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Artificial Intelligence, When Should We Trust It?

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How can we imagine more sustainable ways of transportation?

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How can we imagine more sustainable ways of transportation?

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How does technology help for health advance?

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How does technology help for health advance?

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How to make facial recognition more accurate?

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How to make facial recognition more accurate?

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AI is no longer the future-it's now here in our living rooms and cars and, often, our pockets. As the technology has continued to expand its role in our lives, an important question has emerged: What level of trust can-and should-we place in these AI systems?

To explore this question, we spoke to 30 AI scientists and leading thinkers. They told us that building trust in AI will require a significant effort to instill in it a sense of morality, operate in full transparency and provide education about the opportunities it will create for business and consumers. And, they say, this effort must be collaborative across scientific disciplines, industries and government.

Instilling human values in AI

As AI becomes more pervasive, so too has the concern over how we can trust that it reflects human values. An example that gets cited frequently to show how difficult this can be is the moral decision an autonomous car might have to make to avoid a collision: Suppose there's a bus coming toward a driver who has to swerve to avoid being hit and seriously injured; however, the car will hit a baby if it swerves left and an elderly person if it swerves right-what should the autonomous car do?

"Without proper care in programming AI systems, you could potentially have the bias of the programmer play a part in determining outcomes. We have to develop frameworks for thinking about these types of issues. It is a very, very complicated topic, one that we're starting to address in partnership with other technology organizations," says Arvind Krishna, Senior Vice President of Hybrid Cloud and Director of IBM Research, referring to the Partnership on AI formed by IBM and several other tech giants.

There have already been several high profile instances of machines demonstrating bias. AI technicians have experienced first-hand how this can erode trust in AI systems, and they're making some progress toward identifying and mitigating the origins of bias.

"Machines get biased because the training data they're fed may not be fully representative of what you're trying to teach them," says IBM Chief Science Officer for Cognitive Computing Guru Banavar. "And it could be not only unintentional bias due to a lack of care in picking the right training dataset, but also an intentional one caused by a malicious attacker who hacks into the training dataset that somebody's building just to make it biased."

"AI can be used for social good. But it can also be used for other types of social impact in which one man's good is another man's evil. We must remain aware of that."
- James Hendler, Director of the Institute for Data Exploration and Applications, Rensselaer Polytechnic Institute

As Gabi Zijderveld, Affectiva's head of product strategy and marketing explains, preventing bias in datasets is largely a manual effort. In her organization, which uses facial recognition to measure consumer responses to marketing materials, they select a culturally diverse set of images from more than 75 countries to train their AI system to recognize emotion in faces. While emotional expressions are largely universal, they do sometimes vary across cultures. For example, a smile that appears less pronounced in one culture might actually convey the same level of happiness as a smile in another culture. Her organization also labels all the images with their corresponding emotion by hand and tests every single AI algorithm to verify its accuracy.

To further complicate efforts to instill morality in AI systems, there is no universally accepted ethical system for AI. "It begs the question, 'whose values do we use?'" says IBM Chief Watson Scientist Grady Booch. "I think today, the AI community at large has a self-selecting bias simply because the people who are building such systems are still largely white, young and male. I think there is a recognition that we need to get beyond it, but the reality is that we haven't necessarily done so yet."

And perhaps the value system for a computer should actually be altogether different than that of humans, posits IBM Research Manager in affective computing David Konopnicki. "When we interact with people, the ethics of interaction are usually clear. For example, when you go to a store you often have a salesman that is trying to convince you to buy something by playing on your emotions. We often accept that from a social point of view-it's been happening for thousands of years. The question is, what happens when the salesman is a computer? What people find appropriate or not from a computer might be different than what people are going to accept from a human."

"What does the notion of ethics mean for a machine that does not care whether it or those around it continue to exist, that cannot feel, that cannot suffer, that does not know what fundamental rights are?"
- Vijay Saraswat, Chief Scientist for IBM Compliance Solutions

Taking it a step further, IBM Chief Scientist for Compliance Solutions Vijay Saraswat points out that even if machines get equipped with a clearly defined, universally accepted value system, their inability to truly feel consequences on an emotional level like a human could make them imperfect ethical actors.

"Artificial intelligence will be a different form of thinking-a different form of being, existing," says Saraswat. "In the ethical space, what does the notion of ethics mean for a machine that does not care whether it or those around it continue to exist, that cannot feel, that cannot suffer, that does not know what fundamental rights are? There's no inherent, inalienable notion of this kind built into the very fiber of our computational systems, so how would they then have a sense of ethical behaviors when the basics on which human morality is built are missing?"

There are a few techniques AI scientists are experimenting with to instill AI systems with ethical principles. One that shows some promise is inverse reinforcement learning. This method of training an AI system, IBM Distinguished Researcher Murray Campbell explains, involves letting the system observe how people behave in various situations and figure out what people actually value, allowing the system to make decisions consistent with our underlying ethical principles.

Creating transparency

AI thought leaders also note that transparency is key. To trust computer decisions, ethical or otherwise, people need to know how an AI system arrives at its conclusions and recommendations. Right now, deep learning does poorly in this regard, but some AI systems can serve up the passages from text documents in their knowledge bases from which they drew their conclusions. The AI experts agree, however, that this is simply not enough.

"We will get to a point, likely within the next five years, when an AI system can better explain why it's telling you to do what it's recommending," says Rachel Bellamy, IBM Research Manager for human-agent collaboration. "We need this in all areas in which AI will be used, and particularly in business. At that point, we'll gain a more significant level of trust in the technology."

AI application developers must also be transparent about what the system is doing as it interacts with us. Is it gathering information about us from various places? Is it "looking" at our faces through a web camera to read our expressions? And, the experts say, people should have the ability to turn some of these functions off whenever they like.

