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Science fiction writer Isaac Asimov writes The Three Laws of Robotics, which was a moral code for robots:
1. A robot may not harm a human being.
2. A robot must obey orders given by human beings, except when those orders are to harm a human being.
3. A robot must protect its existence, as long as that doesn't conflict with laws 1 and 2.

Many of Asimov's predictions about the future came surprisingly true!

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Back in 1983, science fiction writer Isaac Asimov was asked to predict how the world would look in 2019.

His thoughts, written originally for the Toronto Star newspaper, can now be compared against reality.

Many have proved surprisingly accurate.

He foresaw the rise of computers, saying the complexity of society would make them "impossible to do without", disrupting work and penetrating the home.

"To think that computers would take over the world was remarkably insightful at that time," thinks Calum Chase, who writes both fiction and non-fiction books on the subject of artificial intelligence.

"Most bosses did not use computers in the 80s. It was their secretaries who had them and they would print out emails for the bosses to read. The internet was around but not many people knew about it."

Asimov also predicted that robotics would revolutionise the way we work, with automation stealing clerical and factory jobs, forcing people to reconsider new careers or even living "a life rich in leisure".

In the world of education, he predicted that children would no longer need teachers, other than to "inspire curiosity", learning everything they needed to know from computers at home.

That has not come true, with many schools relying on teaching methods that have been used for many years. It will take a few more decades for Asimov's vision to become reality, thinks Mr Chase.

"In 30 years time machines will know what each student knows and what he or she needs to learn next. There is no way that humans can equal that educational power," he said.

Moonshot?

Where Asimov was less accurate were his predictions about humankind's relationship with space. He foresaw that by 2019 humans would have mining factories and a solar power station on the Moon, with strides towards building the first space settlement well under way.

The International Space Station is indeed a permanent structure circling the Earth, but the Moon has not been colonised.

The reasons for this are political rather than technological, thinks Mr Chase.

"The space race fell off a cliff when the Soviet Union collapsed. That took the pressure off America which had previously felt they had to beat the Soviets for political and prestige reasons. It became impossible to get the budgets through Congress."

In 2017, the White House announced plans to go back to the Moon and build permanent structures there for exploration and experimentation.

Space entrepreneur Elon Musk hopes to offer the first private passenger flight around the Moon in 2023.

Asimov correctly predicted that over-population and pollution would increase, although he hoped - rather optimistically - that "by 2019 advances in technology will place in our hands the tools that will help accelerate the process whereby the deterioration of the environment will be reversed".

Next 30 years?

"His predictions are absolutely fascinating," said Mr Chase.

"The things he got wrong are interesting but there is a lot that he got right. He was a genius."

And it proves that the art of future-gazing - notoriously difficult at the best of times - can be useful.

"His article shows some of the broad outlines of the future, even if the detail is wrong."

As to what the next 30 years may hold, Mr Chase believes it will be a time of dramatic change.

"I am not sure that anyone has grasped just how big the changes that are coming in the next 30 years are," he told the BBC.

One thing that Asimov did not really predict was the rise of artificial intelligence, which Mr Chase believes will be a key technology for the next few decades.

"In the next 30 years, the global economy will completely reshape," said Mr Chase.

"There will be no professional drivers, no call centres, retail will have changed and we will have to find new things to do. If we can find a way to make it economically possible, we can lead the life of leisure that Asimov talked about."

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Asimov's 2019 predictions - fiction or fact?

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Back in 1983, science fiction writer Isaac Asimov was asked to predict how the world would look in 2019. His thoughts, written originally for the Toronto Star newspaper, can now be compared against reality. Many have proved surprisingly accurate.

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Walter Pitts and Warren McCulloch come up with the plan to use 'neural networks' in machines: networks that mimic that human brain. This was the start of neural networks and deep learning - concepts that are so important in AI.

