new career opportunities," says the ZipRecruiter report.

... Read More

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Is AI Going To Be A Jobs Killer? New Reports About The Future Of Work

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Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people."

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Press, G. (2019, July 17). Is ai going to be a jobs killer? New reports about the future of work. Retrieved March 21, 2021, from https://www.forbes.com/sites/gilpress/2019/07/15/is-ai-going-to-be-a-jobs-killer-new-reports-about-the-future-of-work/?sh=583b52a4afb2

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Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people."

The number of jobs which AI and machines will displace in the future has been the subject of numerous studies and surveys and op-eds and policy papers since 2013, when a pair of Oxford academics, Carl Benedikt Frey and Michael Osborne, estimated that 47% of American jobs are at high risk of automation by the mid-2030s. Here are a few more recent examples of what has become a popular number-crunching (automated, computerized, AI-driven) exercise:

McKinsey Global Institute: between 40 million and 160 million women worldwide may need to transition between occupations by 2030, often into higher-skilled roles. Clerical work, done by secretaries, schedulers and bookkeepers, is an area especially susceptible to automation, and 72% of those jobs in advanced economies are held by women.

Oxford Economics: up to 20 million manufacturing jobs worldwide will be lost to robots by 2030.

McKinsey Global Institute: at the high end of the displacement by automation spectrum are 512 US counties, home to 20.3 million people, where more than 25% of workers could be displaced. The vast majority (429 counties) are rural areas in the Americana and distressed Americana segments. In contrast, urban areas with more diversified economies and workers with higher educational attainment, such as Washington, DC, and Durham, NC, might feel somewhat less severe effects from automation; just over 20% of their workforces are likely to be displaced.

But other reports provide a more positive take:

World Economic Forum: automation will displace 75 million jobs but generate 133 million new ones worldwide by 2022.

Gartner: AI-related job creation will reach two million net-new jobs in 2025.

McKinsey Global Institute: worldwide, with sufficient economic growth, innovation, and investment, there can be enough new job creation to offset the impact of automation, although in some advanced economies additional investments will be needed to reduce the risk of job shortages. In the US, there will be net positive job growth through 2030.

By way of explaining the more positive take on the future of work, a recent Forrester report ( Future of Work) argues that "automation is not a singular trend," and that future scenarios are influenced by the varying fortunes of a number of trends such as the gig economy, the destruction of industry boundaries, and the increasing desire for privacy and transparency. "You can argue that automation will open the aperture to new, previously unthinkable business opportunities as well as be the necessary engine to execute on business strategy," says Forrester.

Dismissing "apocalyptic scenarios that endanger fear," Forrester outlines its recommendations in terms of government policy (understand faster technology's impact), economic planning (maximize opportunity while minimizing impact on local jobs), business planning (good-by graceful planning cycles, hello disruptive forces), and leadership planning (learn to manage humans and machines). Most important, for individuals: "As much as companies must become learning institutions, so must employees become learners - learning core skills, adapting to new working models, and understanding what it means to be ready and fit for the future, maximizing their Robotics Quotient."

Still, Forrester predicts job losses of 29% by 2030 with only 13% job creation to compensate. These kind of estimates indeed endanger fear as we can see in recent surveys of individuals and business executives. For example:

Boston Consulting Group: 67% of Chinese executives and 50% of US executives expect a reduction in the number of employees over the next 5 years due to advanced robotics (global survey of more than 1,300 executives and operations managers).

ZipRecruiter: One in five job seekers (one in three for those between the ages of 18 and 22) fear they will one day lose their job to AI (survey of more than 11,000 job seekers in the US).

A recent Gallup and Northeastern University online survey of 4,394 Americans, 3,049 Canadians and 3,208 U.K. adults found mixed attitudes towards AI, reflecting the mix of apocalyptic and human-friendly scenarios outlined above:

There is a general, pessimistic attitude about the impact of AI adoption on the overall economy, but adults in the U.S., U.K. and Canada remain optimistic about their own jobs.

Seven in ten Americans, six in ten Canadians, and six in ten U.K. residents believe the advent of artificial intelligence will eliminate more jobs than it creates.

When asked to assess the impact that artificial intelligence "will have on how people work and live in the next 10 years," large majorities said the consequences will be "very" or "mostly" positive (72% in Canada, 70% in U.K., 67% in U.S.).

When asked about the best skills to withstand artificial intelligence, six in 10 respondents in Canada and the U.K. believe teamwork, communication, creativity, and critical thinking are most important in the new era of automation; whereas Americans are split 50-50 between those "soft" skills and technical skills like math, science, coding, and working with data.

It may well be that in this, as well as in other surveys, many respondents did not understand or were not familiar with "AI." Says the Gallup/Northeastern report: "Despite frequent media reporting concerning AI in all three countries, adults in these nations are still confused about exactly what the technology is."

That human intelligence tends to fail where semantics and exact meanings are involved is a fact plaguing not just surveys but also number-crunching models, future scenarios, the media, and their audiences. The Economist reports that the above-mentioned Mr. Frey, whose 2013 paper has been cited in more than 4,000 other academic papers, now says that "'Lots of people actually think I believe that half of all jobs are going to be automated in a decade or two,'... leaving half the population unemployed. That is, Mr Frey stresses, 'definitely not what the paper says.'"

What does it say? Only that the 47% of American jobs that falls into the "high risk" category, compared with other professions, are the most vulnerable to automation. The Economist: "'We make no attempt to estimate how many jobs will actually be automated,' the authors write. That, they underscore, will depend on many other things, such as cost, regulatory concerns, political pressure and social resistance."

My very human intelligence fails to see the difference between a prediction that says that close to half of all jobs are high-risk and vulnerable to automation and a prediction that says that close to half of all jobs are actually going to be automated away.

This may or may not be a good example of people jumping to (the wrong) conclusions, but these highly intelligent academic nuances-and meaningless spreadsheet manipulation exercises ( The Economist reports that the classification of high-risk jobs was done by a machine learning model developed by Mr. Frey's, as if this gives it more credibility)-may explain why people have lost their confidence in higher education. The major conclusion of the Gallup/Northeastern survey is

Perhaps most surprisingly, most of the adults in all three countries would not look to higher education for the additional skills and training they would require in response to AI adoption. A majority of the public in all three countries believes large businesses and government are not "doing enough to address the need for career-long learning and training."

Only 3% in the United States, 10% in the U.K., and 12% in Canada "strongly agree" that universities in their countries are preparing graduates for success in the current workforce. And if their skills become outdated, then strong majorities in all three countries would prefer to be educated by an employer rather than by a university, according to the Gallup/Northeastern survey.

Amazon (and other employers) to the rescue?

In the meantime, while we get trained in future-friendly skills and learn to understand better "AI" (and hopefully take apocalyptic scenarios, on any subject, with a grain of salt-or a better understanding of statistics, sampling, and model development and assumptions), here's what happening today:

A December 2018 Dun & Bradstreet survey of AI World Conference and Expo attendees found that 40% percent of respondents' organizations are adding more jobs as a result of deploying AI within their business and only 8% are cutting jobs due to AI implementation.

Mining data from more than 50 million job postings, ZipRecruiter found that AI created three times as many jobs as it destroyed in 2018. The fastest growing jobs AI has created from 2017 to 2018 include Senior Data Scientist with an annual growth of 340% (resulting in average salaries of $257,000 according to Burtch Works), Mobile Application Developer (186%) and SEO Specialist (180%). AI is creating "a surge in new career opportunities," says the ZipRecruiter report.

... Read More

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Is AI Going To Be A Jobs Killer? New Reports About The Future Of Work

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Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people."

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O'Brien, G. (2020, February 26). Social media automation: Good, bad or somewhere in between? Retrieved March 13, 2021, from https://www.articulatemarketing.com/blog/social-media-automation

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Social media automation is a divisive topic. of automatic Critics content sharing maintain that it's the antithesis of social media; it's 'anti social' by definition. Proponents, meanwhile, wax lyrical about efficiency gains and scalability.

So is social media automation 'good' or 'bad' for a brand? Or is it a bit of both?

What is social media automation?

First things first: social media automation, as the name suggests, is the process of automating part or all of your social media marketing activity. This can involve anything from automating your content sharing activity to queuing tweets and recycling evergreen content . Social media automation tools, such as tools like and our own CoSchedule, HubSpot HubToolkit, often do the brunt of the work. They reduce time spent on marketing by taking over repetitive, energy-consuming tasks.

The answer to every marketer's prayers...

Automation sounds great, right? In theory, it is. It's hard to deny its advantages. For small and medium businesses (SMBs) in particular, social media marketing automation is an essential part of any strategy.

Don't believe me? Let's take a look at some stats:

An average of 32 per cent of businesses see increased revenue after 12 months of using automation tools;

while 77 per cent see conversions increase; and

On the whole, business that are automating part of or all of their marketing strategy outperform companies that aren't.

Marketing automation is also a great way to save time and money , because it means less resources and (billable!) hours are spent on manual, repetitive tasks. Hooray!

But a social media marketer's nightmare?

Anything that saves time and money while increasing conversions sounds good to me, but a little critical thinking is required when we consider social media automation.

In many ways, the benefits of automating your social media activity are the same as automating your other marketing activities. With tools like Buffer you can:

Keep your content consistent across channels;

maintain an active presence while you're on holiday (or just busy with other things);

monitor and analyse your social media activity without having to run your own stats and reports; and

post more in less time!

Needless to say these are all positives, but social media automation can have some serious drawbacks too:

It can wreak havoc on your brand equity. Your brand equity (i.e. the value of your brand as seen by your customers, which has a direct impact on sales volume and profit margins) can be seriously damaged by automated social media. Automatically liking, following or posting on social channels can make you look like a spam bot , and make you seem less trustworthy.

A lot of people hate it. Jonathan Crossfield isn't alone in his hatred of automated social media. Many people actively avoid brands who do things like automatically message new followers or post endless streams of content. Social media should be (or at least seem) authentic and 'social,' so automatically generated content can alienate your community.

Some social networks don't allow it. Instagram, for example, doesn't let you use tools or bots to automatically comment, like or follow people; it's a violation of their terms & conditions . You risk having your account suspended if you automate activity such as post liking and commenting. Are a few efficiency gains worth losing your account and carefully crafted content? No.

It still takes a lot of time and effort. Kevan Lee at Buffer made the astute observation that social media is not like a rotisserie oven : you can't 'set it and forget it.' Even if you manage to automate a few of your social media tasks and processes, you'll still have to monitor your channels and manually engage with followers to avoid social media faux pas like these .

HubToolkit: A stellar social media automation tool

Perhaps we sounded a tad negative in the last section. So, here's a positive: a social media automation software we created ourselves.

No - we're not talking about a tool that'll automatically spam your followers with creepy bot comments. HubToolkit is a tool that collects social media content from your favourite (relevant) RSS feeds, hands them to you in a newsfeed, and allows you to share them out via your social channels.

In short, it cuts out the noise and focuses on the third-party content your business (and followers) are truly interested in. It's simple, takes minutes, and best of all, you can trial it out for free today!

Social media automation: a necessary evil?

All things considered, social media automation is still a good way to optimise and scale your marketing activity. It leaves you with more time to create valuable content and engage meaningfully with your community. If you do automate some aspects of your social media activity, make time to learn how to use the tools, tune them properly and pay attention to the results. In other words, humanise the automation.

It can be risky, especially if you're not keeping on top of what's going out on your channels, but with with the right strategy and adherence to best practices the pitfalls of social media automation can be avoided. The trick is to strike a balance, and to know what to automate and when. Here's a few tips:

Don't automate interactions. For the love of all that is social, don't automate things like responses to comments or messages. Any form of automated, bot-generated engagement looks spammy and weird. And it can backfire if you're not careful.

Do automate your editorial calendar. Get yourself set up on HubToolkit or HubSpot and push your content (both internal and curated content) out to all your channels at optimal times. This will amplify the reach of your content and keep your networks active and engaged.

Experiment with different tools and strategies. There's no 'one way' to 'do' social media. At Articulate, we're always trying new things and experimenting with ways to delight and engage with our community. Try a bunch of different tools and find what works best for your strategy , resources and business goals. Here's a list to get you started.

The final verdict

Overall, social media automation hacks are a useful and wonderful thing. But all roses have their thorns and like all things, pulling automation off takes takes patience and skill.

If you want to start automating your social media activity take it one step at a time, and automate processes one by one. Try some of the tools we suggested, including HubToolkit, and let us know when you find social media success.
Hat tip to Mike Mozart for the featured image.
Want to evaluate your social media strategy? Take our quiz:
[This blog was originally published in 2016 and has been edited and updated in 2020]

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Social media automation: good, bad or somewhere in between?

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Social media automation is a divisive topic. of automatic Critics content sharing maintain that it's the antithesis of social media; it's 'anti social' by definition. Proponents, meanwhile, wax lyrical about efficiency gains and scalability. So is social media automation 'good' or 'bad' for a brand? Or is it a bit of both?

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Social automation can be helpful, but there are downsides.

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Social media automation is a divisive topic. of automatic Critics content sharing maintain that it's the antithesis of social media; it's 'anti social' by definition. Proponents, meanwhile, wax lyrical about efficiency gains and scalability.

So is social media automation 'good' or 'bad' for a brand? Or is it a bit of both?

What is social media automation?

First things first: social media automation, as the name suggests, is the process of automating part or all of your social media marketing activity. This can involve anything from automating your content sharing activity to queuing tweets and recycling evergreen content . Social media automation tools, such as tools like and our own CoSchedule, HubSpot HubToolkit, often do the brunt of the work. They reduce time spent on marketing by taking over repetitive, energy-consuming tasks.

The answer to every marketer's prayers...

Automation sounds great, right? In theory, it is. It's hard to deny its advantages. For small and medium businesses (SMBs) in particular, social media marketing automation is an essential part of any strategy.

Don't believe me? Let's take a look at some stats:

An average of 32 per cent of businesses see increased revenue after 12 months of using automation tools;

while 77 per cent see conversions increase; and

On the whole, business that are automating part of or all of their marketing strategy outperform companies that aren't.

Marketing automation is also a great way to save time and money , because it means less resources and (billable!) hours are spent on manual, repetitive tasks. Hooray!

But a social media marketer's nightmare?

Anything that saves time and money while increasing conversions sounds good to me, but a little critical thinking is required when we consider social media automation.

In many ways, the benefits of automating your social media activity are the same as automating your other marketing activities. With tools like Buffer you can:

Keep your content consistent across channels;

maintain an active presence while you're on holiday (or just busy with other things);

monitor and analyse your social media activity without having to run your own stats and reports; and

post more in less time!

Needless to say these are all positives, but social media automation can have some serious drawbacks too:

It can wreak havoc on your brand equity. Your brand equity (i.e. the value of your brand as seen by your customers, which has a direct impact on sales volume and profit margins) can be seriously damaged by automated social media. Automatically liking, following or posting on social channels can make you look like a spam bot , and make you seem less trustworthy.

A lot of people hate it. Jonathan Crossfield isn't alone in his hatred of automated social media. Many people actively avoid brands who do things like automatically message new followers or post endless streams of content. Social media should be (or at least seem) authentic and 'social,' so automatically generated content can alienate your community.

Some social networks don't allow it. Instagram, for example, doesn't let you use tools or bots to automatically comment, like or follow people; it's a violation of their terms & conditions . You risk having your account suspended if you automate activity such as post liking and commenting. Are a few efficiency gains worth losing your account and carefully crafted content? No.

It still takes a lot of time and effort. Kevan Lee at Buffer made the astute observation that social media is not like a rotisserie oven : you can't 'set it and forget it.' Even if you manage to automate a few of your social media tasks and processes, you'll still have to monitor your channels and manually engage with followers to avoid social media faux pas like these .

HubToolkit: A stellar social media automation tool

Perhaps we sounded a tad negative in the last section. So, here's a positive: a social media automation software we created ourselves.

No - we're not talking about a tool that'll automatically spam your followers with creepy bot comments. HubToolkit is a tool that collects social media content from your favourite (relevant) RSS feeds, hands them to you in a newsfeed, and allows you to share them out via your social channels.

In short, it cuts out the noise and focuses on the third-party content your business (and followers) are truly interested in. It's simple, takes minutes, and best of all, you can trial it out for free today!

Social media automation: a necessary evil?

All things considered, social media automation is still a good way to optimise and scale your marketing activity. It leaves you with more time to create valuable content and engage meaningfully with your community. If you do automate some aspects of your social media activity, make time to learn how to use the tools, tune them properly and pay attention to the results. In other words, humanise the automation.

It can be risky, especially if you're not keeping on top of what's going out on your channels, but with with the right strategy and adherence to best practices the pitfalls of social media automation can be avoided. The trick is to strike a balance, and to know what to automate and when. Here's a few tips:

Don't automate interactions. For the love of all that is social, don't automate things like responses to comments or messages. Any form of automated, bot-generated engagement looks spammy and weird. And it can backfire if you're not careful.

Do automate your editorial calendar. Get yourself set up on HubToolkit or HubSpot and push your content (both internal and curated content) out to all your channels at optimal times. This will amplify the reach of your content and keep your networks active and engaged.

Experiment with different tools and strategies. There's no 'one way' to 'do' social media. At Articulate, we're always trying new things and experimenting with ways to delight and engage with our community. Try a bunch of different tools and find what works best for your strategy , resources and business goals. Here's a list to get you started.

The final verdict

Overall, social media automation hacks are a useful and wonderful thing. But all roses have their thorns and like all things, pulling automation off takes takes patience and skill.

If you want to start automating your social media activity take it one step at a time, and automate processes one by one. Try some of the tools we suggested, including HubToolkit, and let us know when you find social media success.
Hat tip to Mike Mozart for the featured image.
Want to evaluate your social media strategy? Take our quiz:
[This blog was originally published in 2016 and has been edited and updated in 2020]

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Social media automation: good, bad or somewhere in between?

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Social media automation is a divisive topic. of automatic Critics content sharing maintain that it's the antithesis of social media; it's 'anti social' by definition. Proponents, meanwhile, wax lyrical about efficiency gains and scalability. So is social media automation 'good' or 'bad' for a brand? Or is it a bit of both?

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Cooper, P. (2020, November 24). What is Social Media Automation? (+ 7 Tools That Will Make it Easier) [Web log post]. Retrieved March 13, 2021, from https://blog.hootsuite.com/social-media-automation/

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Social Media Marketing & Management Dashboard

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If you're spending more time fussing with hashtags or answering DMs than brainstorming new content ideas or planning your long term social media strategy, you could probably use a shortcut. It's time to consider social media automation.

No, we're not talking about trying to bump up your vanity metrics by annoying people with weird bot comments. We're talking about tools that handle admin tasks like posting, monitoring and reporting, so that you can keep your social presence on-brand, up-to-date, and authentic, while spending less time on the day-to-day.

The thing about world-class social media automation is that-when it's done right-it can be pretty much invisible to the outside eye. That makes it tough to figure out what the pros are up to behind the scenes.

Read on to learn about the practices and tools social media experts use to save time and get results.

Bonus: Get a free social media strategy template to quickly and easily plan your own strategy. Also use it to track results and present the plan to your boss, teammates, and clients.

What is social media automation?

Social media automation is using software tools to handle some of the time-consuming tasks involved in maintaining a professional social media presence. For instance, scheduling posts ahead of time, curating content for republishing, triaging routine customer queries, and producing analytics reports are all examples of social media automation.

When it's done right, automating tedious or time-consuming tasks will free up your time so you can focus on the crucial, high-impact creative and strategic work that will move the needle on your real goals. Less time scrolling, more time selling.

However, not all social media tasks can or should be automated. Often the better-known kinds of automation are the ones that look lazy, spammy or fake.

For instance, paid Instagram bots that like, follow and comment are painfully obvious to savvy Instagram users. And using them is a very bad look for reputable brands.

Let's take a look at the kinds of automation that work, and the kinds that should be left in the grimy corners of digital marketing.

The DOs and DON'Ts of social media marketing automation

Integrating social media automation into your workflow can take a bit of initial legwork, especially if you're used to doing everything yourself. Same if you're part of a bigger, more complex department and need to court buy-in from your team.

Well, here are some tips to keep your efforts focused in the right direction.

DON'T post the same message to every network

Cross-posting the same text across all of your social accounts might save a few minutes, but the cost in credibility is high. If a tool (including the social platform itself) offers you the option to automatically cross-post to other platforms, you almost certainly want to decline.

Audiences on different platforms have different expectations, demographics, and vocabularies, and failing to recognize that can look sloppy or out-of-touch. Instead, take the extra time to adjust your message for each platform's audience. At the bare minimum, you'll want to:

Check and adjust user handles

Check and adjust image specs (file type, size, cropping, etc.)

Check and adjust hashtags (number and usage)

Check and adjust your vocabulary (i.e., retweet vs. regram vs. share)

DO post on your audience's schedule

As marketers, everything we do is tailored to our audiences, and that includes posting when they're online, not-alas-when we have a spare second between meetings.

There are two steps you need to take in order to optimize and automate your posting schedule:

1. Use a scheduling tool to craft your posts ahead of time;

2. Evaluate your analytics and schedule your posts for when your audience is on the platform.

Your social media posting schedule will be affected by which platforms you're focusing on, and your particular audience's habits. You can use the standard overall best time to post to social media platforms, and you can evaluate for your audience specifically using analytics tools.

DON'T "set it and forget it"

Even with legitimate social media automation, remember your tools don't have good judgement. In fact, they don't have any judgement at all. If you set an evergreen post to tweet every Friday at 11am eternally, it will do so without shame or remorse. (And no content is that evergreen.)

Whether you're a solopreneur or part of a big corporate team, use a tool with built-in, customizable approval processes to make sure that your posts are copyedited, on-brand and don't have any embarrassing mistakes.

(Source: @McDonalds -kudos to their social team for keeping this hilarious mistake up for the last three years for everyone's enjoyment.)

The other risk with going "hands-free" on your social scheduling tool is that world-changing crises happen all the time on social media, and a poorly timed post can make your brand look out-of-touch or tone deaf.

Pro tip: Batch-schedule your posts, but know what's happening internally and out in the world. Just because your car's got cruise control doesn't mean you can take your eyes off the road, Elon.

DON'T automate your behavior or comments

On social-as in life-one size definitely does not fit all. At Hootsuite, we've run automation experiments to test out various bot services. Long story short: their promises don't pan out, and they can cause lasting damage to your relationships with your audience. (Believe me, if automated comments worked, I would be first in line for a bot to handle my family group chat.)

Using bots to follow/unfollow people, like posts, or-worst of all-leave prefabricated comments, can put your reputation at risk. First impressions are crucial, and you don't want your interactions with potential customers to look fake, inane, or lazy, leaving a bad taste in their mouths.

And just to be clear, it's probably not a good idea to make a bunch of bots to hype your brand, either.

The time you spend keeping your relationships authentic and human will pay off in your analytics and social media ROI.

Pro tip: When it comes to conversations, the more legitimate form of automation is a tool that can handle your DMs, comments, tags in one place, consistently, at scale. For instance, Hootsuite Inbox's semi-automated Saved Replies feature lets you cycle through appropriate, authentic text based on the conversation and your customer's needs.

DO offer customer support 24/7

When it comes to customer support, 64% of people would rather message a brand on social than make a phone call. And 76% of messages that businesses receive on social are customer-service related.

You have three options for responding to customer service inquiries:

1. Pay to have customer service agents on deck around the clock

2. Use automated bots to manage expectations and direct inquiries

3. Leave your customers on read (A.K.A. ignore them)

These days, expectations for customer service on social are a little different than public-facing conversations. It's generally ok-and even expected-to have a chatbot or auto-response in place to handle straightforward inquiries, and appropriately direct customer service requests.

Get the template now!

Pro tip: Look into Facebook Messenger bots, or keep reading for our recommended automated customer support tools.

DO listen to the conversation

No doubt there are people in your life (hopefully not your manager, but probably your parents) who think that your job, as a social media manager, is to sit around watching TikTok all day. We can't help you with your mom (mine tells her friends my job is "writing those spam emails") but I want to reassure you that I really respect that you are trying to watch TikTok efficiently.

Social listening tools flag conversations, topics, and mentions so that you can stay informed about what's happening on social without getting seduced by the algorithm. Social listening is the most efficient way to:

Overall, with the right tools, social listening is one of the best ways to boost engagement. Check out our favourite tools in the list at the end.

DON'T babysit your ads

Ads cost money, and poorly optimized ads cost more money. The added pressure of a diminishing budget can make it tough to tear yourself away from your ads dashboards. But rather than spending your day staring at your cost per clicks and fussing with your ad metrics, consider automating key steps in your social media ads.

Organic and paid social usually demand different strategies, but the thing about ads is that they're so data-driven that automation is the best strategy, here.

One of the easiest shortcuts is a tool (like, for instance, Hootsuite Boost) that can automatically promote your top-performing organic content. If you have a home-run post on your hands you'll want to throw some dollars at it to make sure it has the best chance of snowballing. For instance, a post that gets 2x your average number of shares is something you likely want to show to a wider audience. Hootsuite Boost automates that trigger so it happens whether you're at your desk staring at it, or not.

Bonus tip: Split-testing (or A/B testing) your social ads is pretty much mandatory if you want to hit your KPIs, but consigning yourself to testing ads by hand is cruel and unusual self-punishment. Using a split-testing tool like AdEspresso might sound like a mathy extra step, but once you have it set up it'll improve your results with little ongoing effort on your part.

7 social media automation tools to do it right

Now that we've gone over the best practices for automating your social media presence to save time, let's look at the top tools you can use to make it happen.

This is our favourite social media scheduling tool for obvious reasons. It features an auto-scheduling function that selects the best time for your audience, and allows you to post more, high-quality content in less time.

This video will show you the basics:

Zerofox is an app that alerts you to threatening or offensive content in your feeds and comments. With trust in businesses at record lows, you'll want to protect your audience and reputation from fraud, impostor accounts, phishing and spam.

Here's a quick demo so you can see it in action.

Manage conversations and mentions across all of your platforms from one dashboard. Use the Saved Replies feature to quickly and consistently address common interactions.

You can also integrate your favourite CRM platform (like Salesforce or Microsoft Dynamics 365) in order to funnel incoming leads for your sales team.

Building a customized chatbot can help improve your customer support KPIs, like response times and customer satisfaction.

Your sales team can also use Chatfuel's bots to segment your customer personas or implement drip campaigns, as well as accept payments within the Facebook Messenger app.

Save money and time with this ad optimization tool. It will test your ads' effectiveness before you put your money behind them, and also ensure that you're targeting the right audiences with the right metrics for maximum ROI.

Automated, customized social media reports measure your content's performance as often as you like, so that you can get real-time updates and also high-level overviews for quarterly or annual review.

Pro tip: Having solid data at hand can free up your creativity. When you have proof about what works for your brand, fear of failure gets a bit less scary.