"A similar parallel right now is how willing people are to share their location information with an app. In some cases it has a clear benefit, while in others, they may not want to share because the benefit isn't significant enough for them," says Jay Turcot, Head Scientist and Director of Applied AI at Affectiva. "The key is transparency on how information is used and providing user control-I think that model will be a good one moving forward. From a privacy point of view, I think it will always be a tradeoff between utility and privacy and that each user should be able to make that choice for themselves."

Transparency through education

Another effective way to provide transparency is through education. Misconceptions about what AI can and can't do abound, eroding trust in the abilities they do possess. And, perhaps most significantly, a lack of clarity over which jobs AI might impact breeds an additional level of distrust in the technology. AI thought leaders universally agree that it's mission critical to educate people about where disruption might occur and to teach the skills that will be needed to perform new jobs AI will create in the future.

In most job areas, the experts contend that human input will still be required and will often provide the most valuable component. "There are certain types of advising questions we don't need to spend precious faculty time on," says Satinder Singh, Director of the University of Michigan's Artificial Intelligence Lab. "We can handle them in an automated system and reserve the faculty time for the really challenging psychological questions, for example, where somebody's having trouble with sleep or health or mental health or whatever is causing them difficulty in a university setting."

Where jobs do experience disruption, many technology veterans say history provides examples of how technology often breeds new, unimaginable jobs. "My optimism on jobs rests in history. Things incrementally improve by 1% a year, which is almost invisible except as it accumulates and is looked at retrospectively," says Kevin Kelly, co-founder of Wired and author of the best-seller The Inevitable. "In the past we have undergone huge disruptions and revolutions in livelihood, the last one being the agricultural age where many farmers lost their jobs. The jobs that replaced them were unimaginable to those farmers 150 years ago-their descendants became web designers, mortgage brokers."

"There's no silver bullet," says Kelly. "But I think it's also important to remember that this is not a technical issue. We know how to retrain people en mass. The market cannot do it alone. It needs government, too. And we should start teaching it in our schools-the essential techno-literary skills of learning how to learn, learning how to relearn and becoming a lifelong learner."

"My optimism on jobs rests in history."
- Kevin Kelly, co-founder of Wired and author of the best-seller The Inevitable

Collaborating for responsible advancement of AI

The societal benefits and implications of AI are enormous. Developing and deploying the technology in a responsible manner requires an effort of equal proportion, which means one or even a handful of organizations working toward that end is not enough. A significant collaboration within and across academia, industry and government is required to meet the challenge and ultimately build trust among consumers that their best interests are truly at heart.

With its unique combination of both extending human capabilities and often deriving its very architecture from the structure of the human brain, AI requires a multidisciplinary scientific effort to simply advance its usefulness. "We need to approach AI in a multidisciplinary way because the brain itself is a bundle of interdependent elements which support thinking and behavior that's describable on many different levels. To accelerate our understanding of human cognition, neuroscientists, linguists, psychologists, philosophers, anthropologists, deep learning experts and others need to come together," says Margaret Boden founder of the University of Sussex cognitive science department and advisor at the Leverhulme Centre for the Future of Intelligence.

"We need to approach AI in a multidisciplinary way because the brain itself is a bundle of interdependent elements."
- Margaret Boden, Cognitive Science Research Professor, University of Sussex

Affectiva's Zijderveld believes bringing AI to its most useful state will require technologists to come together to establish common standards and platforms for AI. "As a consumer I'm not going to want to have to jump through hoops to get my phone to talk to my car, right? These are systems that should all be able to talk to each other, from the enterprise applications that we use in business to our mobile devices. Yet there are no standards for interoperability. I believe a consortium of industry will have to come together to solve this, cross-verticals and cross-use cases."

Even as we advance the development of transparent, ethical AI, there's still one necessary ingredient for trust that can't be manufactured-time.

"How do we get to AI systems that we can trust? Ultimately, it's going to be through getting our AI systems to interact in the world in a shared context with humans, side-by-side as our assistants," says IBM's Saraswat. "And over time, we'll develop a sense for how an AI system will operate in different contexts. If they can operate reliably and predictably, we'll start to trust AI the way we trust humans."

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IBM interviewed 30 artificial intelligence experts to explore how we can build trust in artificial intelligence. Here's what they had to say

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We are not going to focus on every innovation that has been imagined, but we are going to take a look at the promises and the challenges of a more efficient and eco-friendly way of moving.

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We are not going to focus on every innovation that has been imagined, but we are going to take a look at the promises and the challenges of a more efficient and eco-friendly way of moving.

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Washington University School of Medicine in St. Louis

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Visit the News Hub

How big data could change health care
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Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time.

In a new Viewpoint article published Dec. 10 in the Journal of the American Medical Association (JAMA), two AI experts at Washington University School of Medicine in St. Louis discuss the best uses for AI in health care and outline some of the challenges for implementing the technology in hospitals and clinics. Philip Payne, PhD, is the Robert J. Terry Professor and director of the Institute for Informatics, and Thomas M. Maddox, MD, is a professor of medicine and director of the Health Systems Innovation Lab, launched in 2017 as a partnership between the School of Medicine and BJC HealthCare. The lab is aimed at developing innovative ways to deliver care and improve people's health.

In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients - such as their ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.

Payne and Maddox answered questions about AI, including its capabilities and limitations, and how it might change the way doctors practice.

Where are the first places we will start to see AI entering medical practice?