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Edmund Berkeley writes a book called Giant Brains, or Machines That Think. This shows that people were already thinking about AI at this point, even though technology was still at the point that the world didn't even have pocket calculators yet.

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Dr. Grey Walter builds the first autonomous robot, calling it a mechanical tortoise

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Alan Turing developed his famous test for AI: Can a computer talk like a human so that a human judge won't know they are talking to a human?

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The Turing test: Can a computer pass for a human? - Alex Gendler

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Arthur Samuel's checkers-playing computer is demonstrated to the public. In 1962, it beats a master checkers player. This was major news in those years!

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The IBM® 700 series, IBM’s first commercially available scientific computer was also the first in which programs were stored in internal, addressable, electronic memory. It led IBM’s transition from punched card machines to electronic computers.

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The term artificial intelligence is born, coined by John McCarthy, a computer scientist at Stanford and the father of artificial intelligence.

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Knowing John McCarthy: The Father of Artificial Intelligence

AI has become so ingrained in our everyday lives that it's difficult to comprehend life without it

It is undeniable that the technology industry has seen a wide variety of innovations over the years. The use of artificial intelligence at any level has proved to be fantastic. It automated a significant number of workers, reducing human effort and has led everyone to believe that there is even more to come.

As per report of Artificial Solutions, "Recent results from a large survey of machine learning researchers predict AI will outperform humans in many activities in the next ten years, such as translating languages (by 2024) all the way to working as a surgeon (by 2053). Researchers also believe there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years."

Nearly every aspect of our lives is being affected by artificial intelligence machines in order to boost profitability and enhance our human capabilities. AI has become so ingrained in our everyday lives that it's difficult to comprehend life without it.

As a result, we will be eternally grateful to those who were the driving force behind this incredible technology and who have contributed to making computer science even more human-like and efficient.

What is the root of the word "Artificial Intelligence"?

After playing a significant role in defining the area devoted to the creation of intelligent machines, John McCarthy, an American computer scientist pioneer and inventor, was called the "Father of Artificial Intelligence." In his 1955 proposal for the 1956 Dartmouth Conference, the first artificial intelligence conference, the cognitive scientist coined the term. The intention was to see if there was a way to create a machine that could think abstractly, solve problems, and develop itself like a human. "Every aspect of learning or any other feature of intelligence can, in principle, be described so precisely that a machine can be made to simulate it," he claimed.

Major AI Accomplishments by John McCarthy

Programming languages, the Internet, the web, and robots are just a few of the world's technological innovations that John paved the way for. He coined the term "Artificial Intelligence," invented the first programming language for symbolic computation, LISP (which is still used as a preferred language in the field of AI), and invented and established time-sharing. Human-level AI and commonsense reasoning were two of his major contributions.

According to Britannica, "McCarthy received (1951) a doctorate in mathematics from Princeton University, where he briefly taught. He also held professorships at Dartmouth College (1955-58), the Massachusetts Institute of Technology (1958-62), and Stanford University (1953-55 and 1962-2000)."

His efforts in the field of artificial intelligence have been immaculate throughout his career. McCarthy's contributions were widely recognized and he received numerous awards. He has won a number of prestigious awards, including:

In 1971, he received the Turing Award from the Association for Computing Machinery.

In 1988, the Kyoto Prize was awarded.

In 1990, he was awarded the National Medal of Science in Statistical, Computational Sciences, and Mathematics by the United States of America.

In 2003, the Franklin Institute awarded him the Benjamin Franklin Medal in Cognitive Science and Computers.

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Knowing John McCarthy: The Father of Artificial Intelligence

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Knowing John McCarthy: The Father of Artificial Intelligence It is undeniable that the technology industry has seen a wide variety of innovations over the years. The use of artificial intelligence at any level has proved to be fantastic. It automated a significant number of workers, reducing human effort and has led everyone to believe that there is even more to come.

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Unimate, the first robot for use in making stuff.