Social listening and monitoring can eat up a lot of time without the right tools. Analyze what your audience and industry is talking about to identify trends, risks, and make better marketing decisions.
Save time on social media by using Hootsuite. From a single dashboard you can plan and schedule content, respond to comments and @mentions, run ads, and measure performance. Try it for free today. Get Started
Try it for Free

Related Articles

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7 Social Media Automation Tools That Will Make Your Job Easier

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If you're spending more time fussing with hashtags or answering DMs than brainstorming new content ideas or planning your long term social media strategy, you could probably use a shortcut. It's time to consider social media automation. No, we're not talking about trying to bump up your vanity metrics by annoying people with weird bot comments.

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Automation can help maintain your business social media platform.

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Social Media Marketing & Management Dashboard

# data[].attributes.attachment_link.readable_text
If you're spending more time fussing with hashtags or answering DMs than brainstorming new content ideas or planning your long term social media strategy, you could probably use a shortcut. It's time to consider social media automation.

No, we're not talking about trying to bump up your vanity metrics by annoying people with weird bot comments. We're talking about tools that handle admin tasks like posting, monitoring and reporting, so that you can keep your social presence on-brand, up-to-date, and authentic, while spending less time on the day-to-day.

The thing about world-class social media automation is that-when it's done right-it can be pretty much invisible to the outside eye. That makes it tough to figure out what the pros are up to behind the scenes.

Read on to learn about the practices and tools social media experts use to save time and get results.

Bonus: Get a free social media strategy template to quickly and easily plan your own strategy. Also use it to track results and present the plan to your boss, teammates, and clients.

What is social media automation?

Social media automation is using software tools to handle some of the time-consuming tasks involved in maintaining a professional social media presence. For instance, scheduling posts ahead of time, curating content for republishing, triaging routine customer queries, and producing analytics reports are all examples of social media automation.

When it's done right, automating tedious or time-consuming tasks will free up your time so you can focus on the crucial, high-impact creative and strategic work that will move the needle on your real goals. Less time scrolling, more time selling.

However, not all social media tasks can or should be automated. Often the better-known kinds of automation are the ones that look lazy, spammy or fake.

For instance, paid Instagram bots that like, follow and comment are painfully obvious to savvy Instagram users. And using them is a very bad look for reputable brands.

Let's take a look at the kinds of automation that work, and the kinds that should be left in the grimy corners of digital marketing.

The DOs and DON'Ts of social media marketing automation

Integrating social media automation into your workflow can take a bit of initial legwork, especially if you're used to doing everything yourself. Same if you're part of a bigger, more complex department and need to court buy-in from your team.

Well, here are some tips to keep your efforts focused in the right direction.

DON'T post the same message to every network

Cross-posting the same text across all of your social accounts might save a few minutes, but the cost in credibility is high. If a tool (including the social platform itself) offers you the option to automatically cross-post to other platforms, you almost certainly want to decline.

Audiences on different platforms have different expectations, demographics, and vocabularies, and failing to recognize that can look sloppy or out-of-touch. Instead, take the extra time to adjust your message for each platform's audience. At the bare minimum, you'll want to:

Check and adjust user handles

Check and adjust image specs (file type, size, cropping, etc.)

Check and adjust hashtags (number and usage)

Check and adjust your vocabulary (i.e., retweet vs. regram vs. share)

DO post on your audience's schedule

As marketers, everything we do is tailored to our audiences, and that includes posting when they're online, not-alas-when we have a spare second between meetings.

There are two steps you need to take in order to optimize and automate your posting schedule:

1. Use a scheduling tool to craft your posts ahead of time;

2. Evaluate your analytics and schedule your posts for when your audience is on the platform.

Your social media posting schedule will be affected by which platforms you're focusing on, and your particular audience's habits. You can use the standard overall best time to post to social media platforms, and you can evaluate for your audience specifically using analytics tools.

DON'T "set it and forget it"

Even with legitimate social media automation, remember your tools don't have good judgement. In fact, they don't have any judgement at all. If you set an evergreen post to tweet every Friday at 11am eternally, it will do so without shame or remorse. (And no content is that evergreen.)

Whether you're a solopreneur or part of a big corporate team, use a tool with built-in, customizable approval processes to make sure that your posts are copyedited, on-brand and don't have any embarrassing mistakes.

(Source: @McDonalds -kudos to their social team for keeping this hilarious mistake up for the last three years for everyone's enjoyment.)

The other risk with going "hands-free" on your social scheduling tool is that world-changing crises happen all the time on social media, and a poorly timed post can make your brand look out-of-touch or tone deaf.

Pro tip: Batch-schedule your posts, but know what's happening internally and out in the world. Just because your car's got cruise control doesn't mean you can take your eyes off the road, Elon.

DON'T automate your behavior or comments

On social-as in life-one size definitely does not fit all. At Hootsuite, we've run automation experiments to test out various bot services. Long story short: their promises don't pan out, and they can cause lasting damage to your relationships with your audience. (Believe me, if automated comments worked, I would be first in line for a bot to handle my family group chat.)

Using bots to follow/unfollow people, like posts, or-worst of all-leave prefabricated comments, can put your reputation at risk. First impressions are crucial, and you don't want your interactions with potential customers to look fake, inane, or lazy, leaving a bad taste in their mouths.

And just to be clear, it's probably not a good idea to make a bunch of bots to hype your brand, either.

The time you spend keeping your relationships authentic and human will pay off in your analytics and social media ROI.

Pro tip: When it comes to conversations, the more legitimate form of automation is a tool that can handle your DMs, comments, tags in one place, consistently, at scale. For instance, Hootsuite Inbox's semi-automated Saved Replies feature lets you cycle through appropriate, authentic text based on the conversation and your customer's needs.

DO offer customer support 24/7

When it comes to customer support, 64% of people would rather message a brand on social than make a phone call. And 76% of messages that businesses receive on social are customer-service related.

You have three options for responding to customer service inquiries:

1. Pay to have customer service agents on deck around the clock

2. Use automated bots to manage expectations and direct inquiries

3. Leave your customers on read (A.K.A. ignore them)

These days, expectations for customer service on social are a little different than public-facing conversations. It's generally ok-and even expected-to have a chatbot or auto-response in place to handle straightforward inquiries, and appropriately direct customer service requests.

Get the template now!

Pro tip: Look into Facebook Messenger bots, or keep reading for our recommended automated customer support tools.

DO listen to the conversation

No doubt there are people in your life (hopefully not your manager, but probably your parents) who think that your job, as a social media manager, is to sit around watching TikTok all day. We can't help you with your mom (mine tells her friends my job is "writing those spam emails") but I want to reassure you that I really respect that you are trying to watch TikTok efficiently.

Social listening tools flag conversations, topics, and mentions so that you can stay informed about what's happening on social without getting seduced by the algorithm. Social listening is the most efficient way to:

Overall, with the right tools, social listening is one of the best ways to boost engagement. Check out our favourite tools in the list at the end.

DON'T babysit your ads

Ads cost money, and poorly optimized ads cost more money. The added pressure of a diminishing budget can make it tough to tear yourself away from your ads dashboards. But rather than spending your day staring at your cost per clicks and fussing with your ad metrics, consider automating key steps in your social media ads.

Organic and paid social usually demand different strategies, but the thing about ads is that they're so data-driven that automation is the best strategy, here.

One of the easiest shortcuts is a tool (like, for instance, Hootsuite Boost) that can automatically promote your top-performing organic content. If you have a home-run post on your hands you'll want to throw some dollars at it to make sure it has the best chance of snowballing. For instance, a post that gets 2x your average number of shares is something you likely want to show to a wider audience. Hootsuite Boost automates that trigger so it happens whether you're at your desk staring at it, or not.

Bonus tip: Split-testing (or A/B testing) your social ads is pretty much mandatory if you want to hit your KPIs, but consigning yourself to testing ads by hand is cruel and unusual self-punishment. Using a split-testing tool like AdEspresso might sound like a mathy extra step, but once you have it set up it'll improve your results with little ongoing effort on your part.

7 social media automation tools to do it right

Now that we've gone over the best practices for automating your social media presence to save time, let's look at the top tools you can use to make it happen.

This is our favourite social media scheduling tool for obvious reasons. It features an auto-scheduling function that selects the best time for your audience, and allows you to post more, high-quality content in less time.

This video will show you the basics:

Zerofox is an app that alerts you to threatening or offensive content in your feeds and comments. With trust in businesses at record lows, you'll want to protect your audience and reputation from fraud, impostor accounts, phishing and spam.

Here's a quick demo so you can see it in action.

Manage conversations and mentions across all of your platforms from one dashboard. Use the Saved Replies feature to quickly and consistently address common interactions.

You can also integrate your favourite CRM platform (like Salesforce or Microsoft Dynamics 365) in order to funnel incoming leads for your sales team.

Building a customized chatbot can help improve your customer support KPIs, like response times and customer satisfaction.

Your sales team can also use Chatfuel's bots to segment your customer personas or implement drip campaigns, as well as accept payments within the Facebook Messenger app.

Save money and time with this ad optimization tool. It will test your ads' effectiveness before you put your money behind them, and also ensure that you're targeting the right audiences with the right metrics for maximum ROI.

Automated, customized social media reports measure your content's performance as often as you like, so that you can get real-time updates and also high-level overviews for quarterly or annual review.

Pro tip: Having solid data at hand can free up your creativity. When you have proof about what works for your brand, fear of failure gets a bit less scary.

Social listening and monitoring can eat up a lot of time without the right tools. Analyze what your audience and industry is talking about to identify trends, risks, and make better marketing decisions.
Save time on social media by using Hootsuite. From a single dashboard you can plan and schedule content, respond to comments and @mentions, run ads, and measure performance. Try it for free today. Get Started
Try it for Free

Related Articles

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7 Social Media Automation Tools That Will Make Your Job Easier

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If you're spending more time fussing with hashtags or answering DMs than brainstorming new content ideas or planning your long term social media strategy, you could probably use a shortcut. It's time to consider social media automation. No, we're not talking about trying to bump up your vanity metrics by annoying people with weird bot comments.

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There are several ways companies can go green.

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Manufacturing Trends

Everyone is "going green" nowadays, from solar-powered USB bikinis to repurposing children's artwork.

And manufacturing companies are leading the way.

With around 315 million manufacturing workers worldwide, companies are figuring out new ways to create green manufacturing plants to retain employees and keep job satisfaction high.

Legal needs, rules, and regulations, and reducing the carbon footprint aren't the only ways to encourage going green. There are several monetary incentives to create green manufacturing plants as well, such as tax savings, reduced costs, and increased productivity.

According to McKinsey & Company, using the right technology in manufacturing will lower costs in the range of $200 to $600 billion across the industry. It really pays to go green.

With that in mind, let's take a look at how manufacturing companies can go green and save money at the same time.

1. Use Circular Manufacturing to Save Energy and Reduce Waste

Recovering resources and repurposing the materials

Lending equipment as a part of the sharing economy

Using predictive maintenance to increase the lifetime value and durability of machines and equipment

Switching to a renewable power source that provides energy to the factories

Manufacturing equipment and companies are becoming more sustainable by creating a regenerative model that fuels their facilities. Circular manufacturing is also called lean manufacturing and it includes:

1. It follows "green" rules and regulations.

2. It's good for the planet

3. It's what the end customers want

Circular manufacturing is a green solution with a three-fold win.

Instead of purchasing raw materials for themselves, green plants simply use the waste produced by another plant (water, energy, and other resources) to meet their needs.

A great example of this is Kalundborg Symbiosis - a group of nine manufacturing companies from Denmark who have been trading waste since 1961. Annually, they save 24 million EUR and reduce carbon emission by 635,000 tons.

2. Implement Safety Measures by Utilizing Automation Tools, AI, IoT, and Cobots

The cloud-based technology, alongside the Internet of Things (IoT) will provide the ability for humans to work alongside automation tools, AI, and cobots, and is one of the ways for companies to go green.

Cobots, or collaborative robots, are intended to work alongside humans in a shared space to complete tasks. IoT will help us navigate the entire manufacturing process, enabling humans to coordinate dangerous jobs with robots. And this is where cobots come into play.

The manufacturing industry has some of the highest rates of on-the-job safety incidents, with an estimated average of 400,000 non-fatal injuries per year. To avoid these injuries and prevent further harm, AI and cobots will perform dangerous tasks and that will decrease the number of injuries per year.

That will turn factories into safer work environments.

But that's not the only benefit. The increased safety measures will result in less downtime for employees and it will reduce the machine reparation downtime since they will go through predictive maintenance. Productivity will rise ( 40% by 2035) and there won't be the (energy) costs of restarting the machines, all the while creating a safer work environment for humans.

But that can only be fully implemented with digitized, internal communication.

3. Digitize Internal Communication

By making all internal communication 100% digital, you're not only saving tons of paper each year, but you're also making your overall operations more efficient.

Better communication improves operations. And real-time, mobile communication is becoming an increasingly popular way to enable frontline manufacturing workers.

Alerting other workers of any hazards and equipment failures which is critical for safety

You can keep the manufacturing pace high by communicating important messages (like shift-changes) fast

It saves time and money by being able to send (and receive) messages instantly (no bulletin boards)

Improves coordination between employees

Improves coordination between employees and managers

Enables employees to manage AI, robots, and cobots using mobile tech tools

Communicating in real-time has multiple benefits:
A digitally connected workforce is faster, safer, more productive, and greener.

According to Deloitte, 77% of manufacturing companies see "online collaboration platforms" as tools that will significantly impact their workforce in the next five years.

And the mobile-first communication tools allow employees to become partners with their peers, managers, and even machines.

This also rebrands the manufacturing plants into green, tech-advanced plants that attract the attention of the new people inside the workforce- millennials.

4. Implement Eco-friendly Products

According to the U.S. Bureau of Labor Statistics, millennials will make up around 75% of the entire workforce by 2030.

So in a matter of 10 years, you will have a workforce that deeply cares about sustainability in the workplace, and companies will have to adjust how they operate to attract the next generation of manufacturing workers.

One of the best ways to encourage going green in a manufacturing plant is to implement eco-friendly products. Not only are these products more sustainable, but they also cut costs for the company at the same time.

Lighting systems are a great example of this.

Being mindful of lighting systems can really affect your monthly electricity bill and even save up on energy. One way to do this is to change incandescent lights into LED lights. Not only are they more effective ( last 25 times longer than incandescent), but they are a green solution since they use 75% less energy than regular lights. That makes a massive difference on the scale of manufacturing plants, especially in the long run.

Taking small steps towards creating a more sustainably run manufacturing plant can have a big impact in the long run and get your company that much closer to being completely green.

Discover how manufacturing will become more sustainable in the coming years. Download our white paper, "Manufacturing Industry Trends" today!

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4 Novel Ways to Transform Your Factory into a Green Manufacturing Plant - Beekeeper

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Manufacturing Trends Everyone is "going green" nowadays, from solar-powered USB bikinis to repurposing children's artwork. And manufacturing companies are leading the way. With around 315 million manufacturing workers worldwide, companies are figuring out new ways to create green manufacturing plants to retain employees and keep job satisfaction high.

# data[].attributes.body
Slotosch, A. (2021, February 23). 4 novel ways to transform your factory into a Green manufacturing plant. Retrieved March 07, 2021, from https://www.beekeeper.io/blog/4-ways-manufacturing-companies-can-go-green/

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Manufacturing Trends

Everyone is "going green" nowadays, from solar-powered USB bikinis to repurposing children's artwork.

And manufacturing companies are leading the way.

With around 315 million manufacturing workers worldwide, companies are figuring out new ways to create green manufacturing plants to retain employees and keep job satisfaction high.

Legal needs, rules, and regulations, and reducing the carbon footprint aren't the only ways to encourage going green. There are several monetary incentives to create green manufacturing plants as well, such as tax savings, reduced costs, and increased productivity.

According to McKinsey & Company, using the right technology in manufacturing will lower costs in the range of $200 to $600 billion across the industry. It really pays to go green.

With that in mind, let's take a look at how manufacturing companies can go green and save money at the same time.

1. Use Circular Manufacturing to Save Energy and Reduce Waste

Recovering resources and repurposing the materials

Lending equipment as a part of the sharing economy

Using predictive maintenance to increase the lifetime value and durability of machines and equipment

Switching to a renewable power source that provides energy to the factories

Manufacturing equipment and companies are becoming more sustainable by creating a regenerative model that fuels their facilities. Circular manufacturing is also called lean manufacturing and it includes:

1. It follows "green" rules and regulations.

2. It's good for the planet

3. It's what the end customers want

Circular manufacturing is a green solution with a three-fold win.

Instead of purchasing raw materials for themselves, green plants simply use the waste produced by another plant (water, energy, and other resources) to meet their needs.

A great example of this is Kalundborg Symbiosis - a group of nine manufacturing companies from Denmark who have been trading waste since 1961. Annually, they save 24 million EUR and reduce carbon emission by 635,000 tons.

2. Implement Safety Measures by Utilizing Automation Tools, AI, IoT, and Cobots

The cloud-based technology, alongside the Internet of Things (IoT) will provide the ability for humans to work alongside automation tools, AI, and cobots, and is one of the ways for companies to go green.

Cobots, or collaborative robots, are intended to work alongside humans in a shared space to complete tasks. IoT will help us navigate the entire manufacturing process, enabling humans to coordinate dangerous jobs with robots. And this is where cobots come into play.

The manufacturing industry has some of the highest rates of on-the-job safety incidents, with an estimated average of 400,000 non-fatal injuries per year. To avoid these injuries and prevent further harm, AI and cobots will perform dangerous tasks and that will decrease the number of injuries per year.

That will turn factories into safer work environments.

But that's not the only benefit. The increased safety measures will result in less downtime for employees and it will reduce the machine reparation downtime since they will go through predictive maintenance. Productivity will rise ( 40% by 2035) and there won't be the (energy) costs of restarting the machines, all the while creating a safer work environment for humans.

But that can only be fully implemented with digitized, internal communication.

3. Digitize Internal Communication

By making all internal communication 100% digital, you're not only saving tons of paper each year, but you're also making your overall operations more efficient.

Better communication improves operations. And real-time, mobile communication is becoming an increasingly popular way to enable frontline manufacturing workers.

Alerting other workers of any hazards and equipment failures which is critical for safety

You can keep the manufacturing pace high by communicating important messages (like shift-changes) fast

It saves time and money by being able to send (and receive) messages instantly (no bulletin boards)

Improves coordination between employees

Improves coordination between employees and managers

Enables employees to manage AI, robots, and cobots using mobile tech tools

Communicating in real-time has multiple benefits:
A digitally connected workforce is faster, safer, more productive, and greener.

According to Deloitte, 77% of manufacturing companies see "online collaboration platforms" as tools that will significantly impact their workforce in the next five years.

And the mobile-first communication tools allow employees to become partners with their peers, managers, and even machines.

This also rebrands the manufacturing plants into green, tech-advanced plants that attract the attention of the new people inside the workforce- millennials.

4. Implement Eco-friendly Products

According to the U.S. Bureau of Labor Statistics, millennials will make up around 75% of the entire workforce by 2030.

So in a matter of 10 years, you will have a workforce that deeply cares about sustainability in the workplace, and companies will have to adjust how they operate to attract the next generation of manufacturing workers.

One of the best ways to encourage going green in a manufacturing plant is to implement eco-friendly products. Not only are these products more sustainable, but they also cut costs for the company at the same time.

Lighting systems are a great example of this.

Being mindful of lighting systems can really affect your monthly electricity bill and even save up on energy. One way to do this is to change incandescent lights into LED lights. Not only are they more effective ( last 25 times longer than incandescent), but they are a green solution since they use 75% less energy than regular lights. That makes a massive difference on the scale of manufacturing plants, especially in the long run.

Taking small steps towards creating a more sustainably run manufacturing plant can have a big impact in the long run and get your company that much closer to being completely green.

Discover how manufacturing will become more sustainable in the coming years. Download our white paper, "Manufacturing Industry Trends" today!

# data[].attributes.attachment_link.title
4 Novel Ways to Transform Your Factory into a Green Manufacturing Plant - Beekeeper

# data[].attributes.attachment_link.description
Manufacturing Trends Everyone is "going green" nowadays, from solar-powered USB bikinis to repurposing children's artwork. And manufacturing companies are leading the way. With around 315 million manufacturing workers worldwide, companies are figuring out new ways to create green manufacturing plants to retain employees and keep job satisfaction high.

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Can automation have a negative effect on environment?

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There seems little doubt the Fourth Industrial Revolution-and particularly the uptake of digital and highly automated systems-will transform our economies in coming decades.

Effects of that transformation are the subject of multiple debates, such as those currently happening at Davos, and there are multiple signals that the spread of artificial intelligence, the Internet of Things, advanced robotics, 3D printing and autonomous transport are set to change society as we know it.

One major stream of conversation about the forthcoming transformation has focused on the changing role of human labour in an age of automation. Indeed, existing technologies already allow automation of half of all activities people are currently paid to do. They also significantly transform current business models and producer-customer relationships and create new employment opportunities for those able to use them. With a good chunk of the global labour force expected to be looking for new jobs by 2030, a robust response is obviously needed to manage adverse social side effects.

But what impact will all this have on energy use, natural resource use and the environment?

A greener, more equitable world won't be an automatic outcome of the digital revolution.

Upsides and Downsides

If carefully managed, changes in production and consumption patterns could create environmental improvements compared with the processes used today. But without proper environmental objectives and management systems, automation alone could have significant adverse impacts-especially on energy use (and emissions generated from the current energy mix), resource use and ecosystems. The figure below visualizes the best- and worst-case scenarios of these disruptive innovations.

Best- and worst-case scenarios of these disruptive innovations

Many emerging technologies offer the potential to reduce emissions. They could also theoretically improve resource-use efficiency, provided increased efficiency does not trigger over-consumption. This is a big "if," since customer relationships are increasingly based on detailed digital surveillance of behavioural patterns and involve highly effective marketing techniques that can ramp up demand for products or services.

On the other hand, changes in both consumption and production patterns increase the total demand for electricity and can easily raise greenhouse gas emissions, depending on the carbon footprints of the power sources used. They could also enhance unsustainable exploitation of natural resources-especially if our dependency on rare metals for production of electronic equipment further deepens. Proliferation of all sorts of electronic equipment and future composite materials also bring new challenges for recycling and waste management.

Lastly, potential large-scale dislocation of the labour force-particularly in low-/middle-income export-oriented economies with high population growth rates-could lead to a return migration to rural areas and increased use of available natural resources for livelihood purposes. This may worsen already significant pressures on ecosystems.

Double-Edged Swords

Considering these facts, there are no upfront guarantees new technological capabilities will automatically foster environmental sustainability. The forthcoming disruptive technologies are double-edged swords that may generate diverse outcomes based on the intentions and skills of their users.

Automation's impact on employment has captured popular interest (and concerns), but what about the environment?

Thus, it's a good time to explore the linkages between these new technologies, the changing economic premises that will accompany their deployment, emerging patterns of production and consumption, and their potential environmental and social impacts. Such an enquiry may be guided by (even if not limited to) global aspirations to reach the Sustainable Development Goals.

From that perspective, the ongoing technological transformation could be strengthened by the use of economic instruments, especially those that: (a) incorporate environmental and natural resource use externalities of emerging business models, products and services; (b) promote resource- and emission-saving innovations; and (c) potentially also generate revenue for social support programs that may need to accompany a transition to new occupations and sources of livelihood. Other mitigation and enhancement options could be identified as our understanding evolves.

As the founder of the World Economic Forum, Klaus Schwab, rightly noted, before we devise strategies to cope with the Fourth Industrial Revolution, we first need to better understand it.

To that end, interested experts are invited to analyze the range of environmental impacts of forthcoming technological changes and their interaction with economic and social considerations. A preliminary scoping paper is available at Research Gate, and we invite interested parties to identify emerging issues of concern, give comments and suggest potential future steps for a deliberative enquiry (including a possible open discussion forum).

A greener, more equitable world won't be an automatic outcome of the digital revolution. It's our duty to shape its development even as its pace takes our breath away.

---
Jiri Dusik is a Technical Specialist with UNDP Viet Nam. Barry Sadler is an Environment and Sustainability Analyst. Opinions expressed are those of the authors and do not necessarily reflect views of the United Nations Development Programme.

# data[].attributes.attachment_link.title
What Effect Will Automation Have on the Environment?

# data[].attributes.attachment_link.description
There seems little doubt the Fourth Industrial Revolution-and particularly the uptake of digital and highly automated systems-will transform our economies in coming decades. Effects of that transformation are the subject of multiple debates, such as those currently happening at Davos, and there are multiple signals that the spread of artificial intelligence, the Internet of Things, advanced robotics, 3D printing and autonomous transport are set to change society as we know it.

# data[].attributes.body
Dusik, J., & Sadler, B. (2019, January 22). What effect will automation have on the environment? Retrieved March 07, 2021, from https://www.iisd.org/articles/automation-environment

# data[].attributes.attachment_link.readable_text
There seems little doubt the Fourth Industrial Revolution-and particularly the uptake of digital and highly automated systems-will transform our economies in coming decades.

Effects of that transformation are the subject of multiple debates, such as those currently happening at Davos, and there are multiple signals that the spread of artificial intelligence, the Internet of Things, advanced robotics, 3D printing and autonomous transport are set to change society as we know it.

One major stream of conversation about the forthcoming transformation has focused on the changing role of human labour in an age of automation. Indeed, existing technologies already allow automation of half of all activities people are currently paid to do. They also significantly transform current business models and producer-customer relationships and create new employment opportunities for those able to use them. With a good chunk of the global labour force expected to be looking for new jobs by 2030, a robust response is obviously needed to manage adverse social side effects.

But what impact will all this have on energy use, natural resource use and the environment?

A greener, more equitable world won't be an automatic outcome of the digital revolution.

Upsides and Downsides

If carefully managed, changes in production and consumption patterns could create environmental improvements compared with the processes used today. But without proper environmental objectives and management systems, automation alone could have significant adverse impacts-especially on energy use (and emissions generated from the current energy mix), resource use and ecosystems. The figure below visualizes the best- and worst-case scenarios of these disruptive innovations.

Best- and worst-case scenarios of these disruptive innovations

Many emerging technologies offer the potential to reduce emissions. They could also theoretically improve resource-use efficiency, provided increased efficiency does not trigger over-consumption. This is a big "if," since customer relationships are increasingly based on detailed digital surveillance of behavioural patterns and involve highly effective marketing techniques that can ramp up demand for products or services.

On the other hand, changes in both consumption and production patterns increase the total demand for electricity and can easily raise greenhouse gas emissions, depending on the carbon footprints of the power sources used. They could also enhance unsustainable exploitation of natural resources-especially if our dependency on rare metals for production of electronic equipment further deepens. Proliferation of all sorts of electronic equipment and future composite materials also bring new challenges for recycling and waste management.

Lastly, potential large-scale dislocation of the labour force-particularly in low-/middle-income export-oriented economies with high population growth rates-could lead to a return migration to rural areas and increased use of available natural resources for livelihood purposes. This may worsen already significant pressures on ecosystems.

Double-Edged Swords

Considering these facts, there are no upfront guarantees new technological capabilities will automatically foster environmental sustainability. The forthcoming disruptive technologies are double-edged swords that may generate diverse outcomes based on the intentions and skills of their users.