Maddox: One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis of cancer or heart problems, for example. There are many types of imaging tests - X-rays, CT scans, MRIs and echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality data. For AI to work well, it's best to have very complete data sets - no missing numbers, so to speak - and digital images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these images - subtle changes in breast tissue over several years of mammograms, for example. There has been some interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly trained physician would not see.

Payne: In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a clinician's attention. This is a computer trying to replicate a human being understanding that data and saying, "This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much larger and more complex sources of data, such as the entire electronic health record and perhaps even data pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.

What effect will this have on how doctors practice medicine?

Payne: We think it's important to emphasize that these tools are never going to replace clinicians. These technologies will provide assistance, helping care providers see important signals in massive amounts of data that would otherwise remain hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate.

Maddox: To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's values? What does this mean for the patient's life and for his or her family? That's never going to be an AI function. As these AI systems slowly emerge, I think we may start to see the roles of physicians changing - in my opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and councilors for patients as they try to navigate their health.

Payne: That means we need to think about new ways to train physicians and other care providers as these systems come into medical practice. We want the humans in our health-care system doing the things that humans are uniquely suited to do, such as interpreting and counseling, as Tom described. And the computers in the system doing the things that computers are uniquely suited to do, such as collecting, filtering and analyzing large amounts of complex data. And those two things are complementary.

Putting information-based tools in doctors' hands

What regulatory issues - especially related to privacy - need to be addressed for AI?

Payne: As medicine is practiced now, there are moral, ethical and privacy contracts that already exist between health-care providers and their patients. If we can find a way to fully reflect those existing contracts from a technical standpoint, we'll be in a good position. They provide guideposts.

Maddox: It's an extension of the Hippocratic oath. There is privacy already inherent in the provider and patient relationship. Privacy requires two things: The first is the mechanics of protecting data, and the second is the establishment of trust. It's incumbent on us to preserve that trust.

Payne: There's a lot of talk about the ethics of data stewardship and whether there is a need for the equivalent of a Hippocratic oath for the people charged with protecting and using patient data appropriately. There is a moral and ethical contract that involves not only protecting patient privacy but making sure that information is used responsibly and in order to make the health-care system better. There's a duty that people charged with doing so accept as part of their professions. Building systems to analyze data in health care is not the same as building systems that manage logistics when someone orders something online. The stakes are much higher, and it is important to acknowledge this difference.

Imagine AI is fully integrated into your practice. How might it change your day-to-day routine?

Maddox: I'm a cardiologist. Typically, patients I see include those who may have had a heart attack, or patients who are dealing with heart failure. Traditionally, we monitor these patients by having them come to our cardiology clinic for follow-up visits. For example, I might have a patient come and see me every six months. But this follow-up time period is basically chosen at random - there's no specific medical reason for it.

With AI, in theory, I would no longer schedule these standard follow-up appointments. Instead, I would review the integrated, AI-analyzed, data streams of my thousand-patient practice every day. The AI algorithms would integrate multiple data streams that can paint a picture of my patients' cardiac health on any given day. For example, I could see my patients' activity levels measured by their wearable devices, their medication adherence patterns from pharmacy data, their breathing and pulse rates from their home-based sensors, their weight fluctuations from their "smart" scale, their exposure to air pollution from environmental sensors, and recent ER visits from their electronic medical record. Taking all that together, the AI could identify any patients who are at high risk for cardiac problems. From a heart-attack risk point of view, there might be a patient who is a smoldering fire, so to speak, and the system prompts me and my team to reach out to that patient for an appointment as soon as possible. For the remainder of my cardiac patients who don't have any current high-risk features, then there would be no need for them to come to my clinic. We would just continue to monitor them remotely and be available for any problems.

Payne: What Tom just described is a smart health-care system - where the consumption of health care is driven by actual need. In his example, the AI sorted through a massive amount of different kinds of data and pulled out the one patient he needed to see and interact with. Some of the best ways to reduce health-care costs and improve health-care outcomes will be to eliminate the care that patients don't need.

Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if we do our jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine.

Maddox TM, Rumsfeld JS, Payne PRO. JAMA Viewpoint: Questions for AI in healthcare. JAMA. Dec. 10, 2018.

Washington University School of Medicine's 1,500 faculty physicians also are the medical staff of Barnes-Jewish and St. Louis Children's hospitals. The School of Medicine is a leader in medical research, teaching and patient care, ranking among the top 10 medical schools in the nation by U.S. News & World Report. Through its affiliations with Barnes-Jewish and St. Louis Children's hospitals, the School of Medicine is linked to BJC HealthCare.

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Artificial intelligence and the future of medicine

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Visit the News Hub How big data could change health care Getty Images Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time.

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Age verification for grocery stores' checkout and Facial recognition for advertising

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Age verification for grocery stores' checkout and Facial recognition for advertising

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We design, train and fine-tune all our own algorithms.

All algorithms run locally on the hardware - quick, no internet required (ICU Pro & ICU Lite)

We use our own algorithms to recognise faces and verify age. We do not use publicly available databases for training or tuning like many other systems, favouring our own extensive datasets especially chosen to reduce gender and skin tone bias. Our algorithms are not publicly available, which makes our system, and customer data more secure.

In the case of age estimation for example the model is trained using millions of images of faces with known ages. The algorithm analyses the features of the person and associates that with the known age. In doing so, the algorithm essentially learns what feature a subject typically has for a certain age. So, when a new image is presented, the algorithm analyses the features, and from what it has learnt, estimates an age based on what age it has associated with those features.

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Biometric Facial Recognition and Age Verification

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Innovative Technology's biometric range offers anonymous age estimation, to assist with the sale of age restricted goods and biometric access control with cutting edge facial recognition. The technology uses local processing to give a fast response with a high level of assurance.

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Breast cancer is an increasing problem in low and middle-income countries, but screening programmes for early detection are rare.