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ELIZA becomes the first chatbot

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Development of Shakey the Robot started - the first robot for general use. It could move around very, very slowly. Some say it sometimes stopped for an hour to think about its next move! Its algorithm is even used by the Mars Rovers.

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Shakey the Robot:  The First Robot to Embody Artificial Intelligence

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Rodney Brooks, a professor at MIT, cofounds iRobot and
argues that AI development needs to be achieved using neural networks. Up until this point, this opinion wasn't widely supported. Rodney Brooks had a massive impact on the development of the AI robots you see today.

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Brooks has spent his life creating intelligent machines that do our bidding. Some people, however, worry that robots like his will eventually supplant the human workforce. He has a different fear: that in the future, there won't be enough robots.

The things I learn about Rodney Brooks before I first meet him make me nervous. I know he was strange from the start. That at age four he was called "the professor." That at 12, he rigged an electronic ticktacktoe game together out of scrap metal, switches, wires, and light bulbs. That, to this day, the movie 2001: A Space Odyssey brings him to tears.

And that when his daughter Alice asked him for a Barbie, he instead bought her a saw and told her to make her own toys.

I've also seen Brooks on film. He was the scraggly haired, wild-eyed techno-topian in Cambridge director Errol Morris's 1997 documentary Fast, Cheap & Out of Control-the one who claimed that his goal in robotics was "to understand life by building something lifelike." In a series called Big Thinkers for the now-defunct TechTV, Brooks declared, "Anything that's living is a machine. I'm a machine; my children are machines. I can step back and see them as being a bag of skin full of biomolecules that are interacting according to some laws."

Brooks has come a long way-and built a lot of robots-since then. He spent a decade as the director of the Artificial Intelligence Lab at MIT, where he was one of the first scientists to give robots the ability to process data on their own. He also cofounded iRobot, maker of the floor-cleaning Roomba and the roadside-bomb-defusing PackBot. And now, with Rethink Robotics, a Fort Point-based company Brooks founded in 2008, he's making an industrial robot named Baxter. In talks available online, I've seen him proselytizing about the oncoming robot revolution with varying degrees of ferocity. Most recently, he's been vehemently warning us that in the future, we might not have enough robots to go around.

All of which explains why, upon entering the offices of Rethink Robotics, I'm concerned that this guy might be, as they say in his native Australia, a complete nutter. Though Brooks is the company's founder, he works from a cubicle in the far recesses of Rethink's space. Brooks greets me by regarding his excessively cluttered desk as if for the first time, and then asking, "Where did this mess come from? Who put all these things here?" For a brief moment, I think he's serious.

But as we chat further, Brooks, 59, is calm and confident, a demeanor more befitting the man who some consider the father of modern robotics than the character in Morris's film. He's also the father of three grown biological children and one stepdaughter. So I ask him, these many years later, to describe the parallels between conceiving children and conceiving robots. But unlike the Brooks in Morris's film, he does not offer a lecture on the definition of life. Instead, he laughs.

"Yeah," Brooks says, "everyone wants to make that comparison. But, nah. That's too stretchy. Reporters would often come to my lab at MIT and say to me, 'Oh, you're making these robots because you don't have a womb and you can't have children.' I'd say, 'Oh yeah? So you see all these women graduate students I have in my lab? Is that why they're here, too? Because they don't have wombs?'"

He throws both hands in the air and shakes them in mock surrender. "Okay. Yes. I will admit it. I don't have a womb. But that's as far as I will go."

He thinks about it another second and reconsiders. "None of my robots have ever shat all over the floor or vomited in my mouth," he says. "But my kids have."

That may be so, but Brooks has worked to make many of his robots lifelike, and has given many human names. He has created a Norman and an Allen and a Herbert and a Polly. Under his watch, his students created a Kismet and a Cog, and iRobot created My Real Baby, all of which had faces and talked to you. His latest creation, Baxter-the flagship of Rethink Robotics- is a tablet-faced robot with big, expressive, cartoon eyes and two red-and-black plastic arms. It doesn't look anything like the faceless industrial robots that now dominate global manufacturing-and that's on purpose.