Automation's impact on employment has captured popular interest (and concerns), but what about the environment?

Thus, it's a good time to explore the linkages between these new technologies, the changing economic premises that will accompany their deployment, emerging patterns of production and consumption, and their potential environmental and social impacts. Such an enquiry may be guided by (even if not limited to) global aspirations to reach the Sustainable Development Goals.

From that perspective, the ongoing technological transformation could be strengthened by the use of economic instruments, especially those that: (a) incorporate environmental and natural resource use externalities of emerging business models, products and services; (b) promote resource- and emission-saving innovations; and (c) potentially also generate revenue for social support programs that may need to accompany a transition to new occupations and sources of livelihood. Other mitigation and enhancement options could be identified as our understanding evolves.

As the founder of the World Economic Forum, Klaus Schwab, rightly noted, before we devise strategies to cope with the Fourth Industrial Revolution, we first need to better understand it.

To that end, interested experts are invited to analyze the range of environmental impacts of forthcoming technological changes and their interaction with economic and social considerations. A preliminary scoping paper is available at Research Gate, and we invite interested parties to identify emerging issues of concern, give comments and suggest potential future steps for a deliberative enquiry (including a possible open discussion forum).

A greener, more equitable world won't be an automatic outcome of the digital revolution. It's our duty to shape its development even as its pace takes our breath away.

---
Jiri Dusik is a Technical Specialist with UNDP Viet Nam. Barry Sadler is an Environment and Sustainability Analyst. Opinions expressed are those of the authors and do not necessarily reflect views of the United Nations Development Programme.

# data[].attributes.attachment_link.title
What Effect Will Automation Have on the Environment?

# data[].attributes.attachment_link.description
There seems little doubt the Fourth Industrial Revolution-and particularly the uptake of digital and highly automated systems-will transform our economies in coming decades. Effects of that transformation are the subject of multiple debates, such as those currently happening at Davos, and there are multiple signals that the spread of artificial intelligence, the Internet of Things, advanced robotics, 3D printing and autonomous transport are set to change society as we know it.

# data[].attributes.body
Going green and automating factories can save manufacturers money.

# data[].attributes.attachment_link.readable_text
Factory automation, often referred to as industrial automation, is the use of control systems to operate processes without human intervention. These systems generally include software, computers, and robotics. The benefits of automation include increases in productivity, accuracy, flexibility, and worker safety while providing overall cost savings. These cost savings for the manufacturer can be transferred to the customer.

The current trend in industrial automation is shifting toward smart manufacturing and Robotic Process Automation (RPA). Through the use of IoT connected devices, data analytics, robotics, RPA practices, and machine learning/artificial intelligence, the concept of "Smart Manufacturing" will lead to an overall more effective and efficient workplace that is both safer for workers and more profitable for employers. One of the great benefits of smart manufacturing and controlled RPA is the ability to create greener factories and, gradually, an overall healthier environment.

Manufacturing processes use nearly one-quarter of the energy in the United States and one-third of the energy across the globe. Manufacturers are beginning to realize that going green is not only good for the environment, it's good for their bottom line. While building green factories may require initial fees up front, going green can save companies money overall. In 2013, the International Energy Agency stated that manufacturers wasted $80B worth of electricity because of outdated manufacturing processes. Updating their manufacturing processes to have a more favorable ecological impact will also make companies more popular with consumers, as indicated by a recent Nielsen survey.

With more automated and "smarter" factories come numerous environmental benefits, of which a few are listed here:

Manufacturers can use analytics to adjust energy loads on machines

Lower heating requirements

Minimal material waste through robots streamlining operations

Lower cycle times and increased production, leading to less energy output

Combining/streamlining processes and the compactness of some robotics, which can reduce the need for factory floor space

A large number of industries are implementing environmentally friendly automation systems, such as:

The Automotive industry,

Agriculture industry,

Aerospace industry,

and food and beverage industry

Even the beer industry is concerned with decreasing energy usage in manufacturing. In 2016, a North American brewer contacted JMP Automation, an industry leader in providing Smart Robotic Solutions, for assistance with a strategy to reduce its energy consumption. JMP was able to assist the brewer in reducing the energy costs associated with ammonia compression.

Within the automation industry, there are specific products that manufacturers have designed to be more energy efficient. Within manufacturing, electric motors drain the greatest amount of power. However, certain electric motors have higher performance and reliability ratings, which can lead to decreased energy consumption. Manufacturers use these motors in factories to act as generators and provide mechanical or hydraulics capabilities.

In addition to the motor's high performance and reliability, the motors can:

provide precision for acceleration and deceleration control, which reduces energy lost as heat

sense current flows and make adjustments leading to 30% to 40% savings in power usage

These GE Fanuc products are a good example of a type of motor that can be purchased and installed in order to significantly lower environmental impacts. In addition to saving energy, manufacturers who use more environmentally-friendly factories can then also focus on sustainability as part of an environmental strategy; to ensure enduring success with their customer base, companies know that they must keep their customers happy. Preserving the environment is something that is important to many consumers. As such, companies are trying to employ goods in a way that protect the environment.

# data[].attributes.attachment_link.title
Factory automation and environmental benefits

# data[].attributes.attachment_link.description
Factory automation, often referred to as industrial automation, is the use of control systems to operate processes without human intervention. These systems generally include software, computers, and robotics. The benefits of automation include increases in productivity, accuracy, flexibility, and worker safety while providing overall cost savings.

# data[].attributes.body
Tomas, T. (2018, July 17). Factory automation and environmental benefits. Retrieved March 07, 2021, from https://www.geospatialworld.net/blogs/factory-automation-and-environmental-benefits/#:~:text=Lower heating requirements,need for factory floor space

# data[].attributes.attachment_link.readable_text
Factory automation, often referred to as industrial automation, is the use of control systems to operate processes without human intervention. These systems generally include software, computers, and robotics. The benefits of automation include increases in productivity, accuracy, flexibility, and worker safety while providing overall cost savings. These cost savings for the manufacturer can be transferred to the customer.

The current trend in industrial automation is shifting toward smart manufacturing and Robotic Process Automation (RPA). Through the use of IoT connected devices, data analytics, robotics, RPA practices, and machine learning/artificial intelligence, the concept of "Smart Manufacturing" will lead to an overall more effective and efficient workplace that is both safer for workers and more profitable for employers. One of the great benefits of smart manufacturing and controlled RPA is the ability to create greener factories and, gradually, an overall healthier environment.

Manufacturing processes use nearly one-quarter of the energy in the United States and one-third of the energy across the globe. Manufacturers are beginning to realize that going green is not only good for the environment, it's good for their bottom line. While building green factories may require initial fees up front, going green can save companies money overall. In 2013, the International Energy Agency stated that manufacturers wasted $80B worth of electricity because of outdated manufacturing processes. Updating their manufacturing processes to have a more favorable ecological impact will also make companies more popular with consumers, as indicated by a recent Nielsen survey.

With more automated and "smarter" factories come numerous environmental benefits, of which a few are listed here:

Manufacturers can use analytics to adjust energy loads on machines

Lower heating requirements

Minimal material waste through robots streamlining operations

Lower cycle times and increased production, leading to less energy output

Combining/streamlining processes and the compactness of some robotics, which can reduce the need for factory floor space

A large number of industries are implementing environmentally friendly automation systems, such as:

The Automotive industry,

Agriculture industry,

Aerospace industry,

and food and beverage industry

Even the beer industry is concerned with decreasing energy usage in manufacturing. In 2016, a North American brewer contacted JMP Automation, an industry leader in providing Smart Robotic Solutions, for assistance with a strategy to reduce its energy consumption. JMP was able to assist the brewer in reducing the energy costs associated with ammonia compression.

Within the automation industry, there are specific products that manufacturers have designed to be more energy efficient. Within manufacturing, electric motors drain the greatest amount of power. However, certain electric motors have higher performance and reliability ratings, which can lead to decreased energy consumption. Manufacturers use these motors in factories to act as generators and provide mechanical or hydraulics capabilities.

In addition to the motor's high performance and reliability, the motors can:

provide precision for acceleration and deceleration control, which reduces energy lost as heat

sense current flows and make adjustments leading to 30% to 40% savings in power usage

These GE Fanuc products are a good example of a type of motor that can be purchased and installed in order to significantly lower environmental impacts. In addition to saving energy, manufacturers who use more environmentally-friendly factories can then also focus on sustainability as part of an environmental strategy; to ensure enduring success with their customer base, companies know that they must keep their customers happy. Preserving the environment is something that is important to many consumers. As such, companies are trying to employ goods in a way that protect the environment.

# data[].attributes.attachment_link.title
Factory automation and environmental benefits

# data[].attributes.attachment_link.description
Factory automation, often referred to as industrial automation, is the use of control systems to operate processes without human intervention. These systems generally include software, computers, and robotics. The benefits of automation include increases in productivity, accuracy, flexibility, and worker safety while providing overall cost savings.

# data[].attributes.body
Necklen, P. (2020, March 26). Prioritizing Automation to Help Your Business Adapt in 2020 [Web log post]. Retrieved February 27, 2021, from https://www.helpsystems.com/blog/prioritizing-automation-help-your-business-adapt-2020

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About the Author

Paul is an RPA expert and evangelist. For over 15 years, he has been successfully solving key business problems with software solutions. At HelpSystems, Paul is a key part of helping businesses find the best way to deploy RPA in their organizations to generate value. ...

# data[].attributes.attachment_link.title
Prioritizing Automation to Help Your Business Adapt in 2020

# data[].attributes.attachment_link.description
About the Author Paul is an RPA expert and evangelist. For over 15 years, he has been successfully solving key business problems with software solutions. At HelpSystems, Paul is a key part of helping businesses find the best way to deploy RPA in their organizations to generate value. ...

# data[].attributes.body
People losing their jobs to machines is bad, but can it bring more stability to times like the pandemic when people can't work?

# data[].attributes.attachment_link.readable_text
About the Author

Paul is an RPA expert and evangelist. For over 15 years, he has been successfully solving key business problems with software solutions. At HelpSystems, Paul is a key part of helping businesses find the best way to deploy RPA in their organizations to generate value. ...

# data[].attributes.attachment_link.title
Prioritizing Automation to Help Your Business Adapt in 2020

# data[].attributes.attachment_link.description
About the Author Paul is an RPA expert and evangelist. For over 15 years, he has been successfully solving key business problems with software solutions. At HelpSystems, Paul is a key part of helping businesses find the best way to deploy RPA in their organizations to generate value. ...

# data[].attributes.body
Even though products could become cheaper, is it ehtical if it means people losing their jobs?

# data[].attributes.body
Could it be considered unethical if companies hire new technicians to work the machines instead of training current employees that could lose their jobs?

# data[].attributes.body
Maxim, R., & Muro, M. (2019, February 25). Automation and AI will disrupt the American labor force. Here’s how we can protect workers [Web log post]. Retrieved February 20, 2021, from https://www.brookings.edu/blog/the-avenue/2019/02/25/automation-and-ai-will-disrupt-the-american-labor-force-heres-how-we-can-protect-workers/

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Automation and AI will disrupt the American labor force. Here's how we can protect workers

# data[].attributes.attachment_link.description
In order to protect workers, policymakers at all levels must step in with new investments to mitigate the impacts of automation.

# data[].attributes.body
What can companies do to help workers that could be replaced by automation?

# data[].attributes.attachment_link.title
Automation and AI will disrupt the American labor force. Here's how we can protect workers

# data[].attributes.attachment_link.description
In order to protect workers, policymakers at all levels must step in with new investments to mitigate the impacts of automation.

# data[].attributes.body
Instead of replacing workers with machines, could theses workers be trained to operate and maintain the machines?

# data[].attributes.body
Can machines make products cheaper?

# data[].attributes.attachment_link.readable_text
Many Americans have been experiencing massive economic insecurity and want to return to a time when they were able to earn a good living and create a decent life for themselves and their families. President Trump promised to deliver on that wish, to "Make America Great Again," by reducing business regulations, fixing trade deals, and stopping the loss of manufacturing jobs.

Some of those policies will help, but they're unlikely to fully address the challenges faced by the middle class.

The problem is that we are now living in a bipolar economy, with a traditional economy at one end and an autonomous economy at the other. The traditional economy is prone to inflation; the autonomous economy toward deflation.

Many middle-class Americans are earning their money in a deflationary economy where wages are falling, and spending it in a traditional economy where prices are rising. Those Americans trapped between the poles of the bipolar economy were among Trump's most enthusiastic supporters.

The traditional economy provides us with most of the basic necessities of life: food, shelter, health care, clothing, transportation, and energy. Money spent on these necessities account for 70% of middle-class expenditures. The prices of most of those expenditures are rising faster than inflation.

Property managers forecasted an 8% increase in rents in 2016. From 2012 to 2014, the median home price rose by 17.3%. The U.S. Department of Agriculture reported that food prices rose 31% from 2005 to 2014. The cost of health insurance has risen by over 44% in the past five years.

The autonomous economy is where intelligent machines, robots, artificial intelligence, big data, and high-speed digital communication power production. Those processes produce high-quality goods and services, frequently with little human involvement. The autonomous economy is extremely labor and capital efficient, sometimes so much so that the prices of its products decline to close to zero. Often the markets they supply shrink in size. Most concerning, the value of human work declines as workers compete with robots for jobs.

The transformation of the movie rental and physical media businesses are examples of what happens when businesses move from the traditional to the autonomous economy.

At one point, Blockbuster Video had 60,000 employees and 9,000 stores. Then it got absorbed into the virtual economy, replaced by Netflix and by Redbox kiosks. Netflix has around 2,450 employees.

This has been good news for consumers. Many movie watchers can now view their movies for free on ad-supported networks like Crackle, which is owned by Sony Pictures Entertainment.

In the meantime, the manufacturers and distributors of physical media are struggling. Blu-ray and DVD sales have suffered declines of more than 10% for the last two years. Even Redbox's revenue plunged by almost 19%.

If you work in an industry transitioning from the traditional to the autonomous economy - say, if until recently you worked at Blockbuster - but most of what you buy is in the traditional economy (rent, food, health care), you're probably not doing very well.

The shift toward the autonomous economy is happening in the services sector, too, which makes up 80% of the workforce. (For all our talk about manufacturing jobs, they account for less than 9% of the workforce). More and more services are delivered by computers transacting with other computers, such as when we make travel reservations, when machines manage our investment portfolios by trading stocks on electronic exchanges, when we shop online, and when systems generate our news feeds and negotiate with other computers over what ads will be presented to us.

While we have no good way of determining the precise amount of goods and services produced autonomously, we know it is very large. Brian Arthur, in his article on the Second Economy, or what he now calls the autonomous economy, estimated that, by 2025, autonomous production would produce goods and services equal to the country's GNP in 1995, about $7.5 trillion.

The shift to the autonomous economy and the pressure it places on workers are likely to only get worse. For an idea of the effects that autonomous production might have, consider the potential impact of the Level 4 Autonomous Vehicle, a car that drives itself and never needs human help.

Imagine that many consumers got rid of their cars and opted for driverless shared car services - a driverless Uber. If that displaced 20% of the 250 million cars Americans own, consumers would save $150 billion, $3,000 for every car displaced, and 1 million jobs would disappear in the automotive related industries - manufacturing, insurance, finance, etc.

There are 3.5 million professional truck drivers in our country, and about 8.7 million people are employed in the trucking business. If autonomous trucks displaced just 20% of them, another 1.75 million jobs would vanish.

The jobs of 200,000 cab and limo drivers, as well as those of 400,000 part-time Uber drivers, are at risk as well. If we could get by with 100,000 of them, the equivalent of somewhere around 250,000 full-time jobs would vanish.

Automated delivery vehicles would facilitate the deliveries from the Amazons of the world. Online retailers, like Amazon, employ about one-third the number of employees per dollar sold as conventional retailers do. If online retailers gained an additional 10% in market share, that would eliminate another 1 million jobs.

Under those assumptions, 4 million jobs would be displaced by the Level 4 Autonomous Vehicle.

Lost jobs have a multiplier effect. If jobs decline in the auto industry, jobs vanish in the automobile supply chain. People who lose jobs purchase fewer retail goods and eat out less often, so other jobs are lost as well.

Numbers vary dramatically about the size of the multiplier effect, but two is a pretty conservative guess. If a multiplier effect of two is used in the case of autonomous vehicles, a total of 12 million jobs would vanish in the scenario outlined above.

You might quibble with these numbers, but that is missing the point. The effects of the Level 4 Autonomous Vehicle will be very large. I personally believe these are conservative guesses.

Autonomous production exerts downward pressure on wages, as workers compete both with machines and with the new influx of job seekers whose jobs have already been replaced. And as we have seen, this process shifts many full-time jobs into the gig economy - places like Uber, TaskRabbit, etc. - where individuals work as independent contractors, without benefits.

It is easy to conclude in response to all of this that there will be a shortage of work in the future, and that we will have to consider other previously unthinkable solutions. Commentators across the political spectrum have proposed guaranteed annual incomes as a potential solution. Others have suggested that shorter workweeks would create more job opportunities. If coupled with aggressive earned income tax credits, these proposals could perhaps allow workers to earn a decent income. Some have proposed offering tax credits to people who perform socially useful work for which they receive no pay, such as someone who stays home from work to care for a child or elder.

Most of us, including myself, feel extremely uncomfortable with these types of ideas. But the autonomous economy is rewriting the economic rules, and so we shouldn't constrain our thinking.

It is comfortable to stick with the old solutions, ignore the likelihood that they will be insufficient, and just hope. But hope is not a strategy. It will only make the long-term problem worse.

Autonomous production is already unleashing a bipolar economic system, and with it some very tough social challenges. If we are really serious about change, we will have to do radical things to address inflation in the traditional economy and deflation in the autonomous one, in response to a world where the value of human work is under pressure.

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Automation Makes Things Cheaper, So Why Doesn't It Feel That Way?

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Many Americans have been experiencing massive economic insecurity and want to return to a time when they were able to earn a good living and create a decent life for themselves and their families. President Trump promised to deliver on that wish, to "Make America Great Again," by reducing business regulations, fixing trade deals, and stopping the loss of manufacturing jobs.

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People being replaced with machines.

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For 23 years, Larry Collins worked in a booth on the Carquinez Bridge in the San Francisco Bay Area, collecting tolls. The fare changed over time, from a few bucks to $6, but the basics of the job stayed the same: Collins would make change, answer questions, give directions and greet commuters. "Sometimes, you're the first person that people see in the morning," says Collins, "and that human interaction can spark a lot of conversation."

But one day in mid-March, as confirmed cases of the coronavirus were skyrocketing, Collins' supervisor called and told him not to come into work the next day. The tollbooths were closing to protect the health of drivers and of toll collectors. Going forward, drivers would pay bridge tolls automatically via FasTrak tags mounted on their windshields or would receive bills sent to the address linked to their license plate. Collins' job was disappearing, as were the jobs of around 185 other toll collectors at bridges in Northern California, all to be replaced by technology.

Machines have made jobs obsolete for centuries. The spinning jenny replaced weavers, buttons displaced elevator operators, and the Internet drove travel agencies out of business. One study estimates that about 400,000 jobs were lost to automation in U.S. factories from 1990 to 2007. But the drive to replace humans with machinery is accelerating as companies struggle to avoid workplace infections of COVID-19 and to keep operating costs low. The U.S. shed around 40 million jobs at the peak of the pandemic, and while some have come back, some will never return. One group of economists estimates that 42% of the jobs lost are gone forever.

More from TIME

This replacement of humans with machines may pick up more speed in coming months as companies move from survival mode to figuring out how to operate while the pandemic drags on. Robots could replace as many as 2 million more workers in manufacturing alone by 2025, according to a recent paper by economists at MIT and Boston University. "This pandemic has created a very strong incentive to automate the work of human beings," says Daniel Susskind, a fellow in economics at Balliol College, University of Oxford, and the author of A World Without Work: Technology, Automation and How We Should Respond. "Machines don't fall ill, they don't need to isolate to protect peers, they don't need to take time off work."

As with so much of the pandemic, this new wave of automation will be harder on people of color like Collins, who is Black, and on low-wage workers. Many Black and Latino Americans are cashiers, food-service employees and customer-service representatives, which are among the 15 jobs most threatened by automation, according to McKinsey. Even before the pandemic, the global consulting company estimated that automation could displace 132,000 Black workers in the U.S. by 2030.

The deployment of robots as a response to the coronavirus was rapid. They were suddenly cleaning floors at airports and taking people's temperatures. Hospitals and universities deployed Sally, a salad-making robot created by tech company Chowbotics, to replace dining-hall employees; malls and stadiums bought Knightscope security-guard robots to patrol empty real estate; companies that manufacture in-demand supplies like hospital beds and cotton swabs turned to industrial robot supplier Yaskawa America to help increase production.

Companies closed call centers employing human customer-service agents and turned to chatbots created by technology company LivePerson or to AI platform Watson Assistant. "I really think this is a new normal-the pandemic accelerated what was going to happen anyway," says Rob Thomas, senior vice president of cloud and data platform at IBM, which deploys Watson. Roughly 100 new clients started using the software from March to June.

In theory, automation and artificial intelligence should free humans from dangerous or boring tasks so they can take on more intellectually stimulating assignments, making companies more productive and raising worker wages. And in the past, technology was deployed piecemeal, giving employees time to transition into new roles. Those who lost jobs could seek retraining, perhaps using severance pay or unemployment benefits to find work in another field. This time the change was abrupt as employers, worried about COVID-19 or under sudden lockdown orders, rushed to replace workers with machines or software. There was no time to retrain. Companies worried about their bottom line cut workers loose instead, and these workers were left on their own to find ways of mastering new skills. They found few options.

In the past, the U.S. responded to technological change by investing in education. When automation fundamentally changed farm jobs in the late 1800s and the 1900s, states expanded access to public schools. Access to college expanded after World War II with the GI Bill, which sent 7.8 million veterans to school from 1944 to 1956. But since then, U.S. investment in education has stalled, putting the burden on workers to pay for it themselves. And the idea of education in the U.S. still focuses on college for young workers rather than on retraining employees. The country spends 0.1% of GDP to help workers navigate job transitions, less than half what it spent 30 years ago.

"The real automation problem isn't so much a robot apocalypse," says Mark Muro, a senior fellow at the Brookings Institution. "It is business as usual of people needing to get retraining, and they really can't get it in an accessible, efficient, well-informed, data-driven way."

This means that tens of thousands of Americans who lost jobs during the pandemic may be unemployed for years or, in Collins' case, for good. Though he has access to retraining funding through his union contract, "I'm too old to think about doing some other job," says Collins, who is 63 and planning on taking early retirement. "I just want to go back to what I was doing."

Check into a hotel today, and a mechanical butler designed by robotics company Savioke might roll down the hall to deliver towels and toothbrushes. ("No tip required," Savioke notes on its website.) Robots have been deployed during the pandemic to meet guests at their rooms with newly disinfected keys. A bricklaying robot can lay more than 3,000 bricks in an eight-hour shift, up to 10 times what a human can do. Robots can plant seeds and harvest crops, separate breastbones and carcasses in slaughterhouses, pack pallets of food in processing facilities.

That doesn't mean they're taking everyone's jobs. For centuries, humans from weavers to mill workers have worried that advances in technology would create a world without work, and that's never proved true. ATMs did not immediately decrease the number of bank tellers, for instance. They actually led to more teller jobs as consumers, lured by the convenience of cash machines, began visiting banks more often. Banks opened more branches and hired tellers to handle tasks that are beyond the capacity of ATMs. Without technological advancement, much of the American workforce would be toiling away on farms, which accounted for 31% of U.S. jobs in 1910 and now account for less than 1%.

But in the past, when automation eliminated jobs, companies created new ones to meet their needs. Manufacturers that were able to produce more goods using machines, for example, needed clerks to ship the goods and marketers to reach additional customers.

Now, as automation lets companies do more with fewer people, successful companies don't need as many workers. The most valuable company in the U.S. in 1964, AT&T, had 758,611 employees; the most valuable company today, Apple, has around 137,000 employees. Though today's big companies make billions of dollars, they share that income with fewer employees, and more of their profit goes to shareholders. "Look at the business model of Google, Facebook, Netflix. They're not in the business of creating new tasks for humans," says Daron Acemoglu, an MIT economist who studies automation and jobs.

The U.S. government incentivizes companies to automate, he says, by giving tax breaks for buying machinery and software. A business that pays a worker $100 pays $30 in taxes, but a business that spends $100 on equipment pays about $3 in taxes, he notes. The 2017 Tax Cuts and Jobs Act lowered taxes on purchases so much that "you can actually make money buying equipment," Acemoglu says.

In addition, artificial intelligence is becoming more adept at jobs that once were the purview of humans, making it harder for humans to stay ahead of machines. JPMorgan says it now has AI reviewing commercial-loan agreements, completing in seconds what used to take 360,000 hours of lawyers' time over the course of a year. In May, amid plunging advertising revenue, Microsoft laid off dozens of journalists at MSN and its Microsoft News service, replacing them with AI that can scan and process content. Radio group iHeartMedia has laid off dozens of DJs to take advantage of its investments in technology and AI. I got help transcribing interviews for this story using Otter.ai, an AI-based transcription service. A few years ago, I might have paid $1 a minute for humans to do the same thing.

These advances make AI an easy choice for companies scrambling to cope during the pandemic. Municipalities that had to close their recycling facilities, where humans worked in close quarters, are using AI-assisted robots to sort through tons of plastic, paper and glass. AMP Robotics, the company that makes these robots, says inquiries from potential customers increased at least fivefold from March to June. Last year, 35 recycling facilities used AMP Robotics, says AMP spokesman Chris Wirth; by the end of 2020, nearly 100 will.

RDS Virginia, a recycling company in Virginia, purchased four AMP robots in 2019 for its Roanoke facility, deploying them on assembly lines to ensure the paper and plastic streams were free of misplaced materials. The robots could work around the clock, didn't take bathroom breaks and didn't require safety training, says Joe Benedetto, the company's president. When the coronavirus hit, robots took over quality control as humans were pulled off assembly lines and given tasks that kept them at a safe distance from one another. Benedetto breathes easier knowing he won't have to raise the robots' pay to meet the minimum wage. He's already thinking about where else he can deploy them. "There are a few reasons I prefer machinery," Benedetto says. "For one thing, as long as you maintain it, it's there every day to work."

Companies deploying automation and AI say the technology allows them to create new jobs. But the number of new jobs is often minuscule compared with the number of jobs lost. LivePerson, which designs conversational software, could enable a company to take a 1,000-person call center and run it with 100 people plus chatbots, says CEO Rob LoCascio. A bot can respond to 10,000 queries in an hour, LoCascio says; an efficient call-center rep can answer six.

LivePerson saw a fourfold increase in demand in March as companies closed call centers, LoCascio says. "What happened was the contact-center representatives went home, and a lot of them can't work from home," he says.