A company in India has developed a cheaper, non-invasive test that uses thermal imaging and AI.

Although considered less reliable than mammography, it is hoped the test might help spot some early cancers in people who might not otherwise have access to mammography screenings.

The US FDA says mammography is the best method of screening breast cancer.

For more positive stories listen to the People Fixing the World podcast.
Reporter: Chhavi Sachdev, c amera: Rajesh Sharma, producer: Richard Kenny

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Using artificial intelligence to spot breast cancer

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Breast cancer is an increasing problem in low and middle-income countries, but screening programmes for early detection are rare. A company in India has developed a cheaper, non-invasive test that uses thermal imaging and AI. Although considered less reliable than mammography, it is hoped the test might help spot some early cancers in people who might not otherwise have access to mammography screenings.

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Svilen Rangelov sports an impressive beard. It's eight years' worth of growth he says.

The beard dates back to when he and his younger brother, an aerospace engineer by training, formed Dronamics as Europe's answer to the emerging market for cargo drones.

He agreed with his brother Konstantin that they would only shave their beards after the first flight of the drone they've been building in their native Bulgaria.

At the time he established Dronamics big tech giants like Amazon were experimenting with drone deliveries to domestic addresses. But Mr Rangelov never believed in the concept of personal goods delivered by the drone.

The practical difficulties of flying a drone right up to someone's front door were obvious to Mr Rangelov. "We couldn't buy into the concept of small drones. We took a different approach."

This take on drone delivery will bear fruit when the prototype cargo aircraft takes to the air.

Looking very much like a conventional light aircraft but without a pilot's cabin, the drone combines "cell phone economics" in terms of cheap electronics, with the ability to land on short runways, says Mr Rangelov.

It will be known as the Black Swan.

"Here in Bulgaria air cargo means one large aircraft offloading goods onto a truck which then goes to a sorting centre where the delivery is broken down for the next stage of its journey to individual sites."

He thinks taking a smaller load to a short airstrip closer to the final recipient will cut costs and take trucks off the road.

"There are 3,000 airstrips across Europe, that's a lot of locations."

Black Swan embodies a combination of lightweight composite materials (his brother's speciality) and a standard piston engine that sips petrol while the drone cruises on long and fuel efficient wings.

This whole package will fly at 20,000ft altitude,below the mass of passenger air traffic. Dronamics sees this height band as unused airspace and is also testing out a new, synthetic aviation fuel which it claims will allow carbon-neutral flights.

The 350kg (770lb) cargo load of the Black Swan equals that of a small courier van. "We're connecting city to city, not door to door."

Dronamics plans to operate Black Swans like an airline, "Europe's first drone cargo airline." It will charge by weight or charter, cutting out the cost and time taken by vehicles that criss-cross Europe to deliver essential goods and parts.

German logistics giant Hellmann is poised to begin using these drones. Jan Kleine-Lasthues is in charge of this initiative and he has spent a long career in airfreight.

Mr Kleine-Lasthues doesn't see conventional air freight facing competition from these new designs, but thinks the drones will allow Hellmann to fly goods that previously travelled by road.

Connecting Greek islands by cargo drone is one of Hellmann's immediate ambitions, says Mr Kleine-Lasthues.

"The drones will be more frequent than ferries and we can use them to break down deliveries into several packages, so we can increase the frequency of deliveries. They represent a big change, they offer speed and flexibility."

Dronamics claims a 2,500km (1,500 miles) range for its aircraft, putting the whole of Western Europe within range of any EU-based cargo hub.

While smaller versions of the drone are already flying in Bulgaria, a full-scale prototype should be airborne in early 2023.

Dronamics says the European aerospace regulator has been kept apprised of its planned operations and given it a limited licence to operate. Hellmann is talking about beginning to fly them during 2023.

Mr Kleine-Lasthues shares the opinion that earlier drone delivery models were a dead end. "I never believed in the idea of parcel drones. That's why we're working with Dronamics, it's not an Amazon delivery type idea."

Cargo drones have attracted the attention of Bristow, a US group that operates helicopters around the globe. Bristow has signalled its intent to buy up to 100 cargo drones from a Californian company, Elroy Air.

While the current of crop of passenger-carrying Electric Vertical Take-Off (Evtol) designs features all-electric power, the Elroy Air cargo drones will run on a hybrid electric engine, a small turbine that generates electrical power and runs off aviation fuel.

The hybrid design means the drone can refuel at existing facilities rather than relying on docking stations for electricity. And it burns less than a third of the fuel a helicopter uses.

"Pure electric power means you're constrained by where you put the charging base" says David Stepanek, a former US Marine Corps helicopter technician who is now a Bristow executive studying cargo droneoperations.

Bristow is looking at using the Elroy drones to back up its operations in locations such as West Africa, where the offshore oil industry needs to shift equipment and Bristow wants to reduce the costs of using helicopters and fixed-wing aircraft.

Elroy Air has been working on a large multi-engined, vertical take-off drone that can heave a 225lb (100kg) load up to 480km (300 miles).

Elroy Air's Kofi Asante researched autonomous trucks at Uber's freight arm. He points out that the idea of a cargo pod attached and then de-coupled from the chassis of a an autonomous truck also works for a cargo drone.

He describes relations with US regulator the Federal Aviation Authority (FAA) as "very positive" with a test flight for a full-sized drone planned by the end of 2022.

At over 8m (26ft) in width the drone, named Chapparal, is large by uncrewed civil drone standards. But that size is the point says Mr Asante.

"It can carry a hundred times the payload of small UAV (unmanned aerial vehicle), it's comparable to a small plane in terms of load but operates at a fraction of the cost of a helicopter."