Unlike those machines, which need to be walled off from human workers because they can't detect when something living is in their way, Baxter is an easily reprogrammed, 165-pound robot equipped with sonar and cameras that help it adapt to a changing environment. Brooks explains that he gave Baxter human qualities specifically so it could integrate more easily into the human world. For example, Baxter's LCD eyes will look at the spot where it's about to reach, making its movements, from a human perspective, more predictable. "If you want a machine to be able to interact with people," Brooks says, "it better not do things that are surprising to people." Brooks likes to demonstrate his machine's sensitivity by sticking his head into the path of one of Baxter's moving arms. As soon as Baxter gets close to its creator, the arm stops. "It's safe," Brooks says. "It won't hurt you."

But Baxter does pose one potential threat to people: At a cost of $25,000, it's significantly cheaper than a typical industrial robot, and cheaper than a lot of factory workers as well. Combined with the fact that Baxter is also easy to train-you just push its arms around and punch a couple of buttons and it does the rest-Brooks's latest creation could put a lot of humans out of work.

long before there was baxter, there was Norman. Built with scrap metal, cheap circuits, and a little mathematical intuition, Norman could follow a flashlight beam or scurry around the room on its own, Roomba-style. Brooks created Norman 39 years ago when he was a kid in Glenelg, Australia, a beachside suburb of Adelaide-450 miles west of Melbourne, 1,700 miles east of Perth, and far, far away from the rest of the world. "I come from a time warp," Brooks says. "We were so isolated that we were almost from another era. Milk was still delivered by horse-drawn cart."

By his own admission, Brooks wasn't a normal kid. He'd go to downtown Adelaide just to stare at a local bank's big IBM mainframe computer. "I won some genetic lottery," he says. "I always happened to be strangely good at mathematics in my head. I just popped out weird."

At 12, he made that electronic ticktacktoe game with a technical limitation that frustrated adults: The game always made the first move, and that move was always the center square. Though the game could be beat, adults took the glitch to mean that it had been designed to cheat them. "Ai yai yai," Brooks says. "I had very little patience for adults. I considered them idiots at the time."

When Brooks wasn't tinkering with circuits in the backyard shed, he was blowing things up around the neighborhood. "You could get sodium chlorate in weed killer and you'd mix that with sugar," he says, his gray hair flaring out from the sides of his head, made worse by his habit of running both hands through it while he speaks. "It's dangerous and makes big explosions."

After getting bachelor's and master's degrees in mathematics from Flinders University, in Adelaide, by 1977, he left Australia for the first time, and in 1981 earned a Ph.D. in computer science at Stanford. He married his first wife (currently an information systems lecturer at Suffolk University), and then headed east, eventually landing a teaching job in MIT's Artificial Intelligence Lab.

In the summer of 1985, while visiting his first wife's family in a Thailand village, Brooks found himself house-bound: He didn't speak Thai, they didn't speak English, and there was some concern for the young professor's safety. Without much to do, Brooks sat and thought and watched mosquitoes buzz around him. Which led him to wonder how it was that mosquitoes could move so efficiently even though they were such simple creatures, with only a few-hundred-thousand neurons? (Human brains, by contrast, have about 86 billion neurons.) The robots being created in labs like Brooks's at MIT utilized vast amounts of computational power, yet they were still dumber than insects.

At the time, robots were designed with sensors that fed information into a transmitter, which then fed that information into a mainframe computer, which then processed the data and figured out what the robot needed to do, then sent a command back through the transmitter to the robot, which executed the command. Needless to say, those robots were really slow. Throw a few obstacles in their way, and the robots could take hours to move a few meters.