Some surprising businesses are embracing automation. David's Bridal, which sells wedding gowns and other formal wear in about 300 stores across North America and the U.K., set up a chatbot called Zoey through LivePerson last year. When the pandemic forced David's Bridal to close its stores, Zoey helped manage customer inquiries flooding the company's call centers, says Holly Carroll, vice president of the customer-service and contact center. Without a bot, "we would have been dead in the water," Carroll says.

David's Bridal now spends 35% less on call centers and can handle three times more messages through its chatbot than it can through voice or email. (Zoey may be cheaper than a human, but it is not infallible. Via text, Zoey promised to connect me to a virtual stylist, but I never heard back from it or the company.)

Many organizations will likely look to technology as they face budget cuts and need to reduce staff. "I don't see us going back to the staffing levels we were at prior to COVID," says Brian Pokorny, the director of information technologies for Otsego County in New York State, who has cut 10% of his staff because of pandemic-related budget issues. "So we need to look at things like AI to streamline government services and make us more efficient."

Pokorny used a free trial from IBM's Watson Assistant early in the pandemic and set up an AI-powered web chat to answer questions from the public, like whether the National Baseball Hall of Fame in Cooperstown, the county seat, had reopened. (It had, as of June 26, with limited capacity.) Now, Watson can answer 75% of the questions people ask, and Otsego County has started paying for the service, which Pokorny says costs "pennies" per conversation. Though the county now uses AI just for online chats, it plans to deploy a Watson virtual assistant that can answer phone calls. Around 36 states have deployed chatbots to respond to questions about the pandemic and available government services, according to the National Association of State Chief Information Officers.

IBM and LivePerson say that by creating AI, they're freeing up humans to do more sophisticated tasks. Companies that contract with LivePerson still need "bot builders" to help teach the AI how to answer questions, and call-center agents see their pay increase by about 15% when they become bot builders, LoCascio says. "We can look at it like there's going to be this massive job loss, or we can look at it that people get moved into different places and positions in the world to better their lives," LoCascio says.

But companies will need far fewer bot builders than call-center agents, and mobility is not always an option, especially for workers without college degrees or whose employers do not offer retraining. Non-union workers are especially vulnerable. Larry Collins and his colleagues, represented by SEIU Local 1000, were fortunate: they're being paid their full salaries for the foreseeable future in exchange for taking 32 hours a week of online classes in computer skills, accounting, entrepreneurship and other fields. (Some might even get their jobs back, albeit temporarily, as the state upgrades its systems.) But just 11.6 % of American workers were represented by a union in 2019.

Yvonne R. Walker, the union president, says most non-union workers don't get this kind of assistance. "Companies out there don't provide employee training and upskilling-they don't see it as a good investment," Walker says. "Unless workers have a union thinking about these things, the workers get left behind."

In Sweden, employers pay into private funds that help workers get retrained; Singapore's SkillsFuture program reimburses citizens up to 500 Singapore dollars (about $362 in U.S. currency) for approved retraining courses. But in the U.S., the most robust retraining programs are for workers whose jobs are sent overseas or otherwise lost because of trade issues. A few states have started promising to pay community-college tuition for adult learners who seek retraining; the Tennessee Reconnect program pays for adults over 25 without college degrees to get certificates, associate's degrees and technical diplomas. But a similar program in Michigan is in jeopardy as states struggle with budget issues, says Michelle Miller-Adams, a researcher at the W.E. Upjohn Institute for Employment Research.

House and Senate Democrats introduced a $15 billion workforce-retraining bill in early May, but it hasn't gained much traction with Republicans, who prefer to encourage retraining by giving tax credits. The federal funds that exist come with restrictions. Pell Grants, which help low-income students pay for education, can't be used for nontraditional programs like boot camps or a 170-hour EMT certification. Local jobless centers, which receive federal funds, spend an average of $3,500 per person on retraining, but they usually run out of money early in a calendar year because of limited funding, says Ayobami Olugbemiga, press secretary at the National Skills Coalition.

Even if federal funding were widely available, the surge of people who need retraining would be more than universities can handle, says Gabe Dalporto, the CEO of Udacity, which offers online courses in programming, data science, AI and more. "A billion people will lose their jobs over the next 10 years due to AI, and if anything, COVID has accelerated that by about nine years," says Dalporto. "If you tried to reskill a billion people in the university system, you would break the university system."

Dalporto says t he coronavirus should be a wake-up call for the federal government to rethink how it funds education. "We have this model where we want to dump huge amounts of capital into very slow, noncareer-specific education," Dalporto says. "If you just repurposed 10% of that, you could retrain 3 million people in about six months."

Online education providers say they can provide retraining and upskilling on workers' own timelines, and for less money than traditional schools. Coursera offers six-month courses for $39 to $79 a month that provide students with certifications needed for a variety of jobs, says CEO Jeff Maggioncalda. Once they've landed a job, they can then pursue a college degree online, he says. "This idea that you get job skills first, get the job, then get your college degree online while you're working, I think for a lot of people will be more economically effective," he says. In April, Coursera launched a Workforce Recovery Initiative that allows the unemployed in some states and other countries, including Colombia and Singapore, to learn for free until the end of the year.

Online learning providers can offer relatively inexpensive upskilling options because they don't have guidance counselors, classrooms and other features of brick-and-mortar schools. But there could be more of a role for employers to provide those support systems going forward. Dalporto, who calls the wave of automation during COVID-19 "our economic Pearl Harbor," argues that the government should provide a tax credit of $2,500 per upskilled worker to companies that provide retraining. He also suggests that company severance packages include $1,500 in retraining credits.

Some employers are turning to Guild Education, which works with employers to subsidize upskilling. A program it launched in May lets companies pay a fee to have Guild assist laid-off workers in finding new jobs. Employers see this as a way to create loyalty among these former employees, says Rachel Carlson, the CEO of Guild. "The most thoughtful consumer companies say, Employee for now, customer for life," she says.

With the economy 30 million jobs short of what it had before the pandemic, though, workers and employers may not see much use in training for jobs that may not be available for months or even years. And not every worker is interested in studying data science, cloud computing or artificial intelligence.

But those who have found a way to move from dying fields to in-demand jobs are likely to do better. A few years ago, Tristen Alexander was a call-center rep at a Georgia power company when he took a six-month online course to earn a Google IT Support Professional Certificate. A Google scholarship covered the cost for Alexander, who has no college degree and was supporting his wife and two kids on about $38,000 a year. Alexander credits his certificate with helping him win a promotion and says he now earns more than $70,000 annually. What's more, the promotion has given him a sense of job security. "I just think there's a great need for everyone to learn something technical," he tells me.

Of course, Alexander knows that technology may significantly change his job in the next decade, so he's already planning his next step. By 2021, he wants to master the skill of testing computer systems to spot vulnerabilities to hackers and gain a certificate in that practice, known as penetration testing. It will all but guarantee him a job, he says, working alongside the technology that's changing the world.

-With reporting by Alejandro de la Garza and Julia Zorthian/New York
This appears in the August 17, 2020 issue of TIME.
More Must-Reads From TIME

Contact us at letters@time.com.

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Millions of Americans Have Lost Jobs in the Pandemic - And Robots and AI Are Replacing Them Faster Than Ever

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The drive to replace humans is accelerating as companies struggle to avoid workplace infections of COVID-19 and keep operating costs low.

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Small businesses competing with large companies.

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Robots don't just take jobs, they could help small businesses grow

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Robots could replace many human jobs, but by taking over mundane tasks they also represent an opportunity for small business growth.

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Davidow, W. H. (2018, March 07). Automation makes things cheaper, so why doesn't it feel that way? Retrieved February 14, 2021, from https://hbr.org/2017/04/automation-makes-things-cheaper-so-why-doesnt-it-feel-that-way

# data[].attributes.attachment_link.readable_text
Many Americans have been experiencing massive economic insecurity and want to return to a time when they were able to earn a good living and create a decent life for themselves and their families. President Trump promised to deliver on that wish, to "Make America Great Again," by reducing business regulations, fixing trade deals, and stopping the loss of manufacturing jobs.

Some of those policies will help, but they're unlikely to fully address the challenges faced by the middle class.

The problem is that we are now living in a bipolar economy, with a traditional economy at one end and an autonomous economy at the other. The traditional economy is prone to inflation; the autonomous economy toward deflation.

Many middle-class Americans are earning their money in a deflationary economy where wages are falling, and spending it in a traditional economy where prices are rising. Those Americans trapped between the poles of the bipolar economy were among Trump's most enthusiastic supporters.

The traditional economy provides us with most of the basic necessities of life: food, shelter, health care, clothing, transportation, and energy. Money spent on these necessities account for 70% of middle-class expenditures. The prices of most of those expenditures are rising faster than inflation.

Property managers forecasted an 8% increase in rents in 2016. From 2012 to 2014, the median home price rose by 17.3%. The U.S. Department of Agriculture reported that food prices rose 31% from 2005 to 2014. The cost of health insurance has risen by over 44% in the past five years.

The autonomous economy is where intelligent machines, robots, artificial intelligence, big data, and high-speed digital communication power production. Those processes produce high-quality goods and services, frequently with little human involvement. The autonomous economy is extremely labor and capital efficient, sometimes so much so that the prices of its products decline to close to zero. Often the markets they supply shrink in size. Most concerning, the value of human work declines as workers compete with robots for jobs.

The transformation of the movie rental and physical media businesses are examples of what happens when businesses move from the traditional to the autonomous economy.

At one point, Blockbuster Video had 60,000 employees and 9,000 stores. Then it got absorbed into the virtual economy, replaced by Netflix and by Redbox kiosks. Netflix has around 2,450 employees.

This has been good news for consumers. Many movie watchers can now view their movies for free on ad-supported networks like Crackle, which is owned by Sony Pictures Entertainment.

In the meantime, the manufacturers and distributors of physical media are struggling. Blu-ray and DVD sales have suffered declines of more than 10% for the last two years. Even Redbox's revenue plunged by almost 19%.

If you work in an industry transitioning from the traditional to the autonomous economy - say, if until recently you worked at Blockbuster - but most of what you buy is in the traditional economy (rent, food, health care), you're probably not doing very well.

The shift toward the autonomous economy is happening in the services sector, too, which makes up 80% of the workforce. (For all our talk about manufacturing jobs, they account for less than 9% of the workforce). More and more services are delivered by computers transacting with other computers, such as when we make travel reservations, when machines manage our investment portfolios by trading stocks on electronic exchanges, when we shop online, and when systems generate our news feeds and negotiate with other computers over what ads will be presented to us.

While we have no good way of determining the precise amount of goods and services produced autonomously, we know it is very large. Brian Arthur, in his article on the Second Economy, or what he now calls the autonomous economy, estimated that, by 2025, autonomous production would produce goods and services equal to the country's GNP in 1995, about $7.5 trillion.

The shift to the autonomous economy and the pressure it places on workers are likely to only get worse. For an idea of the effects that autonomous production might have, consider the potential impact of the Level 4 Autonomous Vehicle, a car that drives itself and never needs human help.

Imagine that many consumers got rid of their cars and opted for driverless shared car services - a driverless Uber. If that displaced 20% of the 250 million cars Americans own, consumers would save $150 billion, $3,000 for every car displaced, and 1 million jobs would disappear in the automotive related industries - manufacturing, insurance, finance, etc.

There are 3.5 million professional truck drivers in our country, and about 8.7 million people are employed in the trucking business. If autonomous trucks displaced just 20% of them, another 1.75 million jobs would vanish.

The jobs of 200,000 cab and limo drivers, as well as those of 400,000 part-time Uber drivers, are at risk as well. If we could get by with 100,000 of them, the equivalent of somewhere around 250,000 full-time jobs would vanish.

Automated delivery vehicles would facilitate the deliveries from the Amazons of the world. Online retailers, like Amazon, employ about one-third the number of employees per dollar sold as conventional retailers do. If online retailers gained an additional 10% in market share, that would eliminate another 1 million jobs.

Under those assumptions, 4 million jobs would be displaced by the Level 4 Autonomous Vehicle.

Lost jobs have a multiplier effect. If jobs decline in the auto industry, jobs vanish in the automobile supply chain. People who lose jobs purchase fewer retail goods and eat out less often, so other jobs are lost as well.

Numbers vary dramatically about the size of the multiplier effect, but two is a pretty conservative guess. If a multiplier effect of two is used in the case of autonomous vehicles, a total of 12 million jobs would vanish in the scenario outlined above.

You might quibble with these numbers, but that is missing the point. The effects of the Level 4 Autonomous Vehicle will be very large. I personally believe these are conservative guesses.

Autonomous production exerts downward pressure on wages, as workers compete both with machines and with the new influx of job seekers whose jobs have already been replaced. And as we have seen, this process shifts many full-time jobs into the gig economy - places like Uber, TaskRabbit, etc. - where individuals work as independent contractors, without benefits.

It is easy to conclude in response to all of this that there will be a shortage of work in the future, and that we will have to consider other previously unthinkable solutions. Commentators across the political spectrum have proposed guaranteed annual incomes as a potential solution. Others have suggested that shorter workweeks would create more job opportunities. If coupled with aggressive earned income tax credits, these proposals could perhaps allow workers to earn a decent income. Some have proposed offering tax credits to people who perform socially useful work for which they receive no pay, such as someone who stays home from work to care for a child or elder.

Most of us, including myself, feel extremely uncomfortable with these types of ideas. But the autonomous economy is rewriting the economic rules, and so we shouldn't constrain our thinking.

It is comfortable to stick with the old solutions, ignore the likelihood that they will be insufficient, and just hope. But hope is not a strategy. It will only make the long-term problem worse.

Autonomous production is already unleashing a bipolar economic system, and with it some very tough social challenges. If we are really serious about change, we will have to do radical things to address inflation in the traditional economy and deflation in the autonomous one, in response to a world where the value of human work is under pressure.

# data[].attributes.attachment_link.title
Automation Makes Things Cheaper, So Why Doesn't It Feel That Way?

# data[].attributes.attachment_link.description
Many Americans have been experiencing massive economic insecurity and want to return to a time when they were able to earn a good living and create a decent life for themselves and their families. President Trump promised to deliver on that wish, to "Make America Great Again," by reducing business regulations, fixing trade deals, and stopping the loss of manufacturing jobs.

# data[].attributes.body
Companies becoming more autonomous can mean lower costs for goods, but adds competitions for workers to find jobs

# data[].attributes.attachment_link.readable_text
Many Americans have been experiencing massive economic insecurity and want to return to a time when they were able to earn a good living and create a decent life for themselves and their families. President Trump promised to deliver on that wish, to "Make America Great Again," by reducing business regulations, fixing trade deals, and stopping the loss of manufacturing jobs.

Some of those policies will help, but they're unlikely to fully address the challenges faced by the middle class.

The problem is that we are now living in a bipolar economy, with a traditional economy at one end and an autonomous economy at the other. The traditional economy is prone to inflation; the autonomous economy toward deflation.

Many middle-class Americans are earning their money in a deflationary economy where wages are falling, and spending it in a traditional economy where prices are rising. Those Americans trapped between the poles of the bipolar economy were among Trump's most enthusiastic supporters.

The traditional economy provides us with most of the basic necessities of life: food, shelter, health care, clothing, transportation, and energy. Money spent on these necessities account for 70% of middle-class expenditures. The prices of most of those expenditures are rising faster than inflation.

Property managers forecasted an 8% increase in rents in 2016. From 2012 to 2014, the median home price rose by 17.3%. The U.S. Department of Agriculture reported that food prices rose 31% from 2005 to 2014. The cost of health insurance has risen by over 44% in the past five years.

The autonomous economy is where intelligent machines, robots, artificial intelligence, big data, and high-speed digital communication power production. Those processes produce high-quality goods and services, frequently with little human involvement. The autonomous economy is extremely labor and capital efficient, sometimes so much so that the prices of its products decline to close to zero. Often the markets they supply shrink in size. Most concerning, the value of human work declines as workers compete with robots for jobs.

The transformation of the movie rental and physical media businesses are examples of what happens when businesses move from the traditional to the autonomous economy.

At one point, Blockbuster Video had 60,000 employees and 9,000 stores. Then it got absorbed into the virtual economy, replaced by Netflix and by Redbox kiosks. Netflix has around 2,450 employees.

This has been good news for consumers. Many movie watchers can now view their movies for free on ad-supported networks like Crackle, which is owned by Sony Pictures Entertainment.

In the meantime, the manufacturers and distributors of physical media are struggling. Blu-ray and DVD sales have suffered declines of more than 10% for the last two years. Even Redbox's revenue plunged by almost 19%.

If you work in an industry transitioning from the traditional to the autonomous economy - say, if until recently you worked at Blockbuster - but most of what you buy is in the traditional economy (rent, food, health care), you're probably not doing very well.

The shift toward the autonomous economy is happening in the services sector, too, which makes up 80% of the workforce. (For all our talk about manufacturing jobs, they account for less than 9% of the workforce). More and more services are delivered by computers transacting with other computers, such as when we make travel reservations, when machines manage our investment portfolios by trading stocks on electronic exchanges, when we shop online, and when systems generate our news feeds and negotiate with other computers over what ads will be presented to us.

While we have no good way of determining the precise amount of goods and services produced autonomously, we know it is very large. Brian Arthur, in his article on the Second Economy, or what he now calls the autonomous economy, estimated that, by 2025, autonomous production would produce goods and services equal to the country's GNP in 1995, about $7.5 trillion.

The shift to the autonomous economy and the pressure it places on workers are likely to only get worse. For an idea of the effects that autonomous production might have, consider the potential impact of the Level 4 Autonomous Vehicle, a car that drives itself and never needs human help.

Imagine that many consumers got rid of their cars and opted for driverless shared car services - a driverless Uber. If that displaced 20% of the 250 million cars Americans own, consumers would save $150 billion, $3,000 for every car displaced, and 1 million jobs would disappear in the automotive related industries - manufacturing, insurance, finance, etc.

There are 3.5 million professional truck drivers in our country, and about 8.7 million people are employed in the trucking business. If autonomous trucks displaced just 20% of them, another 1.75 million jobs would vanish.

The jobs of 200,000 cab and limo drivers, as well as those of 400,000 part-time Uber drivers, are at risk as well. If we could get by with 100,000 of them, the equivalent of somewhere around 250,000 full-time jobs would vanish.

Automated delivery vehicles would facilitate the deliveries from the Amazons of the world. Online retailers, like Amazon, employ about one-third the number of employees per dollar sold as conventional retailers do. If online retailers gained an additional 10% in market share, that would eliminate another 1 million jobs.

Under those assumptions, 4 million jobs would be displaced by the Level 4 Autonomous Vehicle.

Lost jobs have a multiplier effect. If jobs decline in the auto industry, jobs vanish in the automobile supply chain. People who lose jobs purchase fewer retail goods and eat out less often, so other jobs are lost as well.

Numbers vary dramatically about the size of the multiplier effect, but two is a pretty conservative guess. If a multiplier effect of two is used in the case of autonomous vehicles, a total of 12 million jobs would vanish in the scenario outlined above.

You might quibble with these numbers, but that is missing the point. The effects of the Level 4 Autonomous Vehicle will be very large. I personally believe these are conservative guesses.

Autonomous production exerts downward pressure on wages, as workers compete both with machines and with the new influx of job seekers whose jobs have already been replaced. And as we have seen, this process shifts many full-time jobs into the gig economy - places like Uber, TaskRabbit, etc. - where individuals work as independent contractors, without benefits.

It is easy to conclude in response to all of this that there will be a shortage of work in the future, and that we will have to consider other previously unthinkable solutions. Commentators across the political spectrum have proposed guaranteed annual incomes as a potential solution. Others have suggested that shorter workweeks would create more job opportunities. If coupled with aggressive earned income tax credits, these proposals could perhaps allow workers to earn a decent income. Some have proposed offering tax credits to people who perform socially useful work for which they receive no pay, such as someone who stays home from work to care for a child or elder.

Most of us, including myself, feel extremely uncomfortable with these types of ideas. But the autonomous economy is rewriting the economic rules, and so we shouldn't constrain our thinking.

It is comfortable to stick with the old solutions, ignore the likelihood that they will be insufficient, and just hope. But hope is not a strategy. It will only make the long-term problem worse.

Autonomous production is already unleashing a bipolar economic system, and with it some very tough social challenges. If we are really serious about change, we will have to do radical things to address inflation in the traditional economy and deflation in the autonomous one, in response to a world where the value of human work is under pressure.

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Automation Makes Things Cheaper, So Why Doesn't It Feel That Way?

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Many Americans have been experiencing massive economic insecurity and want to return to a time when they were able to earn a good living and create a decent life for themselves and their families. President Trump promised to deliver on that wish, to "Make America Great Again," by reducing business regulations, fixing trade deals, and stopping the loss of manufacturing jobs.

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Robotics can help small companies compete with big ones

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Robots don't just take jobs, they could help small businesses grow

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Robots could replace many human jobs, but by taking over mundane tasks they also represent an opportunity for small business growth.

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Glavas, C., & Letheren, K. (2016, July 12). Robots don't just take jobs, they could help small businesses grow. Retrieved February 14, 2021, from https://www.weforum.org/agenda/2016/07/robots-dont-just-take-jobs-they-could-help-small-businesses-grow/

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Robots don't just take jobs, they could help small businesses grow

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Robots could replace many human jobs, but by taking over mundane tasks they also represent an opportunity for small business growth.

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Whillans, A., Bellis, E. D., Nindl, F., & Schlager, T. (2020, October 05). Robots save us time - but do they make us happier? Retrieved February 14, 2021, from https://hbr.org/2020/10/robots-save-us-time-but-do-they-make-us-happier

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As of 2019, more than 14 million Americans owned a robotic vacuum cleaner. Robotic lawn mowers tend to our yards, robotic suitcases follow us through the airport, and smart cooking machines prepare ingredients and implement entire recipes. Some autonomous products even play with and clean up after our pets. These tools are meant to improve people's lives, relieving them of chores and making them happier as a result - and while some do this, other's don't. How can business leaders ensure that their companies are developing products that people actually feel good about using?

As consumer psychologists, we have accumulated a great deal of evidence that spending money to outsource disliked tasks - such as by paying for a housecleaner - can improve happiness, lower stress, and improve our romantic relationships (even during the pandemic). But as technology develops, we have begun outsourcing not only to humans, but to machines as well.

This trend is accelerating now that many in-person services are impossible due to social distancing requirements. As such, we have shifted our focus from studying the impact of time-saving services toward better understanding how autonomous products do (or don't) improve consumer happiness. In recent research conducted with over 5,000 respondents worldwide, our team found that consumers who owned autonomous products did in fact report greater happiness and less stress than those who did not - but with two important caveats:

Consumers feel guilty if their products seem too human-like.

First, the consumers we studied reported significantly lower levels of happiness when their products reminded them of humans. When autonomous products had "person-like" qualities such as human-like voices or faces, or when consumers named their products after real people, they felt less comfortable with having these products do their dirty work. In fact, some even described feeling "guilty" about using these products.

These findings are consistent with our other recent research, which showed that consumers feel more guilt and are less willing to outsource tasks to a service provider if the person doing the work is "identifiable." When we know who will clean our house, it humanizes the service, leading us to empathize with the provider and feel guilty about asking them to do something unpleasant that we could do ourselves.

Despite these findings, many autonomous products are intentionally designed to mimic human features and behaviors. Companies like Amazon and Samsung have developed products with voice interactions optimized to sound as human-like as possible. Dyson encourages their customers to name their vacuum cleaners. While this humanized approach does have potential benefits, such as reducing loneliness and helping consumers to feel a greater sense of control over these gadgets, our data suggests that these human-like features are also likely to make consumers feel guilty, worsening their experience and reducing happiness.

Consumers worry that using autonomous products makes them seem lazy.

Our research also found that happiness is impeded if the use of autonomous products is perceived as an indication of laziness. In many cultures, busyness is seen as a status symbol. This mentality prevents people from asking for more time on adjustable deadlines at work, taking all of their paid vacation, and spending money to save time. Perhaps as a result of this cultural bias, we found that people judged owners of autonomous products as lower in social status, lazier, and less successful (and they worried that they would be similarly judged if they were to use these products).

These findings could help to explain why the adoption of autonomous products is still significantly lower than initial predictions. While as recently as four years ago, think tanks predicted that a typical family home would hold up to 500 smart objects in 2020, this has not yet come to fruition. For example, as of March 2020, only 10% of Americans owned an autonomous vacuum (despite decreasing price tags making these products fairly affordable).

What should developers of autonomous products do?

Overall, our research points to a few concrete strategies for companies looking to maximize consumer satisfaction.

1. Remind consumers how much time they are saving - doing so can increase happiness. As such, marketing communications should focus on reminding consumers that autonomous products can save them time, which they can then spend on important activities such as work, going for a short walk outside, or (virtually) socializing with a friend.

2. Companies should limit human-like features, and should consider giving their autonomous products clearly non-human names - the more human-like the product seems, the guiltier consumers feel when using it. This is exacerbated if the consumer is encouraged to name the product themselves.

3. Companies should consider encouraging consumers to enjoy these products - and the time-saving benefits - in secret (as opposed to telling their manager or their mother that a robot plays with and cleans up after their pet). Secret enjoyment, or "inconspicuous consumption," is the best bet for maximizing joy and minimizing shame when using autonomous products. If consumers are eager to talk about their autonomous products, companies could encourage consumers to highlight the fact that the time these products save them is allocated toward productive and meaningful activities, such as work or family time, which could mitigate concerns around appearing lazy.

The pandemic has only made time-management more challenging. With children home from school, many services providers closed, and stores facing long lines and product shortages, we all need more support than ever for daily tasks such as delivery, pet care, and housecleaning. Autonomous products can fill that gap - but only if companies build and market these tools in a way that makes people feel good about using them.

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Robots Save Us Time - But Do They Make Us Happier?

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As of 2019, more than 14 million Americans owned a robotic vacuum cleaner. Robotic lawn mowers tend to our yards, robotic suitcases follow us through the airport, and smart cooking machines prepare ingredients and implement entire recipes. Some autonomous products even play with and clean up after our pets.

# data[].attributes.body
Carlisle, B. (2018, January 26). Pick and place for PROFIT: Using robot labor to save money. Retrieved February 14, 2021, from https://www.roboticsbusinessreview.com/manufacturing/pick-place-profit-using-robot-labor-save-money/

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Over the last 50 years the cost of labor in manufacturing has risen steadily, and the willingness of many people to perform highly repetitive tasks on assembly lines has decreased. Over the same period the equivalent hourly cost of robot labor has steadily declined.

Human labor turnover in U.S. manufacturing averaged 16% in 2016 according to a Compensation Force survey, and overseas contract manufacturing's average turnover is 20 to 30% a year, imposing both a high training and quality cost. Also, in the U.S. labor productivity in the manufacturing sector has stalled over the last few years; according to the Bureau of Labor Statistics it was -0.6% in 2015 and 0.2% in 2016.