You may not be ordering a flying drone delivery to your home address anytime soon. But it looks as if the death of one drone dream has opened the way for another more practical concept to thrive.

And this should usher in clean-shaven leadership at Dronamics.

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The cargo hauling aircraft with no pilots on board

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Svilen Rangelov sports an impressive beard. It's eight years' worth of growth he says. The beard dates back to when he and his younger brother, an aerospace engineer by training, formed Dronamics as Europe's answer to the emerging market for cargo drones.

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You can start watching at 3'20 because the beginning of the video is not very interesting for this topic.

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The future of transportation | Ryan Janzen | TEDxToronto

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Here is a look at what does health could look like in a few years. 

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Here is a look at what does health could look like in a few years. 

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Politicians may be accused of being robotic on occasions - but the real robots are creeping into Parliament.

In recent years, robots have given evidence to select committees and one MP has even used a chatbot to write one of his speeches in the House of Commons.

So just to have a bit of festive fun - or perhaps give a terrifying glimpse into our future under artificial intelligence overlords - we asked the chatbot ChatGPT to have a go at taking Prime Minister's Questions.

ChatGPT, created by artificial intelligence research company OpenAI, aims to simulate human conversation based on learning from human writing and trainers.

The chatbot is still being developed and its creators acknowledge its limitations including using "plausible-sounding but incorrect or nonsensical answers" and being "excessively verbose".

But could it imagine being a politician? Here is what we learnt when we asked it to try.

Firstly, chatbot politicians are polite.

During his time as prime minister, Boris Johnson took part in some pretty angry exchanges with Labour leader Sir Keir Starmer.

Mr Johnson called Sir Keir a "pointless human bollard" and "Captain Crash-A-Roony Snooze Fest". Sir Keir said Mr Johnson was "totally deluded" and "totally failing".

However, when we asked ChatGPT to write an exchange between the two men, their relationship was somewhat different.

It began: "Good morning, Keir. How are you today?"

"Good morning, Boris. I'm doing well, thank you. How are you?" came the reply.

"I'm doing well, thank you. So, Keir, I wanted to talk to you about the government's plans for Brexit."

"Yes, I'd be happy to discuss that with you. What specifically do you want to know?"

"Well, we've been working on a new trade deal with the European Union, and I wanted to get your thoughts on it."

The exchange continues in this vein, with both men agreeing to work together in the interests of the country "regardless of political differences".

"Thank you, Boris. Have a good day," robot Sir Keir concludes.

For anyone who remembers the Brexit debates in Parliament, or the PMQs from earlier this year, this display of mutual goodwill will feel very unfamiliar.

When we asked the chatbot to take it up a level and write a "fiery exchange" between the two politicians, we were swiftly admonished.

"I'm sorry," said ChatGPT, "but I am not programmed to create content that is inflammatory."

Currently, the chatbot's knowledge only goes up to 2021, meaning we were unfortunately not able to simulate a conversation between Sir Keir and Mr Johnson's successor Rishi Sunak.

Moving away from Prime Minister's Questions, we asked the computer to have a go at writing an MP's maiden speech - the first speech they give in the House of Commons.

The result was pretty good.

'Churchillian'

The fake MP begins by praising Parliament as "an esteemed body". They then express humility at the trust placed in them by their constituents and pledge to "serve to the best of my ability".

Their local constituency's community is praised as "diverse and vibrant".

Robot MP says they will always put their constituent's interests first and promise to work "across party lines to find solutions to challenges we face".

Add in a few references to the constituency's local football club, and this is pretty similar to the average MP's first speech to Parliament.

And at least one parliamentarian, has already had a go at using a chatbot to write their speech.

Conservative MP for Bosworth Luke Evans asked the tool to write a "Churchillian speech on the state of the United Kingdom over the last 12 months" and read out the 324-word script to MPs.

The speech praises the government for "its success in managing the economy" and "implementing its ambitious plan for Brexit".

It finishes with a quote from the wartime leader Winston Churchill: "Success is not final, failure is not fatal: it is the courage to continue that counts", before adding: "I believe that the UK has shown that courage over the past 12 months."

ChatGPT is not yet allowed to "express political opinions or engage in political activism".

So we are unlikely to see it pop up on ballot papers in the foreseeable future.

And that means the likes of Rishi Sunak and Keir Starmer are safe in their jobs...for now.

Let's give the last word to the chatbot.

Asked if a bot could one day be prime minister, it said: "Overall, while it is theoretically possible for a robot to be the prime minister of a country, it would be a challenging task and would likely require significant advancements in artificial intelligence and decision-making capabilities."

Which sounds exactly like the kind of answer a quietly-ambitious politician would give.

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Could a chatbot answer Prime Minister's Questions?

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Politicians may be accused of being robotic on occasions - but the real robots are creeping into Parliament. In recent years, robots have given evidence to select committees and one MP has even used a chatbot to write one of his speeches in the House of Commons.

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This article deals with twin representation, like in the video just before.

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This article deals with twin representation, like in the video just before.

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Away from novelties like a smart bird feeder and camera-equipped oven, one corner of the world's biggest technology event is inviting attendees to meet their virtual twin.

Set up in the Las Vegas Convention Center at the Consumer Electronics Show (CES), the ambitious "living heart" and "living brain" initiatives are the work of French software company Dassault Systemes.

Both are attempts to use the digital world to improve the physical one.

Much as an engineer would design an aeroplane or car on a computer in 3D before the physical work begins, the concept of a "digital twin" aims to predict how a person might perform in real-world scenarios.

In the case of Dassault, the goal is to apply the technology to health care.

"My daughter was born with a very rare clinical heart defect," senior director Dr Steve Levine told Sky News.