Brooks's revolutionary idea, which he sketched out on paper at his in-laws' house, was to simplify. Don't build a map of the robot's world and dump all that data into its microprocessors just to keep it from running into a wall. Instead, give the robot one rule: "Move your legs," for instance. Then give it another: "Don't run into stuff." Then give it something complicated, like, "Explore." With Brooks's simplified approach, the robot wouldn't need to know everything about the world before starting out. It would do simple stuff in simple ways, just like a mosquito.

Brooks says that his contemporaries considered his idea naive. "They thought we were playing with toys," he says of the insectlike robots he subsequently built in the MIT lab. Well, they did look like toys. And yet one of those "toys," built in 1988, was perhaps the most important robot ever made. It had six legs and could walk, climb, and move at a speed few other robots had reached up to that point. Its name was Genghis.

Brooks talks about Genghis like a guy talking about his high school football glory days. His eyes widen to almost Baxterlike cartoonishness, his Australian accent getting more pronounced as he raises his voice. Genghis was radical because it was endowed with basic artificial intelligence so it could adapt to its environment. That tiny design enhancement sparked a programming revolution-nearly all robots are now built that way-which is why Genghis spent a decade on display at the Smithsonian's National Air and Space Museum, not far from the Apollo 11 command module and Orville and Wilbur Wright's Flyer.

The impact of Brooks's breakthrough-which made robots ever cheaper, smarter, and easier to produce-has been profound. In hospitals, robots made by Aethon shuttle bed sheets to and from laundry facilities. In Amazon warehouses, robots made by Kiva Systems ferry shelves full of products to and from the people who prepare them for shipping. In Afghanistan, iRobot's PackBot scuttles around disposing of bombs, rendering The Hurt Locker 's life-risking approach obsolete.

While all of these robots were influenced by Genghis, they don't look like insects. Nor do they look humanoid, like Baxter. And many of them fail to give humans the cues needed to interact with them. That's a fundamental concept missing from Google's self-driving, robotic car, for example, a shortcoming that infuriates Brooks. You can't make eye contact with it, so how do you know that it sees you? "You can make the assumption that most human drivers are not out to kill pedestrians," Brooks says. "Well, maybe in some parts of Boston they are. But with a person at the wheel who you can see, you behave accordingly. With the robotic car, how do you know what assumption to make?"

Brooks cofounded the bedford-based iRobot in 1990, and his motivation, he explains, had something to do with vanity: "My thoughts on my self-image at the time was that I didn't really want to be remembered for building insects." Then he pauses for a moment and laughs. "But after that I started building vacuum-cleaning robots. And now there is a research group using Baxter to open stool samples. So now it's shit-handling robots. I think maybe I should have quit while I was ahead. You know, that's something no one ever says: 'I hope my kid grows up to open stool samples.'"

The Roomba robotic vacuum didn't hit the market until 2002, and in the meantime, Brooks married his second wife, MIT theater professor Janet Sonenberg, and raised his four children: Alice, 26, Andrew, 29, and Matthew, 31 (whom he'd had with his first wife), plus Anna Rothschild, 28, Sonenberg's daughter. All of his biological kids went to Lincoln-Sudbury High, and two graduated from MIT. Alice has degrees from both MIT and Stanford, and recently founded a startup company called Roominate, which makes engineering toys for girls. "She manufactures in China!" Brooks shouts. "My own flesh and blood manufactures in China! Kids. They never go the way you want them to."

Alice says her father didn't help her finance her California-based company, even though, as Brooks himself will admit, iRobot has made him rich. "I wanted to do it independently of asking him for money," she says. "But I learned a lot from him being in an entrepreneurial business. Seeing the example that anything is possible was a huge influence."