A new trend in robot manufacturing

Large powerful robots were introduced in the 1960s for heavy and dangerous jobs, and smaller robots were introduced in the 1980s for small part assembly and material handing jobs. Until recently robots had to be separated from workers for safety reasons and required trained programmers to develop applications. Safety screens which consumed floor space in factories and application development costs created significant barriers to installing robots.

Recently, robot manufacturers have been introducing a new type of robot called "Collaborative Robots". These machines are designed to be able to work next to people and will not injure people if they bump into them. In addition, for simpler tasks, such and loading and unloading a machine from a pallet of parts, these robots can be programmed from a graphical user interface without the need to write any software.

These newer robots reverse a previous trend toward faster and faster robot motions. Robot manufacturers selling smaller robots for assembly and material handling had sped these robots up to the point where the tool speed could be 10 meters/second, and the motions were so fast that they were quite scary. The newer collaborative robots are limited to slower speeds, typically 0.5 meters/sec to 1.5 meters/sec, which is similar to the speeds people work at, and let people to feel comfortable near the collaborative robots, allowing people and robots to mix on the same line.

Robot labor cost, computed as the installed cost of the robot plus tooling and engineering, running 2 shifts, at $2-$3 per hour, is now lower than the cost of labor in China and other low-cost regions. To the extent that robots can be easily installed for an application, they allow U.S. and European manufacturers to reduce labor cost as a consideration of where to manufacture.

Creating a robotics plan for your business

However, compared to people, robots are still very simple machines and have many limitations. There is a tendency to expect that a robot can perform any task a person can do, and this is not the case. Manufacturers who wish to benefit from the introduction of robot labor into their workforce should take some time to understand what tasks robots can do easily, what tasks are more difficult, and what tasks should be left for people. Manufacturers should have a strategic plan which lays out a roadmap on how they will introduce robots to their factories.

Such a plan should include a prioritization of applications, a clear and simple methodology for financial justification, a training plan for employees, a plan for the operator interface for various machines on the floor, a plan for the data interface and how much data is desired (or not), and a plan for any impact on product design and on part suppliers. Some examples are discussed below.

Examples of easy applications include machine loading, tester loading, packaging, and process applications where the robot uses a single tool, and no major changes are required to the product design or packaging.

An example of a difficult application is assembly, where part feeders must be designed, part packaging must often be changed (affecting suppliers), and the product design may need to be changed. Another example is order picking, where reaching into boxes, designing grippers which can handle a very large number of part shapes and orientations, and changing the packaging from suppliers are all major obstacles to easy automation.

[note style="success" show_icon="true"]

More on Global Robotic Advancements:

[/note]

Implementing Robot Labor

Senior management should establish some quick and clear methods for factory managers to understand how proposed automation investments will be evaluated.

Factory planners should have a plan for the level of complexity they may be introducing into their factories and how they will train employees to handle it. For example, if a factory installs robots from 4 different vendors, and each robot has a different programming interface, operators are going to need to learn 4 different programming interfaces.

In summary, robot labor in now cheaper than overseas labor, and reduces other costs associated with turnover and quality. If companies take the time to understand the capabilities and limitations of robots, and develop a strategic plan for their introduction, robots can dramatically improve productivity and competitiveness.

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Pick and Place for Profit: Using Robot Labor to Save Money - Robotics Business Review

# data[].attributes.attachment_link.description
Over the last 50 years the cost of labor in manufacturing has risen steadily, and the willingness of many people to perform highly repetitive tasks on assembly lines has decreased. Over the same period the equivalent hourly cost of robot labor has steadily declined. Human labor turnover in U.S.

# data[].attributes.body
Implementing robotics into process can save money

# data[].attributes.attachment_link.readable_text
Over the last 50 years the cost of labor in manufacturing has risen steadily, and the willingness of many people to perform highly repetitive tasks on assembly lines has decreased. Over the same period the equivalent hourly cost of robot labor has steadily declined.

Human labor turnover in U.S. manufacturing averaged 16% in 2016 according to a Compensation Force survey, and overseas contract manufacturing's average turnover is 20 to 30% a year, imposing both a high training and quality cost. Also, in the U.S. labor productivity in the manufacturing sector has stalled over the last few years; according to the Bureau of Labor Statistics it was -0.6% in 2015 and 0.2% in 2016.

A new trend in robot manufacturing

Large powerful robots were introduced in the 1960s for heavy and dangerous jobs, and smaller robots were introduced in the 1980s for small part assembly and material handing jobs. Until recently robots had to be separated from workers for safety reasons and required trained programmers to develop applications. Safety screens which consumed floor space in factories and application development costs created significant barriers to installing robots.

Recently, robot manufacturers have been introducing a new type of robot called "Collaborative Robots". These machines are designed to be able to work next to people and will not injure people if they bump into them. In addition, for simpler tasks, such and loading and unloading a machine from a pallet of parts, these robots can be programmed from a graphical user interface without the need to write any software.

These newer robots reverse a previous trend toward faster and faster robot motions. Robot manufacturers selling smaller robots for assembly and material handling had sped these robots up to the point where the tool speed could be 10 meters/second, and the motions were so fast that they were quite scary. The newer collaborative robots are limited to slower speeds, typically 0.5 meters/sec to 1.5 meters/sec, which is similar to the speeds people work at, and let people to feel comfortable near the collaborative robots, allowing people and robots to mix on the same line.

Robot labor cost, computed as the installed cost of the robot plus tooling and engineering, running 2 shifts, at $2-$3 per hour, is now lower than the cost of labor in China and other low-cost regions. To the extent that robots can be easily installed for an application, they allow U.S. and European manufacturers to reduce labor cost as a consideration of where to manufacture.

Creating a robotics plan for your business

However, compared to people, robots are still very simple machines and have many limitations. There is a tendency to expect that a robot can perform any task a person can do, and this is not the case. Manufacturers who wish to benefit from the introduction of robot labor into their workforce should take some time to understand what tasks robots can do easily, what tasks are more difficult, and what tasks should be left for people. Manufacturers should have a strategic plan which lays out a roadmap on how they will introduce robots to their factories.

Such a plan should include a prioritization of applications, a clear and simple methodology for financial justification, a training plan for employees, a plan for the operator interface for various machines on the floor, a plan for the data interface and how much data is desired (or not), and a plan for any impact on product design and on part suppliers. Some examples are discussed below.

Examples of easy applications include machine loading, tester loading, packaging, and process applications where the robot uses a single tool, and no major changes are required to the product design or packaging.

An example of a difficult application is assembly, where part feeders must be designed, part packaging must often be changed (affecting suppliers), and the product design may need to be changed. Another example is order picking, where reaching into boxes, designing grippers which can handle a very large number of part shapes and orientations, and changing the packaging from suppliers are all major obstacles to easy automation.

[note style="success" show_icon="true"]

More on Global Robotic Advancements:

[/note]

Implementing Robot Labor

Senior management should establish some quick and clear methods for factory managers to understand how proposed automation investments will be evaluated.

Factory planners should have a plan for the level of complexity they may be introducing into their factories and how they will train employees to handle it. For example, if a factory installs robots from 4 different vendors, and each robot has a different programming interface, operators are going to need to learn 4 different programming interfaces.

In summary, robot labor in now cheaper than overseas labor, and reduces other costs associated with turnover and quality. If companies take the time to understand the capabilities and limitations of robots, and develop a strategic plan for their introduction, robots can dramatically improve productivity and competitiveness.

# data[].attributes.attachment_link.title
Pick and Place for Profit: Using Robot Labor to Save Money - Robotics Business Review

# data[].attributes.attachment_link.description
Over the last 50 years the cost of labor in manufacturing has risen steadily, and the willingness of many people to perform highly repetitive tasks on assembly lines has decreased. Over the same period the equivalent hourly cost of robot labor has steadily declined. Human labor turnover in U.S.

# data[].attributes.body
Rogers, M. (2019, January 7). These 9 technological innovations will shape the sustainability agenda in 2019. Retrieved February 07, 2021, from https://www.mckinsey.com/business-functions/sustainability/our-insights/sustainability-blog/these-9-technological-innovations-will-shape-the-sustainability-agenda-in-2019#

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With a new year, we're taking a fresh look at where sustainability is headed globally. What technologies will drive the global discussions, and moreover, which will have the greatest impact in 2019? I asked McKinsey's leading sustainability experts for their thoughts.

1. Public electric transport. It's not only individual vehicle owners who have better access to electric vehicles (EVs) than ever before-there are 160 electric and hybrid vehicle models available today-but municipalities are taking notice as well. In China, 300,000 electric buses hum down city streets every day. Their widespread adoption in China-an economic coup as much as a policy one-will entice European cities to follow suit. Although these eBuses have higher acquisition prices due to upfront battery costs, their total cost of ownership (TCO) is lower due to their independence from pricey diesel. They also eliminate local particulates, including SOx, NOx, and CO2, all major issues in most cities today.
Read more: The European electric bus market is charging ahead, but how will it develop?
2. Electric trucks. With personal electric vehicles grabbing more and more market share, commercial fleets could follow suit rapidly. But to ensure an efficient transition, we need a firm understanding of the total cost of ownership. Decades ago, widespread adoption of electric trucks-or "eTrucks"-was cost prohibitive. But today, the total cost of ownership could soon be on par with diesel-run trucks, due in part to increasingly cost competitive and available electric vehicle infrastructure. We predict that adoption of battery electric commercial vehicles (BECVs), especially in the light- and medium-duty segments, could surpass the car EV sales mix in some markets by 2030. And although many heavy-duty BECVs will need to charge mid-route, our analysis shows that a charging station every 80 to 100 kilometers on popular routes will suffice for early phases of adoption.
Read more: What's sparking electric-vehicle adoption in the truck industry?
3. Cheap energy storage. The new age of electric vehicles has rapidly expanded the market for lithium and cobalt batteries-and drastically reduced their price. Lithium ion batteries now cost $200 per kilowatt-hour compared to $1,000 per kilowatt-hour just nine years ago. The expanded market for batteries has implications for more than just EVs. Industry and utilities are finding broader use for them as energy-storage solutions. With prices for batteries rapidly dropping, they are proving valuable to reduce power costs, increase reliability and resiliency, and make power systems more flexible to operate. But the wide accessibility of cheap energy storage also means utilities will need to change quickly. One way will be to move away from a variable rate structure to a fixed fee for access to the grid (like cable TV), especially as consumers begin to generate their own energy. Another will be to revise grid-planning approaches by increasing circuit-by-circuit nodal planning.
Read more: Battery storage: The next disruptive technology in the power sector
4. Long-term storage. Lithium-ion batteries are great for addressing short-term storage needs (4-5 hours) that arise frequently (20-200 times per year), but the market also wants solutions that address long-term storage needs brought on by seasonal shifts and multi-day periods when the sun does not shine and the wind does not blow. Historically, hydropower dams were one of the only approaches to manage these seasonal shifts. Otherwise, the system would need to build a whole series of plants that only run for a few days each year. Fortunately, a new series of innovators believe they are close to developing long-duration storage technologies. Google X just spun off Malta, which is storing renewable energy in molten salt. Antora Energy is trying to solve the same problem by building a low-cost thermal battery for grid-scale energy storage. And BP-backed Lightsource is adding storage to solar developments. What's clear is that if long-term energy storage works, the price of power will decline significantly. These long-term solutions could eliminate the cost incurred through the underutilization of assets during and save money by inserting lower-cost generators such as solar and wind in the power supply.

5. Plastic recycling. 260 million tons of plastic waste is generated across the globe every year, but only 16 percent gets recycled. The plastics industry has the opportunity to move away from a "take, make, and dispose" business model and adopt a circular model, which aims to eliminate waste across sectors while creating economic, societal, and environmental benefits. One promising circular process is pyrolysis, which uses heat and the absence of oxygen to reconvert plastic waste back into liquid feedstock. The benefits are economic as much as environmental, with a recycling-based profit pool estimated at $55 billion by the next decade.
Read more: No time to waste: What plastics recycling could offer
6. LED light efficiency. Energy-efficient LED lighting is quickly replacing traditional incandescent bulbs in American homes and is expected to achieve 84 percent market share by 2030. In 2030 alone, LED lights will reduce energy consumption by 40 percent, which adds up to $26 billion in savings adjusted to today's energy prices. These are dramatic cost savings, but according to the Department of Energy, the U.S. can still see an additional 20 percent in energy savings with increased investment in LED lights.

7. Accessible solar power. Renewable energy continues to become cheaper and more accessible into 2019, a trend that has major implications for the nearly 1 billion people across the globe without access to electricity. While expanding the grid is part of the access solution, countries in sub-Saharan Africa and the Caribbean, which account for a majority of the world's unelectrified population, are exploring renewable solutions like solar energy to bring energy quickly and inexpensively to millions. Innovative financing plans can help make previously unaffordable solar home systems (SHSs) a smart solution for communities that are too far from a reliable grid connection. A recent McKinsey assessment determined that SHSs can help power 150 million households by 2020.
Read more: Bringing (solar) power to the people
8. Carbon capture and storage. Instead of just focusing on completely decarbonizing the major industrial commodities behind plastics and cement, we can also consider safely capturing the carbon emitted when these commodities are produced. Carbon capture and storage (CCS) allows industry to capture carbon at its source, compress it, and move it to a suitable permanent storage site. The technology not only has the potential to significantly reduce greenhouse-gas emissions-it can also mean more money if the CO2 can be used profitably to make other products. Several industries are already working to put captured carbon dioxide to profitable use, including manufacturers who use captured carbon to make plastics, such as polyurethane. Emerging technologies, including direct air capture, have previously been too cost prohibitive to implement at scale. But a new Stanford University study predicts that direct air capture, which grabs carbon dioxide from the air and converts it into synthetic fuel, could eventually drop from $600 per ton of carbon dioxide to less than $100.
Read more: Why commercial use could be the future of carbon capture
9. Hydrogen in the energy transition. It's difficult to imagine how we meet ambitious global warming benchmarks without including hydrogen as a critical part of the solution. Hydrogen-led pathways to cleaning up the environment forecast hydrogen powering more than 400 million cars, 15 to 20 million buses, and more than 20 percent of passenger ships and locomotives by 2050. Although battery-powered electric vehicles exhibit overall higher fuel efficiency, hydrogen-powered fuel cells can store more energy with less weight. This makes them an ideal solution for heavy cargo vehicles that must travel long distances. Hydrogen-powered fuel cell vehicles are already on the road in Japan, South Korea, California, and Germany-and more than 10 models are slated for release by 2020. In short, hydrogen fuel could help the world meet its goal of decreasing carbon dioxide emissions by 60 percent. Although the necessary technology exists today, the costs for producing hydrogen need to decline significantly, and the infrastructure that supports it needs a step up. Hydrogen could facilitate smarter use of other renewables by acting as a long-term transport and storage solution for renewable electricity. It could be a key enabler in the energy transition.
Read more: Hydrogen scaling up: A sustainable pathway for the global energy transition and Hydrogen: The next wave for electric vehicles?

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These 9 technological innovations will shape the sustainability agenda in 2019

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With a new year, we're taking a fresh look at where sustainability is headed globally. What technologies will drive the global discussions, and moreover, which will have the greatest impact in 2019? I asked McKinsey's leading sustainability experts for their thoughts. 1. Public electric transport.

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Advancement in technology and science helping to get closer to reusable and sustainable energy

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With a new year, we're taking a fresh look at where sustainability is headed globally. What technologies will drive the global discussions, and moreover, which will have the greatest impact in 2019? I asked McKinsey's leading sustainability experts for their thoughts.

1. Public electric transport. It's not only individual vehicle owners who have better access to electric vehicles (EVs) than ever before-there are 160 electric and hybrid vehicle models available today-but municipalities are taking notice as well. In China, 300,000 electric buses hum down city streets every day. Their widespread adoption in China-an economic coup as much as a policy one-will entice European cities to follow suit. Although these eBuses have higher acquisition prices due to upfront battery costs, their total cost of ownership (TCO) is lower due to their independence from pricey diesel. They also eliminate local particulates, including SOx, NOx, and CO2, all major issues in most cities today.
Read more: The European electric bus market is charging ahead, but how will it develop?
2. Electric trucks. With personal electric vehicles grabbing more and more market share, commercial fleets could follow suit rapidly. But to ensure an efficient transition, we need a firm understanding of the total cost of ownership. Decades ago, widespread adoption of electric trucks-or "eTrucks"-was cost prohibitive. But today, the total cost of ownership could soon be on par with diesel-run trucks, due in part to increasingly cost competitive and available electric vehicle infrastructure. We predict that adoption of battery electric commercial vehicles (BECVs), especially in the light- and medium-duty segments, could surpass the car EV sales mix in some markets by 2030. And although many heavy-duty BECVs will need to charge mid-route, our analysis shows that a charging station every 80 to 100 kilometers on popular routes will suffice for early phases of adoption.
Read more: What's sparking electric-vehicle adoption in the truck industry?
3. Cheap energy storage. The new age of electric vehicles has rapidly expanded the market for lithium and cobalt batteries-and drastically reduced their price. Lithium ion batteries now cost $200 per kilowatt-hour compared to $1,000 per kilowatt-hour just nine years ago. The expanded market for batteries has implications for more than just EVs. Industry and utilities are finding broader use for them as energy-storage solutions. With prices for batteries rapidly dropping, they are proving valuable to reduce power costs, increase reliability and resiliency, and make power systems more flexible to operate. But the wide accessibility of cheap energy storage also means utilities will need to change quickly. One way will be to move away from a variable rate structure to a fixed fee for access to the grid (like cable TV), especially as consumers begin to generate their own energy. Another will be to revise grid-planning approaches by increasing circuit-by-circuit nodal planning.
Read more: Battery storage: The next disruptive technology in the power sector
4. Long-term storage. Lithium-ion batteries are great for addressing short-term storage needs (4-5 hours) that arise frequently (20-200 times per year), but the market also wants solutions that address long-term storage needs brought on by seasonal shifts and multi-day periods when the sun does not shine and the wind does not blow. Historically, hydropower dams were one of the only approaches to manage these seasonal shifts. Otherwise, the system would need to build a whole series of plants that only run for a few days each year. Fortunately, a new series of innovators believe they are close to developing long-duration storage technologies. Google X just spun off Malta, which is storing renewable energy in molten salt. Antora Energy is trying to solve the same problem by building a low-cost thermal battery for grid-scale energy storage. And BP-backed Lightsource is adding storage to solar developments. What's clear is that if long-term energy storage works, the price of power will decline significantly. These long-term solutions could eliminate the cost incurred through the underutilization of assets during and save money by inserting lower-cost generators such as solar and wind in the power supply.

5. Plastic recycling. 260 million tons of plastic waste is generated across the globe every year, but only 16 percent gets recycled. The plastics industry has the opportunity to move away from a "take, make, and dispose" business model and adopt a circular model, which aims to eliminate waste across sectors while creating economic, societal, and environmental benefits. One promising circular process is pyrolysis, which uses heat and the absence of oxygen to reconvert plastic waste back into liquid feedstock. The benefits are economic as much as environmental, with a recycling-based profit pool estimated at $55 billion by the next decade.
Read more: No time to waste: What plastics recycling could offer
6. LED light efficiency. Energy-efficient LED lighting is quickly replacing traditional incandescent bulbs in American homes and is expected to achieve 84 percent market share by 2030. In 2030 alone, LED lights will reduce energy consumption by 40 percent, which adds up to $26 billion in savings adjusted to today's energy prices. These are dramatic cost savings, but according to the Department of Energy, the U.S. can still see an additional 20 percent in energy savings with increased investment in LED lights.

7. Accessible solar power. Renewable energy continues to become cheaper and more accessible into 2019, a trend that has major implications for the nearly 1 billion people across the globe without access to electricity. While expanding the grid is part of the access solution, countries in sub-Saharan Africa and the Caribbean, which account for a majority of the world's unelectrified population, are exploring renewable solutions like solar energy to bring energy quickly and inexpensively to millions. Innovative financing plans can help make previously unaffordable solar home systems (SHSs) a smart solution for communities that are too far from a reliable grid connection. A recent McKinsey assessment determined that SHSs can help power 150 million households by 2020.
Read more: Bringing (solar) power to the people
8. Carbon capture and storage. Instead of just focusing on completely decarbonizing the major industrial commodities behind plastics and cement, we can also consider safely capturing the carbon emitted when these commodities are produced. Carbon capture and storage (CCS) allows industry to capture carbon at its source, compress it, and move it to a suitable permanent storage site. The technology not only has the potential to significantly reduce greenhouse-gas emissions-it can also mean more money if the CO2 can be used profitably to make other products. Several industries are already working to put captured carbon dioxide to profitable use, including manufacturers who use captured carbon to make plastics, such as polyurethane. Emerging technologies, including direct air capture, have previously been too cost prohibitive to implement at scale. But a new Stanford University study predicts that direct air capture, which grabs carbon dioxide from the air and converts it into synthetic fuel, could eventually drop from $600 per ton of carbon dioxide to less than $100.
Read more: Why commercial use could be the future of carbon capture
9. Hydrogen in the energy transition. It's difficult to imagine how we meet ambitious global warming benchmarks without including hydrogen as a critical part of the solution. Hydrogen-led pathways to cleaning up the environment forecast hydrogen powering more than 400 million cars, 15 to 20 million buses, and more than 20 percent of passenger ships and locomotives by 2050. Although battery-powered electric vehicles exhibit overall higher fuel efficiency, hydrogen-powered fuel cells can store more energy with less weight. This makes them an ideal solution for heavy cargo vehicles that must travel long distances. Hydrogen-powered fuel cell vehicles are already on the road in Japan, South Korea, California, and Germany-and more than 10 models are slated for release by 2020. In short, hydrogen fuel could help the world meet its goal of decreasing carbon dioxide emissions by 60 percent. Although the necessary technology exists today, the costs for producing hydrogen need to decline significantly, and the infrastructure that supports it needs a step up. Hydrogen could facilitate smarter use of other renewables by acting as a long-term transport and storage solution for renewable electricity. It could be a key enabler in the energy transition.
Read more: Hydrogen scaling up: A sustainable pathway for the global energy transition and Hydrogen: The next wave for electric vehicles?

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These 9 technological innovations will shape the sustainability agenda in 2019

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With a new year, we're taking a fresh look at where sustainability is headed globally. What technologies will drive the global discussions, and moreover, which will have the greatest impact in 2019? I asked McKinsey's leading sustainability experts for their thoughts. 1. Public electric transport.

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Negative affects of technology

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Advancements in technology allow people to be more connected than ever, but this may come at a price. Overuse of social media and mobile devices have been linked to eyestrain, difficulty focusing on other tasks, and depression.

While some forms of technology may have made positive changes in the world, there is evidence for the negative effects of technology and its overuse, as well.

The overuse of technology may have a more significant impact on developing children and teenagers.

In this article, learn about the psychological and physical health effects of technology, as well as how to create healthful habits with technology and avoid overuse.

Overuse or dependence on technology may have adverse psychological effects, including:

Isolation

Technologies, such as social media, are designed to bring people together, yet they may have the opposite effect in some cases.

A 2017 study in young adults aged 19-32 years found that people with higher social media use were more than three times as likely to feel socially isolated than those who did not use social media as often.

Finding ways to reduce social media use, such as setting time limits for social apps, may help reduce feelings of isolation in some people.

Depression and anxiety

The authors of a 2016 systematic review discussed the link between social networks and mental health issues, such as depression and anxiety.

Their research found mixed results. People who had more positive interactions and social support on these platforms appeared to have lower levels of depression and anxiety.

However, the reverse was also true. People who perceived that they had more negative social interactions online and who were more prone to social comparison experienced higher levels of depression and anxiety.

So, while there does appear to be a link between social media and mental health, a significant determining factor is the types of interactions people feel they are having on these platforms.

Technology use may increase the risk of physical issues as well, including:

Eyestrain

Technologies, such as handheld tablets, smartphones, and computers, can hold a person's attention for long periods. This may lead to eyestrain.

Symptoms of digital eyestrain can include blurred vision and dry eyes. Eyestrain may also lead to pains in other areas of the body, such as the head, neck, or shoulders.

Several technological factors may lead to eyestrain, such as:

screen time

screen glare

screen brightness

viewing too close or too far away

poor sitting posture

underlying vision issues

Taking regular breaks away from the screen may reduce the likelihood of eyestrain.

Anyone regularly experiencing these symptoms should see an optometrist for a checkup.

The 20-20-20 rule for digital viewing

When using any form of digital screen for longer periods of time, the American Optometric Association recommend using the 20-20-20 rule.

To use the rule, after every 20 minutes of screen time, take a 20-second break to look at something at least 20 feet away.

Doing this may help reduce the strain on the eyes from staring at a screen for a continuous period.
Learn more about the 20-20-20 rule in this article.
Poor posture

The way many people use mobile devices and computers may also contribute to incorrect posture. Over time, this may lead to musculoskeletal issues.

Many technologies promote a "down and forward" user position, meaning the person is hunched forward and looking down at the screen. This can put an unnecessary amount of pressure on the neck and spine.

A 5-year study in the journal Applied Ergonomics found an association between texting on a mobile phone and neck or upper back pain in young adults.

The results indicated the effects were mostly short term, though some people continued to have long-term symptoms.

However, some studies challenge these results.

A in the European Spine Journal found that the posture of the neck while texting made no difference in symptoms such as neck pain.

This study concluded that texting and "text neck" did not influence neck pain in young adults. However, the study did not include a long-term follow-up.

It may be that other factors influence neck pain, as well, such as age and activity levels.

Correcting posture problems while using technology may lead to an overall improvement in posture and strength in the core, neck, and back.

For example, if a person finds themselves sitting in the same position for hours at a time, such as sitting at a desk while working, regularly standing or stretching may help reduce strain on the body.

Additionally, taking short breaks, such as walking around the office every hour, may also help keep the muscles loose and avoid tension and incorrect posture.
Learn more about how to stay active and in good posture at work with this article.
Sleep problems

Using technology too close to bedtime may cause issues with sleep. This effect has to do with the fact that blue light, such as the light from cell phones, e-readers, and computers, stimulates the brain.

Authors of a 2014 study found that this blue light is enough to disturb the body's natural circadian rhythm. This disturbance could make it harder to fall asleep or lead to a person feeling less alert the next day.

To avoid the potential impact of blue light on the brain, people can stop using electronic devices that emit blue light in the hour or two before bedtime.

Gentle activities to wind down with instead, such as reading a book, doing gentle stretches, or taking a bath, are alternatives.

Reduced physical activity

Most everyday digital technologies are sedentary. More extended use of these technologies promotes a more sedentary lifestyle, which is known to have negative health effects, such as contributing to:

Finding ways to take breaks from sedentary technologies may help promote a more active lifestyle.

Other forms of technology may help, however.

Research from 2017 indicates that active technologies, such as app notifications, emails, and wearable technologies that promote exercise may reduce short-term sedentary behavior.

This could help people set healthful patterns and become more physically active.

Children's brains are still developing and may be more sensitive to the effects of technology and its overuse than adult brains.

A 2018 review of various studies noted the possible adverse effects of children using different technologies.