"I watched, as most parents would, kind of helplessly, some of the best doctors really guessing what might work.

"It dawned on me that they really didn't understand the function - and didn't have tools to address things they had never seen before.

"If we can give an engineer a fully functioning jet to try out, why can't we give a doctor a fully functioning heart?"

Visitors to the firm's CES booth can strap on an augmented reality headset to hold, rotate, and squeeze 3D-printed replicas of a heart and brain.
More from CES 2023:
Is this the future of the electric car?
PlayStation unveils accessibility controller
The most eye-catching gadgets at the show

As they do it, their actions are mirrored on a digital recreation of themselves in real time, displayed on a connected touchscreen which measures their heart rate and projects it back on to the virtual clone.

The idea is to showcase what goes into the creation of a virtual twin, and how the results are being used to help doctors and surgeons in the field.

Speaking to Ian King Live, Dr Levine explained: "The way an engineer can predict how a car might crash, fix the weaknesses before it actually gets into production, we can now start to do that in health care.

"We can begin to predict how treatment will affect and be used on a real body before it is tried.

"With a virtual twin, you could perform a surgery beforehand, optimise the surgery, so when it's time to go into the operating room, you can actually know you've got the best surgery and execute it."

Researchers are already utilising the "living heart" to test potential treatments before they are carried out.

The technology is being used around the world, including at London's Great Ormond Street Hospital.

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CES 2023: How 'virtual twins' are helping doctors perform surgery ahead of time

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Away from novelties like a smart bird feeder and camera-equipped oven, one corner of the world's biggest technology event is inviting attendees to meet their virtual twin. Set up in the Las Vegas Convention Center at the Consumer Electronics Show (CES), the ambitious "living heart" and "living brain" initiatives are the work of French software company Dassault Systemes.

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Back in November, researchers hailed the dawn of a new era of Alzheimer's therapies. After decades of failure, a clinical trial finally confirmed that a drug, lecanemab, was able to slow cognitive decline in patients with early stages of the disease. The result may have been modest - a reduction in the decline in patients' overall mental skills by 27% over 18 months - but it could not be more significant in the journey towards better understanding and treating the disease.

Ian Sample speaks to Prof Nick Fox about the clinical trial results, if this could be the first of many new Alzheimer's therapies, and whether we could one day see a cure.

How to listen to podcasts: everything you need to know

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Are we finally nearing a treatment for Alzheimer's?

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Back in November, researchers hailed the dawn of a new era of Alzheimer's therapies. After decades of failure, a clinical trial finally confirmed that a drug, lecanemab, was able to slow cognitive decline in patients with early stages of the disease.

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We have to be careful because it is not a perfect technology yet, especially when it comes to skin tones...

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We have to be careful because it is not a perfect technology yet, especially when it comes to skin tones...

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NEW ORLEANS - Louisiana authorities' use of facial recognition technology led to the mistaken-identity arrest of a Georgia man on a fugitive warrant, an attorney said in a case that renews attention to racial disparities in the use of the digital tool.

Randall Reid, 28, was jailed in late November in DeKalb County, Georgia, The Times-Picayune/The New Orleans Advocate reported.

His attorney, Tommy Calogero, said authorities erroneously linked Reid to purse thefts in Jefferson Parish and Baton Rouge. Reid, arrested on Nov. 25, was released Dec. 1.

Reid is Black, and his arrest brings new attention to the use of a technology critics say results in a higher rate of misidentification of people of color than of white people.

"They told me I had a warrant out of Jefferson Parish. I said, 'What is Jefferson Parish?'" Reid said. "I have never been to Louisiana a day in my life. Then they told me it was for theft. So not only have I not been to Louisiana, I also don't steal."

Calogero said Reid was falsely linked to the June theft of luxury purses from a consignment shop in Metairie, a New Orleans suburb in Jefferson Parish.

A Baton Rouge Police Department detective then adopted the Jefferson Parish Sheriff's Office's identification of Reid to secure an arrest warrant alleging he was among three men involved in another luxury purse theft the same week, court records show, according to the newspaper.

Differences, such as a mole on Reid's face, prompted the Jefferson sheriff to rescind the warrant, said Calogero, who estimated a 40-pound difference between Reid and the purse thief in surveillance footage.

Jefferson Sheriff Joe Lopinto's office did not respond to several requests for information from The Times-Picayune/The New Orleans Advocate on Reid's arrest and release, the agency's use of facial recognition or any safeguards around it.

The agency did not immediately respond to a request, emailed Monday by The Associated Press, for comment on the story and information on the use of the technology.

Reid's case brings renewed attention to the use of facial recognition tools in Louisiana and elsewhere.

Facial recognition systems have faced criticism because of their mass surveillance capabilities, which raise privacy concerns, and because some studies have shown that the technology is far more likely to misidentify Black and other people of color than white people, which has resulted in mistaken arrests.

Police in New Orleans say facial recognition can be used only to generate leads and that officers must get approval from department officials before lodging a request through the Louisiana State Analytic and Fusion Exchange in Baton Rouge. Under the latest city rules, all possible matches must undergo a peer review by other facial recognition investigators.

Legislation to restrict the use of facial recognition statewide died in a 2021 legislative session.

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Facial recognition tool led to mistaken arrest, lawyer says

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Facial recognition systems have faced criticism because of their mass surveillance capabilities and because some studies have shown that the technology is far more likely to misidentify Black and other people of color than white people.

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This video is a very good compilation by Cambridge University of future advances they are thinking of, such as the nanotechnology.

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This video is a very good compilation by Cambridge University of future advances they are thinking of, such as the nanotechnology.