Throughout the '90s, Brooks kept his MIT professorship while working with the iRobot team to develop Roomba. He says his main contribution was hunting all over China trying to find cheap and tiny microprocessors. Then, in the final phase of development, Roomba's engineers realized that those diminutive microchips couldn't run the complex software they'd developed. Adding more memory to the processor would have set the project back by months. "So I told Rod about it," says Colin Angle, Brooks's former student and a cofounder of iRobot, "and Rod said, 'Oh, I'm flying to Japan tomorrow. I'll rewrite the compiler and it'll be okay.' Now, writing a compiler is one of the most challenging software tasks that exists. But he takes off, lands 16 hours later in Narita airport, and sure enough, he emailed an executable file that was 35 percent smaller and ran perfectly."

Angle says Brooks did stuff like that all the time at iRobot: He was "the drive-by shooter of productivity," Angle says. "Anything that needed doing, Rod would do it," agrees Helen Greiner, an MIT graduate who also helped found the company. "But he wasn't someone you could task. He's not the guy who is going to join the team and be involved in all the discussions. He's the guy who comes in and changes the paradigm."

Brooks started thinking about industrial robots around 2005, in part because of all the time he'd spent in China on iRobot's behalf. While there, he'd seen tens of thousands of workers performing mundane, repetitive tasks, and wondered why machines weren't being used for those jobs instead. In some cases, robots weren't adaptable enough to perform the tasks that people were hired to do. In other cases, the answer was simple economics: Unskilled people were still cheaper than robots. One estimate suggests that, over its lifetime, a typical industrial robot could cost a company $500,000, due to servicing and reprogramming costs. But Brooks wasn't just concerned about people doing mind-numbing tasks. He was also fiercely driven by a desire to help American manufacturers compete globally. Brooks's theory was that cheap, adaptable machines would enable them to produce more goods more affordably than even China's low-cost labor force, thus heralding a domestic economic renaissance.

He floated the idea with iRobot's board of directors, but they weren't interested in investing in a new, automated workforce. Their consumer goods were selling well, and the high investment costs of developing tools for a different market didn't make economic sense. "Rod was completely enamored, obsessed, and inspired," Angle says. "His idea was that you could build an extremely low-cost robot arm and change the world with that. But we knew that was a bridge too far for iRobot at the time."

So in 2008, Brooks took a leave from his MIT professorship, which he'd held onto throughout his iRobot days, and wound down his relationship with iRobot to launch Rethink. He had signed a noncompete agreement, but kept his stock and options-by 2011, his last year on iRobot's board, they were worth as much as $20 million. In addition, iRobot received a percentage of ownership in Rethink in return for letting Brooks leave amicably. "Having had a successful exit with iRobot," Brooks says, "I could afford to grease the skids personally."

The efficiency of machine over human has long prompted factory owners to automate so they can compete in the global market, and at a cost of $25,000, Baxter is a great deal. Since Baxter has an estimated lifespan of at least 6,500 hours, its pricing works out to about $4 an hour, at a time when labor costs are rising in most of the world. Chinese manufacturing labor costs tripled between 2002 and 2009; American manufacturing jobs pay an average of $35.53 an hour; and Taiwanese pay $9.34 an hour. In Mexico, those jobs pay $6.48. You'd have to go to the Philippines, where a factory worker makes little more than $2 an hour, to find people working at wages competitive with Baxter.

But with machines like Baxter rapidly coming to the market, manufacturing jobs may disappear faster than workers can retrain for the new automated economy. That's what MIT scholars Erik Brynjolfsson and Andrew McAfee warn in their 2014 book The Second Machine Age: "Technological progress is going to leave behind some people, perhaps even a lot of people, as it races ahead. There's never been a worse time to be a worker with only 'ordinary' skills and abilities to offer, because computers, robots, and other digital technologies are acquiring these skills and abilities at an extraordinary rate."

Brooks has heard that kind of criticism before. Actually, he's heard much worse. Brooks and Baxter have appeared everywhere from Wired to 60 Minutes since Baxter's launch, and some of the stories on Brooks's latest robot have warned of the dangers from "our new robot overlords." It's a topic that seems to exasperate Brooks when I bring it up. "Are those 'terrible' machines really putting those people out of work?" Brooks asks. "Or are they getting rid of a really dull job that we shouldn't be torturing people with? Individuals who have done that job for a long time and are settled into it may feel it's not good [to eliminate it], but on the other hand, as a species, shouldn't we get rid of jobs that are that dull and are mind-deadening? People don't say, 'I just had a kid and I hope it turns out to be a factory worker.'"