Children who overuse technology may be more likely to experience issues, including:

low academic performance

lack of attention

low creativity

delays in language development

delays in social and emotional development

physical inactivity and obesity

poor sleep quality

social issues, such as social incompatibility and anxiety

aggressive behaviors

addiction to these technologies

The research also noted the importance of teaching children to interact with these technologies in healthful ways by monitoring their time using them and providing interesting alternatives.

Additionally, a study of teenagers aged 15-16 found that those who had high digital media use had an increased chance of developing symptoms of attention-deficit hyperactivity disorder (ADHD).

This does not mean that digital media use causes ADHD, rather that there is an association between the two. More research needs to determine what this association means.

The authors of 2015 research found that technology appears to negatively affect the overall health of children and teenagers of all ages. Researchers noted the importance of parents and caregivers controlling screen time in all children.

The American Academy of Pediatrics recommend children under 18 months old avoid screen time altogether, while 2-5-year-olds have no more than 1 hour a day of high-quality viewing with an adult.

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Negative effects of technology: Psychological, social, and health

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While technology has many positives, it can also lead to negative psychological and physical health effects. Learn about the adverse effects of technology here.

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Semuels, A. (2020, August 6). Millions of Americans Have Lost Jobs in the Pandemic—And Robots and AI Are Replacing Them Faster Than Ever. TIME, (August 17, 2020). doi:https://time.com/5876604/machines-jobs-coronavirus/

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For 23 years, Larry Collins worked in a booth on the Carquinez Bridge in the San Francisco Bay Area, collecting tolls. The fare changed over time, from a few bucks to $6, but the basics of the job stayed the same: Collins would make change, answer questions, give directions and greet commuters. "Sometimes, you're the first person that people see in the morning," says Collins, "and that human interaction can spark a lot of conversation."

But one day in mid-March, as confirmed cases of the coronavirus were skyrocketing, Collins' supervisor called and told him not to come into work the next day. The tollbooths were closing to protect the health of drivers and of toll collectors. Going forward, drivers would pay bridge tolls automatically via FasTrak tags mounted on their windshields or would receive bills sent to the address linked to their license plate. Collins' job was disappearing, as were the jobs of around 185 other toll collectors at bridges in Northern California, all to be replaced by technology.

Machines have made jobs obsolete for centuries. The spinning jenny replaced weavers, buttons displaced elevator operators, and the Internet drove travel agencies out of business. One study estimates that about 400,000 jobs were lost to automation in U.S. factories from 1990 to 2007. But the drive to replace humans with machinery is accelerating as companies struggle to avoid workplace infections of COVID-19 and to keep operating costs low. The U.S. shed around 40 million jobs at the peak of the pandemic, and while some have come back, some will never return. One group of economists estimates that 42% of the jobs lost are gone forever.

More from TIME

This replacement of humans with machines may pick up more speed in coming months as companies move from survival mode to figuring out how to operate while the pandemic drags on. Robots could replace as many as 2 million more workers in manufacturing alone by 2025, according to a recent paper by economists at MIT and Boston University. "This pandemic has created a very strong incentive to automate the work of human beings," says Daniel Susskind, a fellow in economics at Balliol College, University of Oxford, and the author of A World Without Work: Technology, Automation and How We Should Respond. "Machines don't fall ill, they don't need to isolate to protect peers, they don't need to take time off work."

As with so much of the pandemic, this new wave of automation will be harder on people of color like Collins, who is Black, and on low-wage workers. Many Black and Latino Americans are cashiers, food-service employees and customer-service representatives, which are among the 15 jobs most threatened by automation, according to McKinsey. Even before the pandemic, the global consulting company estimated that automation could displace 132,000 Black workers in the U.S. by 2030.

The deployment of robots as a response to the coronavirus was rapid. They were suddenly cleaning floors at airports and taking people's temperatures. Hospitals and universities deployed Sally, a salad-making robot created by tech company Chowbotics, to replace dining-hall employees; malls and stadiums bought Knightscope security-guard robots to patrol empty real estate; companies that manufacture in-demand supplies like hospital beds and cotton swabs turned to industrial robot supplier Yaskawa America to help increase production.

Companies closed call centers employing human customer-service agents and turned to chatbots created by technology company LivePerson or to AI platform Watson Assistant. "I really think this is a new normal-the pandemic accelerated what was going to happen anyway," says Rob Thomas, senior vice president of cloud and data platform at IBM, which deploys Watson. Roughly 100 new clients started using the software from March to June.

In theory, automation and artificial intelligence should free humans from dangerous or boring tasks so they can take on more intellectually stimulating assignments, making companies more productive and raising worker wages. And in the past, technology was deployed piecemeal, giving employees time to transition into new roles. Those who lost jobs could seek retraining, perhaps using severance pay or unemployment benefits to find work in another field. This time the change was abrupt as employers, worried about COVID-19 or under sudden lockdown orders, rushed to replace workers with machines or software. There was no time to retrain. Companies worried about their bottom line cut workers loose instead, and these workers were left on their own to find ways of mastering new skills. They found few options.

In the past, the U.S. responded to technological change by investing in education. When automation fundamentally changed farm jobs in the late 1800s and the 1900s, states expanded access to public schools. Access to college expanded after World War II with the GI Bill, which sent 7.8 million veterans to school from 1944 to 1956. But since then, U.S. investment in education has stalled, putting the burden on workers to pay for it themselves. And the idea of education in the U.S. still focuses on college for young workers rather than on retraining employees. The country spends 0.1% of GDP to help workers navigate job transitions, less than half what it spent 30 years ago.

"The real automation problem isn't so much a robot apocalypse," says Mark Muro, a senior fellow at the Brookings Institution. "It is business as usual of people needing to get retraining, and they really can't get it in an accessible, efficient, well-informed, data-driven way."

This means that tens of thousands of Americans who lost jobs during the pandemic may be unemployed for years or, in Collins' case, for good. Though he has access to retraining funding through his union contract, "I'm too old to think about doing some other job," says Collins, who is 63 and planning on taking early retirement. "I just want to go back to what I was doing."

Check into a hotel today, and a mechanical butler designed by robotics company Savioke might roll down the hall to deliver towels and toothbrushes. ("No tip required," Savioke notes on its website.) Robots have been deployed during the pandemic to meet guests at their rooms with newly disinfected keys. A bricklaying robot can lay more than 3,000 bricks in an eight-hour shift, up to 10 times what a human can do. Robots can plant seeds and harvest crops, separate breastbones and carcasses in slaughterhouses, pack pallets of food in processing facilities.

That doesn't mean they're taking everyone's jobs. For centuries, humans from weavers to mill workers have worried that advances in technology would create a world without work, and that's never proved true. ATMs did not immediately decrease the number of bank tellers, for instance. They actually led to more teller jobs as consumers, lured by the convenience of cash machines, began visiting banks more often. Banks opened more branches and hired tellers to handle tasks that are beyond the capacity of ATMs. Without technological advancement, much of the American workforce would be toiling away on farms, which accounted for 31% of U.S. jobs in 1910 and now account for less than 1%.

But in the past, when automation eliminated jobs, companies created new ones to meet their needs. Manufacturers that were able to produce more goods using machines, for example, needed clerks to ship the goods and marketers to reach additional customers.

Now, as automation lets companies do more with fewer people, successful companies don't need as many workers. The most valuable company in the U.S. in 1964, AT&T, had 758,611 employees; the most valuable company today, Apple, has around 137,000 employees. Though today's big companies make billions of dollars, they share that income with fewer employees, and more of their profit goes to shareholders. "Look at the business model of Google, Facebook, Netflix. They're not in the business of creating new tasks for humans," says Daron Acemoglu, an MIT economist who studies automation and jobs.

The U.S. government incentivizes companies to automate, he says, by giving tax breaks for buying machinery and software. A business that pays a worker $100 pays $30 in taxes, but a business that spends $100 on equipment pays about $3 in taxes, he notes. The 2017 Tax Cuts and Jobs Act lowered taxes on purchases so much that "you can actually make money buying equipment," Acemoglu says.

In addition, artificial intelligence is becoming more adept at jobs that once were the purview of humans, making it harder for humans to stay ahead of machines. JPMorgan says it now has AI reviewing commercial-loan agreements, completing in seconds what used to take 360,000 hours of lawyers' time over the course of a year. In May, amid plunging advertising revenue, Microsoft laid off dozens of journalists at MSN and its Microsoft News service, replacing them with AI that can scan and process content. Radio group iHeartMedia has laid off dozens of DJs to take advantage of its investments in technology and AI. I got help transcribing interviews for this story using Otter.ai, an AI-based transcription service. A few years ago, I might have paid $1 a minute for humans to do the same thing.

These advances make AI an easy choice for companies scrambling to cope during the pandemic. Municipalities that had to close their recycling facilities, where humans worked in close quarters, are using AI-assisted robots to sort through tons of plastic, paper and glass. AMP Robotics, the company that makes these robots, says inquiries from potential customers increased at least fivefold from March to June. Last year, 35 recycling facilities used AMP Robotics, says AMP spokesman Chris Wirth; by the end of 2020, nearly 100 will.

RDS Virginia, a recycling company in Virginia, purchased four AMP robots in 2019 for its Roanoke facility, deploying them on assembly lines to ensure the paper and plastic streams were free of misplaced materials. The robots could work around the clock, didn't take bathroom breaks and didn't require safety training, says Joe Benedetto, the company's president. When the coronavirus hit, robots took over quality control as humans were pulled off assembly lines and given tasks that kept them at a safe distance from one another. Benedetto breathes easier knowing he won't have to raise the robots' pay to meet the minimum wage. He's already thinking about where else he can deploy them. "There are a few reasons I prefer machinery," Benedetto says. "For one thing, as long as you maintain it, it's there every day to work."

Companies deploying automation and AI say the technology allows them to create new jobs. But the number of new jobs is often minuscule compared with the number of jobs lost. LivePerson, which designs conversational software, could enable a company to take a 1,000-person call center and run it with 100 people plus chatbots, says CEO Rob LoCascio. A bot can respond to 10,000 queries in an hour, LoCascio says; an efficient call-center rep can answer six.

LivePerson saw a fourfold increase in demand in March as companies closed call centers, LoCascio says. "What happened was the contact-center representatives went home, and a lot of them can't work from home," he says.

Some surprising businesses are embracing automation. David's Bridal, which sells wedding gowns and other formal wear in about 300 stores across North America and the U.K., set up a chatbot called Zoey through LivePerson last year. When the pandemic forced David's Bridal to close its stores, Zoey helped manage customer inquiries flooding the company's call centers, says Holly Carroll, vice president of the customer-service and contact center. Without a bot, "we would have been dead in the water," Carroll says.

David's Bridal now spends 35% less on call centers and can handle three times more messages through its chatbot than it can through voice or email. (Zoey may be cheaper than a human, but it is not infallible. Via text, Zoey promised to connect me to a virtual stylist, but I never heard back from it or the company.)

Many organizations will likely look to technology as they face budget cuts and need to reduce staff. "I don't see us going back to the staffing levels we were at prior to COVID," says Brian Pokorny, the director of information technologies for Otsego County in New York State, who has cut 10% of his staff because of pandemic-related budget issues. "So we need to look at things like AI to streamline government services and make us more efficient."

Pokorny used a free trial from IBM's Watson Assistant early in the pandemic and set up an AI-powered web chat to answer questions from the public, like whether the National Baseball Hall of Fame in Cooperstown, the county seat, had reopened. (It had, as of June 26, with limited capacity.) Now, Watson can answer 75% of the questions people ask, and Otsego County has started paying for the service, which Pokorny says costs "pennies" per conversation. Though the county now uses AI just for online chats, it plans to deploy a Watson virtual assistant that can answer phone calls. Around 36 states have deployed chatbots to respond to questions about the pandemic and available government services, according to the National Association of State Chief Information Officers.

IBM and LivePerson say that by creating AI, they're freeing up humans to do more sophisticated tasks. Companies that contract with LivePerson still need "bot builders" to help teach the AI how to answer questions, and call-center agents see their pay increase by about 15% when they become bot builders, LoCascio says. "We can look at it like there's going to be this massive job loss, or we can look at it that people get moved into different places and positions in the world to better their lives," LoCascio says.

But companies will need far fewer bot builders than call-center agents, and mobility is not always an option, especially for workers without college degrees or whose employers do not offer retraining. Non-union workers are especially vulnerable. Larry Collins and his colleagues, represented by SEIU Local 1000, were fortunate: they're being paid their full salaries for the foreseeable future in exchange for taking 32 hours a week of online classes in computer skills, accounting, entrepreneurship and other fields. (Some might even get their jobs back, albeit temporarily, as the state upgrades its systems.) But just 11.6 % of American workers were represented by a union in 2019.

Yvonne R. Walker, the union president, says most non-union workers don't get this kind of assistance. "Companies out there don't provide employee training and upskilling-they don't see it as a good investment," Walker says. "Unless workers have a union thinking about these things, the workers get left behind."

In Sweden, employers pay into private funds that help workers get retrained; Singapore's SkillsFuture program reimburses citizens up to 500 Singapore dollars (about $362 in U.S. currency) for approved retraining courses. But in the U.S., the most robust retraining programs are for workers whose jobs are sent overseas or otherwise lost because of trade issues. A few states have started promising to pay community-college tuition for adult learners who seek retraining; the Tennessee Reconnect program pays for adults over 25 without college degrees to get certificates, associate's degrees and technical diplomas. But a similar program in Michigan is in jeopardy as states struggle with budget issues, says Michelle Miller-Adams, a researcher at the W.E. Upjohn Institute for Employment Research.

House and Senate Democrats introduced a $15 billion workforce-retraining bill in early May, but it hasn't gained much traction with Republicans, who prefer to encourage retraining by giving tax credits. The federal funds that exist come with restrictions. Pell Grants, which help low-income students pay for education, can't be used for nontraditional programs like boot camps or a 170-hour EMT certification. Local jobless centers, which receive federal funds, spend an average of $3,500 per person on retraining, but they usually run out of money early in a calendar year because of limited funding, says Ayobami Olugbemiga, press secretary at the National Skills Coalition.

Even if federal funding were widely available, the surge of people who need retraining would be more than universities can handle, says Gabe Dalporto, the CEO of Udacity, which offers online courses in programming, data science, AI and more. "A billion people will lose their jobs over the next 10 years due to AI, and if anything, COVID has accelerated that by about nine years," says Dalporto. "If you tried to reskill a billion people in the university system, you would break the university system."

Dalporto says t he coronavirus should be a wake-up call for the federal government to rethink how it funds education. "We have this model where we want to dump huge amounts of capital into very slow, noncareer-specific education," Dalporto says. "If you just repurposed 10% of that, you could retrain 3 million people in about six months."

Online education providers say they can provide retraining and upskilling on workers' own timelines, and for less money than traditional schools. Coursera offers six-month courses for $39 to $79 a month that provide students with certifications needed for a variety of jobs, says CEO Jeff Maggioncalda. Once they've landed a job, they can then pursue a college degree online, he says. "This idea that you get job skills first, get the job, then get your college degree online while you're working, I think for a lot of people will be more economically effective," he says. In April, Coursera launched a Workforce Recovery Initiative that allows the unemployed in some states and other countries, including Colombia and Singapore, to learn for free until the end of the year.

Online learning providers can offer relatively inexpensive upskilling options because they don't have guidance counselors, classrooms and other features of brick-and-mortar schools. But there could be more of a role for employers to provide those support systems going forward. Dalporto, who calls the wave of automation during COVID-19 "our economic Pearl Harbor," argues that the government should provide a tax credit of $2,500 per upskilled worker to companies that provide retraining. He also suggests that company severance packages include $1,500 in retraining credits.

Some employers are turning to Guild Education, which works with employers to subsidize upskilling. A program it launched in May lets companies pay a fee to have Guild assist laid-off workers in finding new jobs. Employers see this as a way to create loyalty among these former employees, says Rachel Carlson, the CEO of Guild. "The most thoughtful consumer companies say, Employee for now, customer for life," she says.

With the economy 30 million jobs short of what it had before the pandemic, though, workers and employers may not see much use in training for jobs that may not be available for months or even years. And not every worker is interested in studying data science, cloud computing or artificial intelligence.

But those who have found a way to move from dying fields to in-demand jobs are likely to do better. A few years ago, Tristen Alexander was a call-center rep at a Georgia power company when he took a six-month online course to earn a Google IT Support Professional Certificate. A Google scholarship covered the cost for Alexander, who has no college degree and was supporting his wife and two kids on about $38,000 a year. Alexander credits his certificate with helping him win a promotion and says he now earns more than $70,000 annually. What's more, the promotion has given him a sense of job security. "I just think there's a great need for everyone to learn something technical," he tells me.

Of course, Alexander knows that technology may significantly change his job in the next decade, so he's already planning his next step. By 2021, he wants to master the skill of testing computer systems to spot vulnerabilities to hackers and gain a certificate in that practice, known as penetration testing. It will all but guarantee him a job, he says, working alongside the technology that's changing the world.

-With reporting by Alejandro de la Garza and Julia Zorthian/New York
This appears in the August 17, 2020 issue of TIME.
More Must-Reads From TIME

Contact us at letters@time.com.

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Millions of Americans Have Lost Jobs in the Pandemic - And Robots and AI Are Replacing Them Faster Than Ever

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The drive to replace humans is accelerating as companies struggle to avoid workplace infections of COVID-19 and keep operating costs low.

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Could the advancement of AI eventually replace the need for a human workforce?

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At what point do we reach the peak of scientific and technological advancement?

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Brown, S., &amp; Loprest, P. J. (2018, September 28). [Web log post]. Retrieved January 29, 2021, from https://www.urban.org/urban-wire/how-technological-advancement-changing-labor-market

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How is technological advancement changing the labor market?

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Millions of jobs could be lost as a result of new technologies, but millions of jobs will also be created.

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Branscomb, L. M. (2019, July 03). Science, Politics, and U.S. Democracy. Retrieved January 29, 2021, from https://issues.org/branscomb-3/

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Political manipulation of scientific evidence in the interest of ideological convictions has been a commonplace of the U.S. democracy since the end of World War II. In 1952, the incoming secretary of commerce, Sinclair Weeks, fired Alan Astin, director of the National Bureau of Standards, after the Bureau's electrochemists testified for the Federal Trade Commission and Post Office in a suit to stop a small Republican manufacturer from Oakland, California, from fraudulent advertising. The Bureau found that the product, a battery additive called ADX-2, was worthless, and over time would actually harm a battery. Because the administration believed that caveat emptor should take precedence over a laboratory analysis of the product, the Bureau's work came into conflict with the ideology of the Eisenhower administration. Senate Republicans accused the government scientists of not taking the "play of the marketplace" into account in their research. This became a raging controversy that was eventually resolved by Astin's vindication and reinstatement as well as the dismissal of the undersecretary who had urged the firing of Astin in the first place. In January 1973, President Nixon abolished the White House Office of Science and Technology (OST) and the President's Science Advisory Committee (PSAC), when some scientists spoke out publicly against the president's plans for funding the supersonic transport and the antiballistic missile system. Congress and President Ford subsequently reinstated the office by statute.

Both parties have occasionally yielded to the temptation to punish scientists who objected to government policy by cutting their research funding. President Johnson is said to have personally scratched out certain academic research projects because of the researchers' opposition to the war in Vietnam. When President Carter took office in 1977, his Department of Energy (DOE), during the furor over the energy crisis, inherited a study called the Market Oriented Program Planning Study (MOPPS), which found both lower projected demand and a greater abundance of future natural gas supply than the "Malthusians" found acceptable. DOE reportedly sent the study back to the MOPPS team several times, seeking an assessment of future energy resources more acceptable to the administration. They finally ordered the study removed from the shelves of depository libraries, forced the resignation of the director of the U.S. Geological Survey, and removed Christian Knudsen from his position as director of the MOPPS survey.

But the past two years have been unique in the number, scope, and intensity of press reports and scientists' allegations of political interference with the processes for bringing objective scientific information and advice to government policy decisions. The most extensive compilation and interpretation of the allegations of misuse of science advice by the Bush administration is that produced by the Union of Concerned Scientists (UCS); a similar compilation is available on the Web site of Rep. Henry Waxman, ranking member of the Committee on Government Reform. These accusations include suppression or manipulation by high ranking officials of information bearing on public health and the environment, replacement of experts on advisory committees when their views came into conflict with industry or ideological interests, screening of candidates for such committees for their political views, and the deletion of important scientific information from government Web sites. Although a response to the UCS report by the director of the Office of Science and Technology Policy (OSTP) disputed some of the details, the controversy between the scientific community and the administration is not so much over whether these events occurred but rather on the interpretation that should be placed on them and what they might mean for the future of the nation's democracy.

Were these cases examples of unacceptable interference by government officials with entrenched political or ideological positions, resulting in their corruption of otherwise objective science advice? Or were they examples of the unavoidable and natural balancing of political interests and many other factors that influence policy decisions, only one of which is the relevance of available scientific knowledge to the ultimate political decision? Why do the 4,000 U.S. scientists, including many of the country's most distinguished, who have signed on to a February 18, 2004, statement decrying these events, feel so outraged? Why does the White House feel equally strongly that nothing improper has been done? Most importantly, what are the consequences for the functioning of U.S. democracy if this situation cannot be resolved?

Truth and legitimacy

In the U.S. democracy science and politics are uniquely dependent on one another, but the relationship has never been an easy one. Science is about the search for objective evidence that would support successful predictions about the world around us. Politics is about governing based on the public's acceptance of the legitimacy and accountability of elected officials. The search for truth in science and for legitimacy in politics both require systems for generating public trust, but these systems are not the same, and indeed they are often incompatible.

The failure to be open minded and objective in basic science-one might call this scientific bias-is a serious obstacle to scientific progress. In their laboratory research scientists must subject themselves to a disciplined process-transparency in reporting their work, independent verification of results, faithful attention to prior research, and an unrelenting search for alternative explanations and outright mistakes. When a scientist fails to submit to this discipline, the professional penalties can be severe.

Of course, both politicians and policy scholars are quick to point out that giving scientific advice to inform important policy decisions is not at all the same as doing scientific research. In advice to policy, the scientist is often searching for consensus judgments in the absence of full knowledge. Even when scientific understanding is incomplete, judgments about future consequences of policy are required, and the policy process makes rigorous demands on advisors. As policy scholars William C. Clark and Giandomenico Majone pointed out in 1985, if advice is to make a difference in policy, it must satisfy the following criteria: The technical work on which the advice is based must be technically credible; policy relevant, and politically legitimate. More specifically, the scientific analysis must be up to standards of due diligence, using good methods and critical analysis of data. Policy relevance requires that the issues address what the policymakers actually want to know in a timely manner. Legitimacy of the advice derives from an independent scientific effort to get at the truth, free from being shaped as a rhetorical instrument of one interested party or another. All three of these attributes of good advice must be perceived as such by many relevant stakeholders with different preferred outcomes.

Scientists must understand that the officials being advised are not obligated to adopt policies based solely on the scientists' technical analysis.

Minimizing perceptions of bias among scientific advisors is both necessary and difficult. A great deal of attention has been given by scholars and by nongovernmental advisory institutions, such as the National Research Council (NRC), to balancing out the influence of different sources of bias, since bias can never be entirely eliminated. The results of such efforts, plus years of experience with many different processes to improve the ability of scientists to usefully and honestly inform public decisions, has led to the enormously complex system of science advisory bodies the U.S. government uses today. The difficulties are present even when the government officials seeking the advice are scrupulous in their avoidance of political interference in the work of advisors. The advisory system is fragile at best, and it cannot withstand purposeful efforts to corrupt it.

The symbiosis of science and politics

Scientists are fiercely defensive of their intellectual independence, but the financing of most of their research depends on maintaining the confidence and support of Congress and the president. The institutions of science need broad public and political support for their claims to provide both practical and cultural value to society. But the national system of research, especially longer-term or basic research, has a critical dependence on government financial support. In 2003, the federal government provided an estimated $19 billion for R&D to U.S. universities and colleges, and education leaders know that politicians can succumb to the temptation to use the purse as a tool for disciplining scientists who publicly oppose their policies. Perhaps the most extreme case was President Nixon's instruction to his staff to revoke federal research funds to the Massachusetts Institute of Technology because of his annoyance with MIT President Jerome Wiesner's opposition to the antiballistic missile program. His staff wisely declined to execute this intemperate order.

The health of U.S. science also depends on public policy in a variety of other ways-foreign policies that promote or limit scientific collaborations with colleagues abroad, educational investments to attract and train the next generation of scientists, new scientific institutions and facilities that define the leading-edge capabilities of science. Finally, scientists, like other citizens, do care about how society uses the knowledge their research creates. And for this reason, many thousands are happy to serve on advisory committees without financial compensation.

Despite the discomfort they might have with scientists who seem insufficiently grateful for the government's largess or who are too willing to oppose federal policies while accepting federal funding, politicians are also dependent on competent, objective, and useful science advice. In most cases, technical advice is simply a part of the efficient functioning of government agencies that deal with an extraordinarily broad range of technical issues. No agency can expect its own scientific staff to have all the skills required for every task. If nothing else, government scientists need to check their work against the critical judgment of peers outside government. Where political and ideological issues are not in question, this part of the advisory system works very well.

For example, the NRC-the operating arm of the National Academy of Sciences, National Academy of Engineering, and the Institute of Medicine- appoints an array of academic and industrial experts to assess and assure the quality of research at government laboratories such as the National Institute for Standards and Technology. Other committees advise DOE on the research strategy for realizing fusion energy and help the National Science Foundation and the National Aeronautics and Space Administration on priorities for new telescopes on earth and in space. In 2001, the NRC performed 242 studies for the executive branch and Congress. A staff of more than 1,000, working with some 5,000 volunteer experts from universities and industry, prepared these studies and served as quality control reviewers of the finished products. Most of these studies were quite technical and, from a policy perspective, largely uncontroversial.

Government policymakers, however, need the advice of professional experts from outside government for a more profound reason, touching on the basic structure of U.S. democracy. Americans will not give a self-selected elite authority to decide complex matters on their behalf. U.S. leaders are selected by a highly decentralized voting system that, in principle at least, chooses leaders from a broad spectrum of citizens. How can the public judge the performance of these leaders? What makes their actions in office seem legitimate to us, the voters, and what kinds of information do we seek in holding them accountable? In the U.S. political tradition, public officials are judged by what they do, not by who they are.

Contrast the U.S. system with that in France or Japan. In those countries elected officials make the decisive political decisions, but the senior posts in the ministries are held by highly educated career employees. The legitimacy of these officials comes not from the visibility to the public of what actions they take but rather from the prestige associated with their education in a small number of very special schools- the grandes écoles of France and the former imperial universities of Japan. In these countries and in Britain as well, political appointees fill only the very top layer of the ministries; the agencies are run by career professionals. This reflects a level of public trust of senior government officials not found in the United States, where politically appointed officials, serving at the administration's pleasure, are found four or five layers deep in many parts of government.