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This video is a great explanation of how do people help each other to convert themselves to more sustainable vehicles.

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Developing the Future of Transportation | National Geographic

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This article is not about health progress but it deals with the correlation between the future and healthcare jobs. Here is a summarise of it because it is very complete and contains a lot of numbers.

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This article is not about health progress but it deals with the correlation between the future and healthcare jobs. Here is a summarise of it because it is very complete and contains a lot of numbers.

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Data is the lifeblood of health care. That data takes many forms: It includes the number of immunizations performed in each state; how many patients in a large medical practice have elevated blood glucose readings; and how many hospital inpatients have been billed under each International Classification of Disease (ICD) code. Without this kind of data, the health care industry could not function. But this large amount of data would be impossible to manage without technology and the professionals who understand how to translate it into actionable strategies to improve health outcomes.

Most administrators and clinicians lack the expertise to effectively collect, store and interpret this data, which explains why career opportunities for health informatics professionals have never been more promising.

Why Is Health Informatics Expanding So Rapidly?

To understand why we need health informatics professionals - particularly individuals capable of managing teams of those professionals - we also need to understand what this field actually encompasses.

According to the National Library of Medicine, health care informatics is the interdisciplinary study of the design, development, adoption and application of IT-based innovations in health care services, delivery, management and planning. That definition covers a wide range of professional responsibilities and employment paths. Roles in the health informatics field include:

These and many other positions are needed to help develop new mobile medical apps, protect electronic records systems from data breaches, analyze patient satisfaction surveys to improve quality of care, manage hardware and software updates in medical practices, and create statewide databases to conduct disease surveillance. They will play a crucial role in improving health care delivery by utilizing information to make sound decisions.

Health informatics has captured the attention of clinical, administrative and public health leaders around the nation as they realize its potential to solve problems that have vexed these fields for decades. But these are not the only interested groups: The broader field of health IT has also generated the attention of national policymakers and decision-makers across the political spectrum. That rare convergence of interests has resulted in several well-funded federal initiatives that have turned information technology - and health informatics in particular - into one of the major pillars of the nation's identity.

A closer look at legislation illustrates the emerging role of IT in health care. The American Reinvestment and Recovery Act (ARRA) of 2009 laid the groundwork for a program designed to equip hospitals and medical practices around the country with electronic health record systems. Called the Meaningful Use program, it has provided financial incentives to health care organizations to install these computerized systems. More specifically, the Centers for Medicare and Medicaid Services is making $27 billion available to medical practices and hospitals with the hope that all eligible practitioners will take advantage of the funding to improve access to patient data. This has resulted in an explosion of electronic health records (EHR) companies to meet the need and has generated countless jobs for software engineers, analysts and related IT positions.

Even before ARRA came into existence, the federal government realized the value of computer technology, as evidenced by the creation of a division within the Department of Health and Human Services to help develop a national health IT infrastructure. In 2004, the first national health information coordinator was appointed to oversee this new national initiative (the role, previously held by Dr. Karen DeSalvo, is now occupied by Dr. B Vindell Washington). In 2010, the Affordable Care Act was also enacted, which further enhanced the role of informatics in the practice of medicine.

All of this legislation created a new surge of activity in health informatics. By 2010, the U.S. Bureau of Labor Statistics had estimated that there would be a shortage of more than 50,000 IT workers over the next five years. The demand for IT professionals - and for health care professionals in general - has not slowed down yet. A recent report on the top paying health care careers concluded that "health care is one of the fastest growing careers in the United States. According to the Bureau of Labor Statistics (BLS), jobs in health care are expected to grow at an astonishing rate of 23 percent job growth over the next decade, with an estimated 974,000 new jobs expected."And the Bureau of Labor Statistics says that the median pay for a computer and information systems manager in 2015 was $131,600. A separate survey published by the Healthcare Information and Management Services Society (HIMSS) suggests that the average salary in health IT is $111,387, with a median of $90,000.

Meeting the Challenge Requires Training and Passion

With these opportunities in mind, college students and health professionals working in other specialties are no doubt wondering what kind of education, skill sets and experience will be needed to take advantage of the shifting health care scene.

Hands-on experience in generic information technology can give job candidates an advantage when looking for a position in health informatics, but many health care decision-makers are interested in recruiting people who understand the unique problems in medicine and nursing. Many also prefer someone with a clinical background who already knows the language of medicine.

Educational training is also important, with master's-prepared job seekers having an advantage over those with a bachelor's. A study from the American Health Information Management Association (AHIMA), for example, found that a master's degree in health care informatics will generate $20,000 more a year in salary than a Bachelor of Science. Equally important in the job search are cognitive and social skills. An analytic mindset and a familiarity with statistics and medical research methodology have merit. Similarly, leadership skills coupled with a willingness to passionately pursue technological solutions to clinical problems will also get recruiters' attention.

There are, no doubt, many challenges ahead in health care. The population is getting older, the cost of medical care is outpacing the incomes of many Americans, the science that underpins patient care is increasingly complex, and the accumulation of biomedical information is growing exponentially. But for those willing to face these challenges, opportunities abound. To help meet the immense need for professionals who possess this critical array of skills, the Milken Institute School of Public Health at the George Washington University has developed HealthInformatics@GW, the online Master of Science in Management of Health Informatics and Analytics program. HealthInformatics@GW enables students to gain knowledge in both health care IT and health care management so that they can lead innovative teams capable of improving the future of public health and health care.
References 1. The Healthcare Information and Management Systems Society (HIMSS). Health informatics defined. Jan. 7, 2014. 2. The Office of the National Coordinator for Health Information Technology. EHR Incentives & Certification. Apr. 4, 2014. 3. McGee M. The Workforce Challenge. 12/9/2010. 4. Kemppainen, S. 50 top paying healthcare careers. Best Medical Degrees. March 14, 2016. 5. S. Department of Labor Bureau of Labor Statistics. Computer and information systems managers. 6. HIMSS 2015 Compensation Survey. Citation for this content: HealthInformatics@GW is the online Master of Science (M.S.) in Management of Health Informatics and Analytics program from the Milken Institute School of Public Health at the George Washington University

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What Does the Future Hold for Health Informatics?

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Data is the lifeblood of health care. That data takes many forms: It includes the number of immunizations performed in each state; how many patients in a large medical practice have elevated blood glucose readings; and how many hospital inpatients have been billed under each International Classification of Disease (ICD) code.

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Since its launch in November last year, ChatGPT has become an extraordinary hit. Essentially a souped-up chatbot, the AI program can churn out answers to the biggest and smallest questions in life, and draw up college essays, fictional stories, haikus, and even job application letters. It does this by drawing on what it has gleaned from a staggering amount of text on the internet, with careful guidance from human experts. Ask ChatGPT a question, as millions have in recent weeks, and it will do its best to respond - unless it knows it cannot. The answers are confident and fluently written, even if they are sometimes spectacularly wrong.

The program is the latest to emerge from OpenAI, a research laboratory in California, and is based on an earlier AI from the outfit, called GPT-3. Known in the field as a large language model or LLM, the AI is fed hundreds of billions of words in the form of books, conversations and web articles, from which it builds a model, based on statistical probability, of the words and sentences that tend to follow whatever text came before. It is a bit like predictive text on a mobile phone, but scaled up massively, allowing it to produce entire responses instead of single words.

The significant step forward with ChatGPT lies in the extra training it received. The initial language model was fine-tuned by feeding it a vast number of questions and answers provided by human AI trainers. These were then incorporated into its dataset. Next, the program was asked to produce several different responses to a wide variety questions, which human experts then ranked from best to worst. This human-guided fine-tuning means ChatGPT is often highly impressive at working out what information a question is really after, gathering the right information, and framing a response in a natural manner.

The result, according to Elon Musk, is "scary good", as many early users - including college students who see it as a saviour for late assignments - will attest. It is also harder to corrupt than earlier chatbots. Unlike older chatbots, ChatGPT has been designed to refuse inappropriate questions and to avoid making stuff up by churning out responses on issues it has not been trained on. For example, ChatGPT knows nothing in the world post-2021 as its data has not been updated since then. It has other, more fundamental limitations, too. ChatGPT has no handle on the truth, so even when answers are fluent and plausible, there is no guarantee they are correct.

Prof Michael Wooldridge, director of foundational AI research at the Alan Turing Institute in London, says: "If I write a text message to my wife that starts: 'I'm going to be ...' it might suggest the next words 'in the pub' or 'late', because it's looked at all the messages I've sent to my wife and learned that these are the most likely ways I'll complete that sentence. ChatGPT does exactly the same thing on a massively large scale.

"These are the first systems that I can genuinely get excited about. It would take 1,000 human lifetimes to read the amount of text the system was trained on and hidden away in all of that text is an awful lot of knowledge about the world."

As OpenAI notes: "ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers" and "will sometimes respond to harmful instructions or exhibit biased behaviour." It can also give long-winded replies, a problem its developers put down to trainers "preferring long answers that look more comprehensive".

"One of the biggest problems with ChatGPT is that it comes back, very confidently, with falsities," says Wooldridge. "It doesn't know what's true or false. It doesn't know about the world. You should absolutely not trust it. You need to check what it says.

"We are nowhere near the Hollywood dream of AI. It cannot tie a pair of shoelaces or ride a bicycle. If you ask it for a recipe for an omelette, it'll probably do a good job, but that doesn't mean it knows what an omelette is." It is very much a work in progress, but a transformative one nonetheless.

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ChatGPT: what can the extraordinary artificial intelligence chatbot do?

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Since its launch in November last year, ChatGPT has become an extraordinary hit. Essentially a souped-up chatbot, the AI program can churn out answers to the biggest and smallest questions in life, and draw up college essays, fictional stories, haikus, and even job application letters.

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More than 3,000 swimmers were rescued off the UK coast by Royal National Lifeboat Institution (RNLI) lifeguards in 2021 - but there were also more than 100 accidental deaths.

So could there be a way to reach those who need help more quickly?

BBC Click's LJ Rich reports.

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Drone trial to help sea swimmers in trouble

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More than 3,000 swimmers were rescued off the UK coast by Royal National Lifeboat Institution (RNLI) lifeguards in 2021 - but there were also more than 100 accidental deaths. So could there be a way to reach those who need help more quickly? BBC Click's LJ Rich reports.

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In this video, it is interesting to see how does the drone help to improve the efficiency of rescues.

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In this video, it is interesting to see how does the drone help to improve the efficiency of rescues.

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DJI - M200 Series – Search and Rescue in Extreme Environments

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Robots can also be a great way to decrease the danger of being a firefighter.

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Robots can also be a great way to decrease the danger of being a firefighter.

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LAFD's New Firefighting Robot Rolls Into Action Early At Downtown LA Building Fire

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Make sure that you take a look at pages 9-12, 26 and 35;37.

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Make sure that you take a look at pages 9-12, 26 and 35;37.

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Artificial Intelligence helps taking decisions

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The future of transportation predicted by analyzing current trends

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This is a funny video about machine learning taking place at home.

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Lighthouse AI Smart Security Home Camera

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In this Padlet, you are going to discover four departments of innovation. The last section is more equivocal.

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In this Padlet, you are going to discover four departments of innovation. The last section is more equivocal.