In France, for example, when the Chernobyl nuclear power plant accident spread radioactive material over the farms of Western Europe, the French government did not announce their tests for radioactive contamination of French crops until nearly a week had passed. Government officials explained that if there had been something the public needed to know, they would have been told. When something goes seriously wrong in the United States, the public immediately demands its leaders to explain "What did they know and when did they know it?" Although the U.S. public possesses limited technical literacy and suspects that segments of the media are guilty of bias, it still turns to the press and independent voices to judge the government's performance. It places its trust in transparency, not in political elites.

This pragmatism in U.S. politics originates with the authors of the Constitution, who sought to build a government "of and by the people," immune to restoration of monarchy. They were creating the world's first constitutional democracy. Reflecting the philosophy of the Enlightenment, the founders saw science as a model for a rational approach to public choices and thus a model for democratic politics.

Politics deals with outcomes people can experience. U.S. voters have traditionally paid relatively little attention to political ideology; the two parties have been fundamentally very similar in philosophy. The philosophical goals of the society (equity, culture, freedom, spiritual well-being) have, in the past, been most effectively expressed politically through empirical evidence-"Are you better off than you were four years ago?"-not by abstract arguments. Letting the facts speak for themselves gives government policies credibility. When the public sees government officials basing their policies on objective, professional knowledge, the public confers authority on those who govern. Appeals to other sources of authority, such as religion or inherited power, disconnect accountability from authority.

This helps political scientists explain why government leaders are more likely to work behind the scenes to shape the advice they receive than they are to shut down the advisory committees. They need the validation that support from committees of experts can bring to their policies. The public expects those policies to be grounded in evidence and reasoned argument. Most presidents, from the right and from the left, have therefore sought to maintain a credible and active system for validating their policies through expert advice from outside government. However, as noted above, when sufficiently unhappy with the advice received, they have some times disowned the advice or even abolished the panel giving the advice.

The importance of trust

Experts giving advice must also earn their legitimacy. To be sure, credentials inevitably play a much bigger role in establishing the right of scientists to claim to be experts. Accordingly, the public insists on transparency in the advisory process, just as it does in government policymaking. That transparency was enacted into law following the push for more open government in the 1970s. The Freedom of Information Act opened up most agency records to public and press inspection. The Federal Advisory Committee Act, passed in 1972, requires access by the press and the public to meetings of most advisory committees. Together with many conflict of interest laws, these acts are expressions of a political will to keep advice given to government open to the sunshine of public witness.

It follows that if either scientists or politicians so politicize their mutual engagement that they sacrifice the credibility of the scientists and the legitimacy of the government officials, the consequences to the nation's time-honored system of governance could be serious indeed. This compels both the scientific community and the government to find a way to bridge the gaps in interests, culture, and process that divide them. They must work together to develop processes that give each the value they seek from the relationship and that also protect the integrity of the relationship against temptations by either side to corrupt it. What, then, are the mechanisms through which these bridges might be built?

Perhaps the most essential structural element in the bridge between science and politics is the understanding that scientists insist on being allowed to inform policy through balanced and expert views of relevant technical facts and best judgments. Indeed, those politicians who believe sound advice will bring added political support to their policies should insist that the technical advice be appropriately organized and managed. However, the scientists must also understand that the officials being advised are not obligated to adopt policies based solely on the scientists' technical analysis. Many factors go into the soup of politics, and artful government requires careful weighing of all these factors.

Litmus tests of political allegiance should not be among these criteria for selecting scientists for advisory committees.

The scientist giving the advice does have recourse if she or he does not like the final decision. The scientist can exercise each citizen's political right to oppose the policy publicly. However, to preserve the nonpolitical nature of the advisory process, the scientist might resign from the panel before going public with a political position. The events leading up to President Nixon's abolition of OST illustrate the difficulty of trying to serve as a nonpolitical advisor while publicly expressing private positions on public issues. A member of PSAC accepted an invitation to testify before Congress about the wisdom of President Nixon's desire to build an antiballistic missile system. In testimony the scientist not only made clear that he spoke for himself and not for PSAC; he also said that his testimony did not rest on information available only to PSAC. He spoke as a knowledgeable private citizen. The press nevertheless interpreted the testimony as evidence that PSAC had given Nixon advice he did not wish to accept, and the president reacted by shutting down PSAC and OST. This happened despite the president's statement to PSAC, relayed by the science advisor, that PSAC members should feel free to testify on either side of the issues and need not resign before doing so.

The sensitivity of the relationship between government officials and independent advisory committees demands clear guidelines for operation. I propose four rules that would help ensure sound and uncorrupted science-based public decisions:

The criteria for selection of scientists to serve on advisory committees, including description of their scientific qualifications and disclosure of all other activities that might bias their judgment, should be publicly documented. Litmus tests of political allegiance should not be among these criteria. Ideological or religious criteria can be considered in making policy but they should not be represented as science.

Key policy and regulatory decisions must not be deliberately deprived of relevant, independent, and expert scientific information. The science advice derived from this information should be published, along with the charter for the study, before the final regulatory decision is made.

An effective system of protections for whistle-blowers must be established to ensure that scientists inside government agencies are able to report with impunity allegations of deliberate political interference with their work and advice.

The president should formally document the policies that are to govern the relationship between science advice and policy, both through advisory structures using scientists outside government and those using government scientists. This should include a set of procedures like those above (and more extensively documented by the NRC) and should identify the locus of responsibility for detecting transgressions of the policy and procedures for investigation and correction if appropriate.

But who is to have the responsibility to oversee adherence to a presidential policy that insists on competent, objective, balanced, and open advice, and how is the policy to be enforced? The conventional institutional answer is the president's science advisor.

The president's science advisor

Before we can talk about who can bridge the gap between science and politics, we need to describe the turbulence that flows under the bridge. Scientists who have extensive government experience understand the conflict between the scientists' demand for an advisory system giving balanced, objective, and technically expert advice and the government official's insistence on panel members who share the president's political philosophy. If the president's science advisor is to mediate this conflict, he or she must understand and bridge both interests.

But listen to William D. Carey, former assistant director of the Bureau of the Budget and executive officer of the American Association for the Advancement of Science: "If a science advisor is going to count, he must be a foot soldier marching to the program of the president, not the company chaplain." I would characterize this as an extreme, perhaps even demeaning, view of the role of science advisor to the president. I am sure John Marburger does not so characterize his job as director of OSTP in the executive office of President Bush. Indeed, to be effective, a science advisor to the president must be somewhat aloof from the demands of tactical politics. However, this independence is not to be exercised by failing to support the president's established policies. It is won by the very high level of respect accorded the advisor's scientific qualifications and prestige and by his or her acceptance of the broad framework of presidential policy.

If the president is serious about protecting the time-honored system of scientific inputs to inform policy, as President Bush has publicly affirmed, the president's own prestige, the effectiveness of his governance, and the strength of the nation's commitment to science would all benefit. But while the scientific community and the press refer to Marburger as the "president's science advisor," this is not his official title. Bush did not appoint Marburger to the traditional White House position of assistant to the president for science and technology. His formal position is director of OSTP, reporting to chief of staff Andrew Card. Had he been included in the president's White House inner circle and given the position assistant to the president accorded to D. Allan Bromley by President George H. W. Bush, perhaps many of the events catalogued by UCS might have been avoided.

It might be, however, that behind the stressful relations between many scientists and President Bush over the events documented by UCS, something much more fundamental and foreboding is happening in U.S. politics, developments that might lie beyond thescience advisor's ability to correct. In the earlier discussion it was pointed out that U.S. voters traditionally measure their leaders by objective assessments of what they achieve for the lives of the people. Political scientists have written that U.S. pragmatism traditionally outweighs the influence of ideology, religion, and elite connections. Scholars tell us that it was for that reason that government officials, over the years, encouraged the best and the brightest of science to advise the government or even to make careers in science-based public policy. But all that seems to be changing.

In the current presidential campaign much of the debate, especially from the Republican side, is, in fact, about social, religious, and patriotic values. Some of most intense conflicts between science advice and public policy have turned on objections by scientists to the primacy of ideology over science. Fourteen years ago scholars were already observing a growing preference for images that presented the appearance of pragmatic measures of achievement. We now live in an era of images and "spin." In her 1990 book The Fifth Branch: Science Advisors as Policy Makers, Sheila Jasanoff writes, "In the closing decades of the 20th century the intellectual and technical advance of science coincides with its visible decline as a force in the rhetoric of liberal-democratic politics."

The integrity of the science advisory process cannot withstand overt actions to censor or suppress unwanted advice, to mischaracterize it, or to construct it by use of political litmus tests in the selection of individuals to serve on committees. Nor can it survive threats to the job security of scientists in government when they attempt to call such political interventions to the attention of Congress or the press. Science advice must not be allowed to become politically or ideologically constructed. If we fail in the attempt to preserve the integrity of science in democratic governance, a strong source of unity in the electorate, based on common interest in the actual performance of government, will be eroded. Policymaking by ideology requires that reality be set aside; it can be maintained only by moving towards ever more authoritarian forms of governance.

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Science, Politics, and U.S. Democracy | Issues in Science and Technology

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But who is to have the responsibility to oversee adherence to a presidential policy that insists on competent, objective, balanced, and open advice, and how is the policy to be enforced? The conventional institutional answer is the president's science advisor. The president's science advisor Before we can talk about who can bridge the gap between [...]

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Becoming political

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Making science fiction a reality

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Find new uses for old tech

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Improved tech can make life easier

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People becoming less social

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Technology affects the way individuals communicate, learn, and think. It helps society and determines how people interact with each other on a daily basis. Technology plays an important role in society today. It has positive and negative effects on the world and it impacts daily lives. We are living in an era where technological advances are common. The internet and cell phones are some examples. However, with technological advances, there's a downside to it all.

One aspect of technology that has had a great impact on society is how it affects learning. It's made learning more interactive and collaborative, this helps people better engage with the material that they are learning and have trouble with. Also, it gets you better access to resources. With the creation of the internet, it gives us access to information at a twenty-four-hour rate and you have access to almost anything online. In addition, it allows students to get work done easier. Students can take quizzes and exams more easily, and teachers being able to hold online classes can be very effective. It also expands the boundaries of the classroom, encouraging self-paced learning. People can access learning through YouTube and social media. This helps students learn better than sitting down for lectures and reading from textbooks. These technological advancements made learning more fun and convenient.

Another way technology has impacted society is through communication, how we talk and communicate with one another worldwide. Technology brought many new methods of electronic communication. For example, there are emails, social networking, you can facetime a person that lives on the other side of the world, and here's video conferencing where you can have conferences electronically. Lastly, the technological advancements that were made within the health industry have helped keep people safe and healthy. There are many innovate apps on phones that although people to watch their weight, how many calories they intake, heart rate and other health properties any time of the day. There's increased accessibility of treatment available, there's the change in healthcare that adds benefits for the elderly, and hospitals using advanced technology within their surgical rooms.

However, studies show that mobile communication affects people in a negative way when it comes to being sociable and making face-to-face contact. Mobile technology can decrease communication and relations between people. There's less personal time, where you find that you don't enough time for yourself because you're always in contact with someone. Also, it can be distracting from your schoolwork. There is also loss of privacy, because anyone can find you anywhere, at any time of the day. In conclusion, all of these things impact how humans act today. Without technological advancements, our way of life would not be as complex. Technological influences shape the way humans act today.

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Technological Influence on Society | BCTV

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Technology affects the way individuals communicate, learn, and think. It helps society and determines how people interact with each other on a daily basis. Technology plays an important role in society today. It has positive and negative effects on the world and it impacts daily lives.

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Create new diseases

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Develop new medicine

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Machines replacing people

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For 23 years, Larry Collins worked in a booth on the Carquinez Bridge in the San Francisco Bay Area, collecting tolls. The fare changed over time, from a few bucks to $6, but the basics of the job stayed the same: Collins would make change, answer questions, give directions and greet commuters. "Sometimes, you're the first person that people see in the morning," says Collins, "and that human interaction can spark a lot of conversation."

But one day in mid-March, as confirmed cases of the coronavirus were skyrocketing, Collins' supervisor called and told him not to come into work the next day. The tollbooths were closing to protect the health of drivers and of toll collectors. Going forward, drivers would pay bridge tolls automatically via FasTrak tags mounted on their windshields or would receive bills sent to the address linked to their license plate. Collins' job was disappearing, as were the jobs of around 185 other toll collectors at bridges in Northern California, all to be replaced by technology.

Machines have made jobs obsolete for centuries. The spinning jenny replaced weavers, buttons displaced elevator operators, and the Internet drove travel agencies out of business. One study estimates that about 400,000 jobs were lost to automation in U.S. factories from 1990 to 2007. But the drive to replace humans with machinery is accelerating as companies struggle to avoid workplace infections of COVID-19 and to keep operating costs low. The U.S. shed around 40 million jobs at the peak of the pandemic, and while some have come back, some will never return. One group of economists estimates that 42% of the jobs lost are gone forever.

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This replacement of humans with machines may pick up more speed in coming months as companies move from survival mode to figuring out how to operate while the pandemic drags on. Robots could replace as many as 2 million more workers in manufacturing alone by 2025, according to a recent paper by economists at MIT and Boston University. "This pandemic has created a very strong incentive to automate the work of human beings," says Daniel Susskind, a fellow in economics at Balliol College, University of Oxford, and the author of A World Without Work: Technology, Automation and How We Should Respond. "Machines don't fall ill, they don't need to isolate to protect peers, they don't need to take time off work."

As with so much of the pandemic, this new wave of automation will be harder on people of color like Collins, who is Black, and on low-wage workers. Many Black and Latino Americans are cashiers, food-service employees and customer-service representatives, which are among the 15 jobs most threatened by automation, according to McKinsey. Even before the pandemic, the global consulting company estimated that automation could displace 132,000 Black workers in the U.S. by 2030.

The deployment of robots as a response to the coronavirus was rapid. They were suddenly cleaning floors at airports and taking people's temperatures. Hospitals and universities deployed Sally, a salad-making robot created by tech company Chowbotics, to replace dining-hall employees; malls and stadiums bought Knightscope security-guard robots to patrol empty real estate; companies that manufacture in-demand supplies like hospital beds and cotton swabs turned to industrial robot supplier Yaskawa America to help increase production.

Companies closed call centers employing human customer-service agents and turned to chatbots created by technology company LivePerson or to AI platform Watson Assistant. "I really think this is a new normal-the pandemic accelerated what was going to happen anyway," says Rob Thomas, senior vice president of cloud and data platform at IBM, which deploys Watson. Roughly 100 new clients started using the software from March to June.

In theory, automation and artificial intelligence should free humans from dangerous or boring tasks so they can take on more intellectually stimulating assignments, making companies more productive and raising worker wages. And in the past, technology was deployed piecemeal, giving employees time to transition into new roles. Those who lost jobs could seek retraining, perhaps using severance pay or unemployment benefits to find work in another field. This time the change was abrupt as employers, worried about COVID-19 or under sudden lockdown orders, rushed to replace workers with machines or software. There was no time to retrain. Companies worried about their bottom line cut workers loose instead, and these workers were left on their own to find ways of mastering new skills. They found few options.

In the past, the U.S. responded to technological change by investing in education. When automation fundamentally changed farm jobs in the late 1800s and the 1900s, states expanded access to public schools. Access to college expanded after World War II with the GI Bill, which sent 7.8 million veterans to school from 1944 to 1956. But since then, U.S. investment in education has stalled, putting the burden on workers to pay for it themselves. And the idea of education in the U.S. still focuses on college for young workers rather than on retraining employees. The country spends 0.1% of GDP to help workers navigate job transitions, less than half what it spent 30 years ago.

"The real automation problem isn't so much a robot apocalypse," says Mark Muro, a senior fellow at the Brookings Institution. "It is business as usual of people needing to get retraining, and they really can't get it in an accessible, efficient, well-informed, data-driven way."

This means that tens of thousands of Americans who lost jobs during the pandemic may be unemployed for years or, in Collins' case, for good. Though he has access to retraining funding through his union contract, "I'm too old to think about doing some other job," says Collins, who is 63 and planning on taking early retirement. "I just want to go back to what I was doing."

Check into a hotel today, and a mechanical butler designed by robotics company Savioke might roll down the hall to deliver towels and toothbrushes. ("No tip required," Savioke notes on its website.) Robots have been deployed during the pandemic to meet guests at their rooms with newly disinfected keys. A bricklaying robot can lay more than 3,000 bricks in an eight-hour shift, up to 10 times what a human can do. Robots can plant seeds and harvest crops, separate breastbones and carcasses in slaughterhouses, pack pallets of food in processing facilities.

That doesn't mean they're taking everyone's jobs. For centuries, humans from weavers to mill workers have worried that advances in technology would create a world without work, and that's never proved true. ATMs did not immediately decrease the number of bank tellers, for instance. They actually led to more teller jobs as consumers, lured by the convenience of cash machines, began visiting banks more often. Banks opened more branches and hired tellers to handle tasks that are beyond the capacity of ATMs. Without technological advancement, much of the American workforce would be toiling away on farms, which accounted for 31% of U.S. jobs in 1910 and now account for less than 1%.

But in the past, when automation eliminated jobs, companies created new ones to meet their needs. Manufacturers that were able to produce more goods using machines, for example, needed clerks to ship the goods and marketers to reach additional customers.

Now, as automation lets companies do more with fewer people, successful companies don't need as many workers. The most valuable company in the U.S. in 1964, AT&T, had 758,611 employees; the most valuable company today, Apple, has around 137,000 employees. Though today's big companies make billions of dollars, they share that income with fewer employees, and more of their profit goes to shareholders. "Look at the business model of Google, Facebook, Netflix. They're not in the business of creating new tasks for humans," says Daron Acemoglu, an MIT economist who studies automation and jobs.

The U.S. government incentivizes companies to automate, he says, by giving tax breaks for buying machinery and software. A business that pays a worker $100 pays $30 in taxes, but a business that spends $100 on equipment pays about $3 in taxes, he notes. The 2017 Tax Cuts and Jobs Act lowered taxes on purchases so much that "you can actually make money buying equipment," Acemoglu says.

In addition, artificial intelligence is becoming more adept at jobs that once were the purview of humans, making it harder for humans to stay ahead of machines. JPMorgan says it now has AI reviewing commercial-loan agreements, completing in seconds what used to take 360,000 hours of lawyers' time over the course of a year. In May, amid plunging advertising revenue, Microsoft laid off dozens of journalists at MSN and its Microsoft News service, replacing them with AI that can scan and process content. Radio group iHeartMedia has laid off dozens of DJs to take advantage of its investments in technology and AI. I got help transcribing interviews for this story using Otter.ai, an AI-based transcription service. A few years ago, I might have paid $1 a minute for humans to do the same thing.

These advances make AI an easy choice for companies scrambling to cope during the pandemic. Municipalities that had to close their recycling facilities, where humans worked in close quarters, are using AI-assisted robots to sort through tons of plastic, paper and glass. AMP Robotics, the company that makes these robots, says inquiries from potential customers increased at least fivefold from March to June. Last year, 35 recycling facilities used AMP Robotics, says AMP spokesman Chris Wirth; by the end of 2020, nearly 100 will.

RDS Virginia, a recycling company in Virginia, purchased four AMP robots in 2019 for its Roanoke facility, deploying them on assembly lines to ensure the paper and plastic streams were free of misplaced materials. The robots could work around the clock, didn't take bathroom breaks and didn't require safety training, says Joe Benedetto, the company's president. When the coronavirus hit, robots took over quality control as humans were pulled off assembly lines and given tasks that kept them at a safe distance from one another. Benedetto breathes easier knowing he won't have to raise the robots' pay to meet the minimum wage. He's already thinking about where else he can deploy them. "There are a few reasons I prefer machinery," Benedetto says. "For one thing, as long as you maintain it, it's there every day to work."

Companies deploying automation and AI say the technology allows them to create new jobs. But the number of new jobs is often minuscule compared with the number of jobs lost. LivePerson, which designs conversational software, could enable a company to take a 1,000-person call center and run it with 100 people plus chatbots, says CEO Rob LoCascio. A bot can respond to 10,000 queries in an hour, LoCascio says; an efficient call-center rep can answer six.

LivePerson saw a fourfold increase in demand in March as companies closed call centers, LoCascio says. "What happened was the contact-center representatives went home, and a lot of them can't work from home," he says.

Some surprising businesses are embracing automation. David's Bridal, which sells wedding gowns and other formal wear in about 300 stores across North America and the U.K., set up a chatbot called Zoey through LivePerson last year. When the pandemic forced David's Bridal to close its stores, Zoey helped manage customer inquiries flooding the company's call centers, says Holly Carroll, vice president of the customer-service and contact center. Without a bot, "we would have been dead in the water," Carroll says.

David's Bridal now spends 35% less on call centers and can handle three times more messages through its chatbot than it can through voice or email. (Zoey may be cheaper than a human, but it is not infallible. Via text, Zoey promised to connect me to a virtual stylist, but I never heard back from it or the company.)

Many organizations will likely look to technology as they face budget cuts and need to reduce staff. "I don't see us going back to the staffing levels we were at prior to COVID," says Brian Pokorny, the director of information technologies for Otsego County in New York State, who has cut 10% of his staff because of pandemic-related budget issues. "So we need to look at things like AI to streamline government services and make us more efficient."

Pokorny used a free trial from IBM's Watson Assistant early in the pandemic and set up an AI-powered web chat to answer questions from the public, like whether the National Baseball Hall of Fame in Cooperstown, the county seat, had reopened. (It had, as of June 26, with limited capacity.) Now, Watson can answer 75% of the questions people ask, and Otsego County has started paying for the service, which Pokorny says costs "pennies" per conversation. Though the county now uses AI just for online chats, it plans to deploy a Watson virtual assistant that can answer phone calls. Around 36 states have deployed chatbots to respond to questions about the pandemic and available government services, according to the National Association of State Chief Information Officers.

IBM and LivePerson say that by creating AI, they're freeing up humans to do more sophisticated tasks. Companies that contract with LivePerson still need "bot builders" to help teach the AI how to answer questions, and call-center agents see their pay increase by about 15% when they become bot builders, LoCascio says. "We can look at it like there's going to be this massive job loss, or we can look at it that people get moved into different places and positions in the world to better their lives," LoCascio says.

But companies will need far fewer bot builders than call-center agents, and mobility is not always an option, especially for workers without college degrees or whose employers do not offer retraining. Non-union workers are especially vulnerable. Larry Collins and his colleagues, represented by SEIU Local 1000, were fortunate: they're being paid their full salaries for the foreseeable future in exchange for taking 32 hours a week of online classes in computer skills, accounting, entrepreneurship and other fields. (Some might even get their jobs back, albeit temporarily, as the state upgrades its systems.) But just 11.6 % of American workers were represented by a union in 2019.

Yvonne R. Walker, the union president, says most non-union workers don't get this kind of assistance. "Companies out there don't provide employee training and upskilling-they don't see it as a good investment," Walker says. "Unless workers have a union thinking about these things, the workers get left behind."

In Sweden, employers pay into private funds that help workers get retrained; Singapore's SkillsFuture program reimburses citizens up to 500 Singapore dollars (about $362 in U.S. currency) for approved retraining courses. But in the U.S., the most robust retraining programs are for workers whose jobs are sent overseas or otherwise lost because of trade issues. A few states have started promising to pay community-college tuition for adult learners who seek retraining; the Tennessee Reconnect program pays for adults over 25 without college degrees to get certificates, associate's degrees and technical diplomas. But a similar program in Michigan is in jeopardy as states struggle with budget issues, says Michelle Miller-Adams, a researcher at the W.E. Upjohn Institute for Employment Research.

House and Senate Democrats introduced a $15 billion workforce-retraining bill in early May, but it hasn't gained much traction with Republicans, who prefer to encourage retraining by giving tax credits. The federal funds that exist come with restrictions. Pell Grants, which help low-income students pay for education, can't be used for nontraditional programs like boot camps or a 170-hour EMT certification. Local jobless centers, which receive federal funds, spend an average of $3,500 per person on retraining, but they usually run out of money early in a calendar year because of limited funding, says Ayobami Olugbemiga, press secretary at the National Skills Coalition.

Even if federal funding were widely available, the surge of people who need retraining would be more than universities can handle, says Gabe Dalporto, the CEO of Udacity, which offers online courses in programming, data science, AI and more. "A billion people will lose their jobs over the next 10 years due to AI, and if anything, COVID has accelerated that by about nine years," says Dalporto. "If you tried to reskill a billion people in the university system, you would break the university system."

Dalporto says t he coronavirus should be a wake-up call for the federal government to rethink how it funds education. "We have this model where we want to dump huge amounts of capital into very slow, noncareer-specific education," Dalporto says. "If you just repurposed 10% of that, you could retrain 3 million people in about six months."

Online education providers say they can provide retraining and upskilling on workers' own timelines, and for less money than traditional schools. Coursera offers six-month courses for $39 to $79 a month that provide students with certifications needed for a variety of jobs, says CEO Jeff Maggioncalda. Once they've landed a job, they can then pursue a college degree online, he says. "This idea that you get job skills first, get the job, then get your college degree online while you're working, I think for a lot of people will be more economically effective," he says. In April, Coursera launched a Workforce Recovery Initiative that allows the unemployed in some states and other countries, including Colombia and Singapore, to learn for free until the end of the year.

Online learning providers can offer relatively inexpensive upskilling options because they don't have guidance counselors, classrooms and other features of brick-and-mortar schools. But there could be more of a role for employers to provide those support systems going forward. Dalporto, who calls the wave of automation during COVID-19 "our economic Pearl Harbor," argues that the government should provide a tax credit of $2,500 per upskilled worker to companies that provide retraining. He also suggests that company severance packages include $1,500 in retraining credits.

Some employers are turning to Guild Education, which works with employers to subsidize upskilling. A program it launched in May lets companies pay a fee to have Guild assist laid-off workers in finding new jobs. Employers see this as a way to create loyalty among these former employees, says Rachel Carlson, the CEO of Guild. "The most thoughtful consumer companies say, Employee for now, customer for life," she says.

With the economy 30 million jobs short of what it had before the pandemic, though, workers and employers may not see much use in training for jobs that may not be available for months or even years. And not every worker is interested in studying data science, cloud computing or artificial intelligence.

But those who have found a way to move from dying fields to in-demand jobs are likely to do better. A few years ago, Tristen Alexander was a call-center rep at a Georgia power company when he took a six-month online course to earn a Google IT Support Professional Certificate. A Google scholarship covered the cost for Alexander, who has no college degree and was supporting his wife and two kids on about $38,000 a year. Alexander credits his certificate with helping him win a promotion and says he now earns more than $70,000 annually. What's more, the promotion has given him a sense of job security. "I just think there's a great need for everyone to learn something technical," he tells me.

Of course, Alexander knows that technology may significantly change his job in the next decade, so he's already planning his next step. By 2021, he wants to master the skill of testing computer systems to spot vulnerabilities to hackers and gain a certificate in that practice, known as penetration testing. It will all but guarantee him a job, he says, working alongside the technology that's changing the world.

-With reporting by Alejandro de la Garza and Julia Zorthian/New York
This appears in the August 17, 2020 issue of TIME.
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Millions of Americans Have Lost Jobs in the Pandemic - And Robots and AI Are Replacing Them Faster Than Ever

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The drive to replace humans is accelerating as companies struggle to avoid workplace infections of COVID-19 and keep operating costs low.

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Help further science

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Allen, M. (2019, October 28). Technological Influence on Society. Retrieved January 30, 2021, from https://www.bctv.org/2019/11/07/technological-influence-on-society/#:~:text=Technology%20affects%20the%20way%20individuals,other%20on%20a%20daily%20basis.&amp;text=It's%20made%20learning%20more%20interactive,learning%20and%20have%20trouble%20with.

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Technology affects the way individuals communicate, learn, and think. It helps society and determines how people interact with each other on a daily basis. Technology plays an important role in society today. It has positive and negative effects on the world and it impacts daily lives. We are living in an era where technological advances are common. The internet and cell phones are some examples. However, with technological advances, there's a downside to it all.

One aspect of technology that has had a great impact on society is how it affects learning. It's made learning more interactive and collaborative, this helps people better engage with the material that they are learning and have trouble with. Also, it gets you better access to resources. With the creation of the internet, it gives us access to information at a twenty-four-hour rate and you have access to almost anything online. In addition, it allows students to get work done easier. Students can take quizzes and exams more easily, and teachers being able to hold online classes can be very effective. It also expands the boundaries of the classroom, encouraging self-paced learning. People can access learning through YouTube and social media. This helps students learn better than sitting down for lectures and reading from textbooks. These technological advancements made learning more fun and convenient.

Another way technology has impacted society is through communication, how we talk and communicate with one another worldwide. Technology brought many new methods of electronic communication. For example, there are emails, social networking, you can facetime a person that lives on the other side of the world, and here's video conferencing where you can have conferences electronically. Lastly, the technological advancements that were made within the health industry have helped keep people safe and healthy. There are many innovate apps on phones that although people to watch their weight, how many calories they intake, heart rate and other health properties any time of the day. There's increased accessibility of treatment available, there's the change in healthcare that adds benefits for the elderly, and hospitals using advanced technology within their surgical rooms.

However, studies show that mobile communication affects people in a negative way when it comes to being sociable and making face-to-face contact. Mobile technology can decrease communication and relations between people. There's less personal time, where you find that you don't enough time for yourself because you're always in contact with someone. Also, it can be distracting from your schoolwork. There is also loss of privacy, because anyone can find you anywhere, at any time of the day. In conclusion, all of these things impact how humans act today. Without technological advancements, our way of life would not be as complex. Technological influences shape the way humans act today.

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Technological Influence on Society | BCTV

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Technology affects the way individuals communicate, learn, and think. It helps society and determines how people interact with each other on a daily basis. Technology plays an important role in society today. It has positive and negative effects on the world and it impacts daily lives.

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Johnson, J. (2020, February 25). Negative effects of technology: Psychological, social, and health. Retrieved January 30, 2021, from https://www.medicalnewstoday.com/articles/negative-effects-of-technology

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Advancements in technology allow people to be more connected than ever, but this may come at a price. Overuse of social media and mobile devices have been linked to eyestrain, difficulty focusing on other tasks, and depression.

While some forms of technology may have made positive changes in the world, there is evidence for the negative effects of technology and its overuse, as well.

The overuse of technology may have a more significant impact on developing children and teenagers.

In this article, learn about the psychological and physical health effects of technology, as well as how to create healthful habits with technology and avoid overuse.

Overuse or dependence on technology may have adverse psychological effects, including:

Isolation

Technologies, such as social media, are designed to bring people together, yet they may have the opposite effect in some cases.

A 2017 study in young adults aged 19-32 years found that people with higher social media use were more than three times as likely to feel socially isolated than those who did not use social media as often.

Finding ways to reduce social media use, such as setting time limits for social apps, may help reduce feelings of isolation in some people.

Depression and anxiety

The authors of a 2016 systematic review discussed the link between social networks and mental health issues, such as depression and anxiety.

Their research found mixed results. People who had more positive interactions and social support on these platforms appeared to have lower levels of depression and anxiety.

However, the reverse was also true. People who perceived that they had more negative social interactions online and who were more prone to social comparison experienced higher levels of depression and anxiety.

So, while there does appear to be a link between social media and mental health, a significant determining factor is the types of interactions people feel they are having on these platforms.

Technology use may increase the risk of physical issues as well, including:

Eyestrain

Technologies, such as handheld tablets, smartphones, and computers, can hold a person's attention for long periods. This may lead to eyestrain.

Symptoms of digital eyestrain can include blurred vision and dry eyes. Eyestrain may also lead to pains in other areas of the body, such as the head, neck, or shoulders.

Several technological factors may lead to eyestrain, such as:

screen time

screen glare

screen brightness

viewing too close or too far away

poor sitting posture

underlying vision issues

Taking regular breaks away from the screen may reduce the likelihood of eyestrain.

Anyone regularly experiencing these symptoms should see an optometrist for a checkup.

The 20-20-20 rule for digital viewing

When using any form of digital screen for longer periods of time, the American Optometric Association recommend using the 20-20-20 rule.

To use the rule, after every 20 minutes of screen time, take a 20-second break to look at something at least 20 feet away.

Doing this may help reduce the strain on the eyes from staring at a screen for a continuous period.
Learn more about the 20-20-20 rule in this article.
Poor posture

The way many people use mobile devices and computers may also contribute to incorrect posture. Over time, this may lead to musculoskeletal issues.

Many technologies promote a "down and forward" user position, meaning the person is hunched forward and looking down at the screen. This can put an unnecessary amount of pressure on the neck and spine.

A 5-year study in the journal Applied Ergonomics found an association between texting on a mobile phone and neck or upper back pain in young adults.

The results indicated the effects were mostly short term, though some people continued to have long-term symptoms.

However, some studies challenge these results.

A in the European Spine Journal found that the posture of the neck while texting made no difference in symptoms such as neck pain.

This study concluded that texting and "text neck" did not influence neck pain in young adults. However, the study did not include a long-term follow-up.

It may be that other factors influence neck pain, as well, such as age and activity levels.

Correcting posture problems while using technology may lead to an overall improvement in posture and strength in the core, neck, and back.

For example, if a person finds themselves sitting in the same position for hours at a time, such as sitting at a desk while working, regularly standing or stretching may help reduce strain on the body.

Additionally, taking short breaks, such as walking around the office every hour, may also help keep the muscles loose and avoid tension and incorrect posture.
Learn more about how to stay active and in good posture at work with this article.
Sleep problems

Using technology too close to bedtime may cause issues with sleep. This effect has to do with the fact that blue light, such as the light from cell phones, e-readers, and computers, stimulates the brain.

Authors of a 2014 study found that this blue light is enough to disturb the body's natural circadian rhythm. This disturbance could make it harder to fall asleep or lead to a person feeling less alert the next day.

To avoid the potential impact of blue light on the brain, people can stop using electronic devices that emit blue light in the hour or two before bedtime.

Gentle activities to wind down with instead, such as reading a book, doing gentle stretches, or taking a bath, are alternatives.

Reduced physical activity

Most everyday digital technologies are sedentary. More extended use of these technologies promotes a more sedentary lifestyle, which is known to have negative health effects, such as contributing to:

Finding ways to take breaks from sedentary technologies may help promote a more active lifestyle.

Other forms of technology may help, however.

Research from 2017 indicates that active technologies, such as app notifications, emails, and wearable technologies that promote exercise may reduce short-term sedentary behavior.

This could help people set healthful patterns and become more physically active.

Children's brains are still developing and may be more sensitive to the effects of technology and its overuse than adult brains.

A 2018 review of various studies noted the possible adverse effects of children using different technologies.

Children who overuse technology may be more likely to experience issues, including:

low academic performance

lack of attention

low creativity

delays in language development

delays in social and emotional development

physical inactivity and obesity

poor sleep quality

social issues, such as social incompatibility and anxiety

aggressive behaviors

addiction to these technologies

The research also noted the importance of teaching children to interact with these technologies in healthful ways by monitoring their time using them and providing interesting alternatives.

Additionally, a study of teenagers aged 15-16 found that those who had high digital media use had an increased chance of developing symptoms of attention-deficit hyperactivity disorder (ADHD).

This does not mean that digital media use causes ADHD, rather that there is an association between the two. More research needs to determine what this association means.

The authors of 2015 research found that technology appears to negatively affect the overall health of children and teenagers of all ages. Researchers noted the importance of parents and caregivers controlling screen time in all children.

The American Academy of Pediatrics recommend children under 18 months old avoid screen time altogether, while 2-5-year-olds have no more than 1 hour a day of high-quality viewing with an adult.

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Negative effects of technology: Psychological, social, and health

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While technology has many positives, it can also lead to negative psychological and physical health effects. Learn about the adverse effects of technology here.

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Does government overwatch hinder advancement or protect society from "mad scientist"

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Political manipulation of scientific evidence in the interest of ideological convictions has been a commonplace of the U.S. democracy since the end of World War II. In 1952, the incoming secretary of commerce, Sinclair Weeks, fired Alan Astin, director of the National Bureau of Standards, after the Bureau's electrochemists testified for the Federal Trade Commission and Post Office in a suit to stop a small Republican manufacturer from Oakland, California, from fraudulent advertising. The Bureau found that the product, a battery additive called ADX-2, was worthless, and over time would actually harm a battery. Because the administration believed that caveat emptor should take precedence over a laboratory analysis of the product, the Bureau's work came into conflict with the ideology of the Eisenhower administration. Senate Republicans accused the government scientists of not taking the "play of the marketplace" into account in their research. This became a raging controversy that was eventually resolved by Astin's vindication and reinstatement as well as the dismissal of the undersecretary who had urged the firing of Astin in the first place. In January 1973, President Nixon abolished the White House Office of Science and Technology (OST) and the President's Science Advisory Committee (PSAC), when some scientists spoke out publicly against the president's plans for funding the supersonic transport and the antiballistic missile system. Congress and President Ford subsequently reinstated the office by statute.

Both parties have occasionally yielded to the temptation to punish scientists who objected to government policy by cutting their research funding. President Johnson is said to have personally scratched out certain academic research projects because of the researchers' opposition to the war in Vietnam. When President Carter took office in 1977, his Department of Energy (DOE), during the furor over the energy crisis, inherited a study called the Market Oriented Program Planning Study (MOPPS), which found both lower projected demand and a greater abundance of future natural gas supply than the "Malthusians" found acceptable. DOE reportedly sent the study back to the MOPPS team several times, seeking an assessment of future energy resources more acceptable to the administration. They finally ordered the study removed from the shelves of depository libraries, forced the resignation of the director of the U.S. Geological Survey, and removed Christian Knudsen from his position as director of the MOPPS survey.

But the past two years have been unique in the number, scope, and intensity of press reports and scientists' allegations of political interference with the processes for bringing objective scientific information and advice to government policy decisions. The most extensive compilation and interpretation of the allegations of misuse of science advice by the Bush administration is that produced by the Union of Concerned Scientists (UCS); a similar compilation is available on the Web site of Rep. Henry Waxman, ranking member of the Committee on Government Reform. These accusations include suppression or manipulation by high ranking officials of information bearing on public health and the environment, replacement of experts on advisory committees when their views came into conflict with industry or ideological interests, screening of candidates for such committees for their political views, and the deletion of important scientific information from government Web sites. Although a response to the UCS report by the director of the Office of Science and Technology Policy (OSTP) disputed some of the details, the controversy between the scientific community and the administration is not so much over whether these events occurred but rather on the interpretation that should be placed on them and what they might mean for the future of the nation's democracy.

Were these cases examples of unacceptable interference by government officials with entrenched political or ideological positions, resulting in their corruption of otherwise objective science advice? Or were they examples of the unavoidable and natural balancing of political interests and many other factors that influence policy decisions, only one of which is the relevance of available scientific knowledge to the ultimate political decision? Why do the 4,000 U.S. scientists, including many of the country's most distinguished, who have signed on to a February 18, 2004, statement decrying these events, feel so outraged? Why does the White House feel equally strongly that nothing improper has been done? Most importantly, what are the consequences for the functioning of U.S. democracy if this situation cannot be resolved?

Truth and legitimacy

In the U.S. democracy science and politics are uniquely dependent on one another, but the relationship has never been an easy one. Science is about the search for objective evidence that would support successful predictions about the world around us. Politics is about governing based on the public's acceptance of the legitimacy and accountability of elected officials. The search for truth in science and for legitimacy in politics both require systems for generating public trust, but these systems are not the same, and indeed they are often incompatible.

The failure to be open minded and objective in basic science-one might call this scientific bias-is a serious obstacle to scientific progress. In their laboratory research scientists must subject themselves to a disciplined process-transparency in reporting their work, independent verification of results, faithful attention to prior research, and an unrelenting search for alternative explanations and outright mistakes. When a scientist fails to submit to this discipline, the professional penalties can be severe.

Of course, both politicians and policy scholars are quick to point out that giving scientific advice to inform important policy decisions is not at all the same as doing scientific research. In advice to policy, the scientist is often searching for consensus judgments in the absence of full knowledge. Even when scientific understanding is incomplete, judgments about future consequences of policy are required, and the policy process makes rigorous demands on advisors. As policy scholars William C. Clark and Giandomenico Majone pointed out in 1985, if advice is to make a difference in policy, it must satisfy the following criteria: The technical work on which the advice is based must be technically credible; policy relevant, and politically legitimate. More specifically, the scientific analysis must be up to standards of due diligence, using good methods and critical analysis of data. Policy relevance requires that the issues address what the policymakers actually want to know in a timely manner. Legitimacy of the advice derives from an independent scientific effort to get at the truth, free from being shaped as a rhetorical instrument of one interested party or another. All three of these attributes of good advice must be perceived as such by many relevant stakeholders with different preferred outcomes.

Scientists must understand that the officials being advised are not obligated to adopt policies based solely on the scientists' technical analysis.

Minimizing perceptions of bias among scientific advisors is both necessary and difficult. A great deal of attention has been given by scholars and by nongovernmental advisory institutions, such as the National Research Council (NRC), to balancing out the influence of different sources of bias, since bias can never be entirely eliminated. The results of such efforts, plus years of experience with many different processes to improve the ability of scientists to usefully and honestly inform public decisions, has led to the enormously complex system of science advisory bodies the U.S. government uses today. The difficulties are present even when the government officials seeking the advice are scrupulous in their avoidance of political interference in the work of advisors. The advisory system is fragile at best, and it cannot withstand purposeful efforts to corrupt it.

The symbiosis of science and politics

Scientists are fiercely defensive of their intellectual independence, but the financing of most of their research depends on maintaining the confidence and support of Congress and the president. The institutions of science need broad public and political support for their claims to provide both practical and cultural value to society. But the national system of research, especially longer-term or basic research, has a critical dependence on government financial support. In 2003, the federal government provided an estimated $19 billion for R&D to U.S. universities and colleges, and education leaders know that politicians can succumb to the temptation to use the purse as a tool for disciplining scientists who publicly oppose their policies. Perhaps the most extreme case was President Nixon's instruction to his staff to revoke federal research funds to the Massachusetts Institute of Technology because of his annoyance with MIT President Jerome Wiesner's opposition to the antiballistic missile program. His staff wisely declined to execute this intemperate order.

The health of U.S. science also depends on public policy in a variety of other ways-foreign policies that promote or limit scientific collaborations with colleagues abroad, educational investments to attract and train the next generation of scientists, new scientific institutions and facilities that define the leading-edge capabilities of science. Finally, scientists, like other citizens, do care about how society uses the knowledge their research creates. And for this reason, many thousands are happy to serve on advisory committees without financial compensation.

Despite the discomfort they might have with scientists who seem insufficiently grateful for the government's largess or who are too willing to oppose federal policies while accepting federal funding, politicians are also dependent on competent, objective, and useful science advice. In most cases, technical advice is simply a part of the efficient functioning of government agencies that deal with an extraordinarily broad range of technical issues. No agency can expect its own scientific staff to have all the skills required for every task. If nothing else, government scientists need to check their work against the critical judgment of peers outside government. Where political and ideological issues are not in question, this part of the advisory system works very well.

For example, the NRC-the operating arm of the National Academy of Sciences, National Academy of Engineering, and the Institute of Medicine- appoints an array of academic and industrial experts to assess and assure the quality of research at government laboratories such as the National Institute for Standards and Technology. Other committees advise DOE on the research strategy for realizing fusion energy and help the National Science Foundation and the National Aeronautics and Space Administration on priorities for new telescopes on earth and in space. In 2001, the NRC performed 242 studies for the executive branch and Congress. A staff of more than 1,000, working with some 5,000 volunteer experts from universities and industry, prepared these studies and served as quality control reviewers of the finished products. Most of these studies were quite technical and, from a policy perspective, largely uncontroversial.

Government policymakers, however, need the advice of professional experts from outside government for a more profound reason, touching on the basic structure of U.S. democracy. Americans will not give a self-selected elite authority to decide complex matters on their behalf. U.S. leaders are selected by a highly decentralized voting system that, in principle at least, chooses leaders from a broad spectrum of citizens. How can the public judge the performance of these leaders? What makes their actions in office seem legitimate to us, the voters, and what kinds of information do we seek in holding them accountable? In the U.S. political tradition, public officials are judged by what they do, not by who they are.

Contrast the U.S. system with that in France or Japan. In those countries elected officials make the decisive political decisions, but the senior posts in the ministries are held by highly educated career employees. The legitimacy of these officials comes not from the visibility to the public of what actions they take but rather from the prestige associated with their education in a small number of very special schools- the grandes écoles of France and the former imperial universities of Japan. In these countries and in Britain as well, political appointees fill only the very top layer of the ministries; the agencies are run by career professionals. This reflects a level of public trust of senior government officials not found in the United States, where politically appointed officials, serving at the administration's pleasure, are found four or five layers deep in many parts of government.

In France, for example, when the Chernobyl nuclear power plant accident spread radioactive material over the farms of Western Europe, the French government did not announce their tests for radioactive contamination of French crops until nearly a week had passed. Government officials explained that if there had been something the public needed to know, they would have been told. When something goes seriously wrong in the United States, the public immediately demands its leaders to explain "What did they know and when did they know it?" Although the U.S. public possesses limited technical literacy and suspects that segments of the media are guilty of bias, it still turns to the press and independent voices to judge the government's performance. It places its trust in transparency, not in political elites.

This pragmatism in U.S. politics originates with the authors of the Constitution, who sought to build a government "of and by the people," immune to restoration of monarchy. They were creating the world's first constitutional democracy. Reflecting the philosophy of the Enlightenment, the founders saw science as a model for a rational approach to public choices and thus a model for democratic politics.

Politics deals with outcomes people can experience. U.S. voters have traditionally paid relatively little attention to political ideology; the two parties have been fundamentally very similar in philosophy. The philosophical goals of the society (equity, culture, freedom, spiritual well-being) have, in the past, been most effectively expressed politically through empirical evidence-"Are you better off than you were four years ago?"-not by abstract arguments. Letting the facts speak for themselves gives government policies credibility. When the public sees government officials basing their policies on objective, professional knowledge, the public confers authority on those who govern. Appeals to other sources of authority, such as religion or inherited power, disconnect accountability from authority.

This helps political scientists explain why government leaders are more likely to work behind the scenes to shape the advice they receive than they are to shut down the advisory committees. They need the validation that support from committees of experts can bring to their policies. The public expects those policies to be grounded in evidence and reasoned argument. Most presidents, from the right and from the left, have therefore sought to maintain a credible and active system for validating their policies through expert advice from outside government. However, as noted above, when sufficiently unhappy with the advice received, they have some times disowned the advice or even abolished the panel giving the advice.

The importance of trust

Experts giving advice must also earn their legitimacy. To be sure, credentials inevitably play a much bigger role in establishing the right of scientists to claim to be experts. Accordingly, the public insists on transparency in the advisory process, just as it does in government policymaking. That transparency was enacted into law following the push for more open government in the 1970s. The Freedom of Information Act opened up most agency records to public and press inspection. The Federal Advisory Committee Act, passed in 1972, requires access by the press and the public to meetings of most advisory committees. Together with many conflict of interest laws, these acts are expressions of a political will to keep advice given to government open to the sunshine of public witness.

It follows that if either scientists or politicians so politicize their mutual engagement that they sacrifice the credibility of the scientists and the legitimacy of the government officials, the consequences to the nation's time-honored system of governance could be serious indeed. This compels both the scientific community and the government to find a way to bridge the gaps in interests, culture, and process that divide them. They must work together to develop processes that give each the value they seek from the relationship and that also protect the integrity of the relationship against temptations by either side to corrupt it. What, then, are the mechanisms through which these bridges might be built?

Perhaps the most essential structural element in the bridge between science and politics is the understanding that scientists insist on being allowed to inform policy through balanced and expert views of relevant technical facts and best judgments. Indeed, those politicians who believe sound advice will bring added political support to their policies should insist that the technical advice be appropriately organized and managed. However, the scientists must also understand that the officials being advised are not obligated to adopt policies based solely on the scientists' technical analysis. Many factors go into the soup of politics, and artful government requires careful weighing of all these factors.

Litmus tests of political allegiance should not be among these criteria for selecting scientists for advisory committees.

The scientist giving the advice does have recourse if she or he does not like the final decision. The scientist can exercise each citizen's political right to oppose the policy publicly. However, to preserve the nonpolitical nature of the advisory process, the scientist might resign from the panel before going public with a political position. The events leading up to President Nixon's abolition of OST illustrate the difficulty of trying to serve as a nonpolitical advisor while publicly expressing private positions on public issues. A member of PSAC accepted an invitation to testify before Congress about the wisdom of President Nixon's desire to build an antiballistic missile system. In testimony the scientist not only made clear that he spoke for himself and not for PSAC; he also said that his testimony did not rest on information available only to PSAC. He spoke as a knowledgeable private citizen. The press nevertheless interpreted the testimony as evidence that PSAC had given Nixon advice he did not wish to accept, and the president reacted by shutting down PSAC and OST. This happened despite the president's statement to PSAC, relayed by the science advisor, that PSAC members should feel free to testify on either side of the issues and need not resign before doing so.

The sensitivity of the relationship between government officials and independent advisory committees demands clear guidelines for operation. I propose four rules that would help ensure sound and uncorrupted science-based public decisions:

The criteria for selection of scientists to serve on advisory committees, including description of their scientific qualifications and disclosure of all other activities that might bias their judgment, should be publicly documented. Litmus tests of political allegiance should not be among these criteria. Ideological or religious criteria can be considered in making policy but they should not be represented as science.

Key policy and regulatory decisions must not be deliberately deprived of relevant, independent, and expert scientific information. The science advice derived from this information should be published, along with the charter for the study, before the final regulatory decision is made.

An effective system of protections for whistle-blowers must be established to ensure that scientists inside government agencies are able to report with impunity allegations of deliberate political interference with their work and advice.

The president should formally document the policies that are to govern the relationship between science advice and policy, both through advisory structures using scientists outside government and those using government scientists. This should include a set of procedures like those above (and more extensively documented by the NRC) and should identify the locus of responsibility for detecting transgressions of the policy and procedures for investigation and correction if appropriate.

But who is to have the responsibility to oversee adherence to a presidential policy that insists on competent, objective, balanced, and open advice, and how is the policy to be enforced? The conventional institutional answer is the president's science advisor.

The president's science advisor

Before we can talk about who can bridge the gap between science and politics, we need to describe the turbulence that flows under the bridge. Scientists who have extensive government experience understand the conflict between the scientists' demand for an advisory system giving balanced, objective, and technically expert advice and the government official's insistence on panel members who share the president's political philosophy. If the president's science advisor is to mediate this conflict, he or she must understand and bridge both interests.

But listen to William D. Carey, former assistant director of the Bureau of the Budget and executive officer of the American Association for the Advancement of Science: "If a science advisor is going to count, he must be a foot soldier marching to the program of the president, not the company chaplain." I would characterize this as an extreme, perhaps even demeaning, view of the role of science advisor to the president. I am sure John Marburger does not so characterize his job as director of OSTP in the executive office of President Bush. Indeed, to be effective, a science advisor to the president must be somewhat aloof from the demands of tactical politics. However, this independence is not to be exercised by failing to support the president's established policies. It is won by the very high level of respect accorded the advisor's scientific qualifications and prestige and by his or her acceptance of the broad framework of presidential policy.

If the president is serious about protecting the time-honored system of scientific inputs to inform policy, as President Bush has publicly affirmed, the president's own prestige, the effectiveness of his governance, and the strength of the nation's commitment to science would all benefit. But while the scientific community and the press refer to Marburger as the "president's science advisor," this is not his official title. Bush did not appoint Marburger to the traditional White House position of assistant to the president for science and technology. His formal position is director of OSTP, reporting to chief of staff Andrew Card. Had he been included in the president's White House inner circle and given the position assistant to the president accorded to D. Allan Bromley by President George H. W. Bush, perhaps many of the events catalogued by UCS might have been avoided.

It might be, however, that behind the stressful relations between many scientists and President Bush over the events documented by UCS, something much more fundamental and foreboding is happening in U.S. politics, developments that might lie beyond thescience advisor's ability to correct. In the earlier discussion it was pointed out that U.S. voters traditionally measure their leaders by objective assessments of what they achieve for the lives of the people. Political scientists have written that U.S. pragmatism traditionally outweighs the influence of ideology, religion, and elite connections. Scholars tell us that it was for that reason that government officials, over the years, encouraged the best and the brightest of science to advise the government or even to make careers in science-based public policy. But all that seems to be changing.

In the current presidential campaign much of the debate, especially from the Republican side, is, in fact, about social, religious, and patriotic values. Some of most intense conflicts between science advice and public policy have turned on objections by scientists to the primacy of ideology over science. Fourteen years ago scholars were already observing a growing preference for images that presented the appearance of pragmatic measures of achievement. We now live in an era of images and "spin." In her 1990 book The Fifth Branch: Science Advisors as Policy Makers, Sheila Jasanoff writes, "In the closing decades of the 20th century the intellectual and technical advance of science coincides with its visible decline as a force in the rhetoric of liberal-democratic politics."

The integrity of the science advisory process cannot withstand overt actions to censor or suppress unwanted advice, to mischaracterize it, or to construct it by use of political litmus tests in the selection of individuals to serve on committees. Nor can it survive threats to the job security of scientists in government when they attempt to call such political interventions to the attention of Congress or the press. Science advice must not be allowed to become politically or ideologically constructed. If we fail in the attempt to preserve the integrity of science in democratic governance, a strong source of unity in the electorate, based on common interest in the actual performance of government, will be eroded. Policymaking by ideology requires that reality be set aside; it can be maintained only by moving towards ever more authoritarian forms of governance.

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Science, Politics, and U.S. Democracy | Issues in Science and Technology

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But who is to have the responsibility to oversee adherence to a presidential policy that insists on competent, objective, balanced, and open advice, and how is the policy to be enforced? The conventional institutional answer is the president's science advisor. The president's science advisor Before we can talk about who can bridge the gap between [...]