In fact, a 2011 report by Deloitte and the Manufacturing Institute supports Brooks's assertion that Americans, at least, don't want those jobs. According to the report, U.S. factories are being handicapped by a labor shortage, exacerbated by the "stubbornly poor perception of manufacturing jobs among younger workers...among 18-[to-]24-year-olds, manufacturing ranks dead last among industries in which they would choose to start their careers." Therefore, it continued, a significant number of American manufacturing jobs (up to 600,000 by one estimate) are going unfilled, negatively affecting "critical functions like new product development, implementation of new technologies, or attaining productivity targets."

Which is why Brynjolfsson and McAfee concede that, in the short run, Baxter could actually increase demand for a skilled manufacturing workforce. Brynjolfsson tells me that Baxter is "an example of what we call racing with machines instead of racing against machines. Technologies like this will help bring manufacturing back to the U.S. and other high-wage countries." Indeed, the manufacturing report notes that with increased automation and the prevailing factory-work-averse culture, "access to a highly skilled, flexible workforce is the most important factor in [manufacturers'] effectiveness."

Yet, as Rethink and third-party programmers increase Baxter's capabilities, the robot could replace a broader range of jobs, possibly beyond the factory and right into your local Starbucks. Baxter has made a cup of coffee and poured a drink before. But Brooks has said repeatedly that the robot isn't dexterous or adaptable enough-yet-to do the many tasks that even a fast-food worker might perform in a given day. This summer, with a Rethink software update, Baxter's speed and accuracy doubled. "We've had a dramatic improvement in performance this year," says Paul Maeder, a founding partner of the Boston-based Highland Capital Partners, one of the venture capital firms that has invested in Rethink. "Now our sales are starting to explode."

All of this alarms Martin Ford, a Silicon Valley-based futurist and the author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future. "As I think about the robot revolution," Ford tells me, "I worry a lot more about robots in fast food, robots in the retail store, than I do about manufacturing. The service sector is where 90 percent of the employment in the United States is." Ford argues that jobs like flipping burgers and making coffee drinks have been a godsend for a shrinking middle class: "Think of all the college graduates who take jobs as cashiers or baristas before they find salaried work," he has said. "If those jobs were to vanish, those workers would be forced to file for unemployment instead."

And if Chinese companies decide to employ Baxter, too? Maeder confirms that Rethink has had some interest from Asia. Introducing Baxter to China could "potentially threaten millions of jobs in China and other emerging countries," Ford says.

"The point is not for people to keep busy," Maeder says. "The point is you can only get a higher standard of living by doing higher-skilled jobs that other people can't do. The Chinese get that."

Several weeks after our initial conversation in Rethink's offices, Brooks meets with me again to discuss worries about robot armies destroying jobs. We're at Flour Bakery in Fort Point, only a few blocks from the space Rethink leases in a former manufacturing plant that dates to the late 1800s. There's still a giant brick smokestack outside that office; left as a nostalgic nod to the area's industrial past, it's now bedecked with cell-phone transmitters.

Sitting on the patio and drinking an espresso, Brooks admits that "in all new technologies, there is some disruption." He then tells a story about his father, a technician who worked on phone systems. When Brooks was growing up, if you wanted to call from one Australian state to another, you had to book the call with an operator two days in advance. "Then there was this newfangled stuff they came out with called subscriber trunk dialing," he says. "STD. That was before STD meant something else. With that you could dial your own interstate call. My father was aghast at that. 'Why do we need that stuff?' he'd say. But we did. We all do want the ease of technology. But it did displace those phone operators."

Brooks then counters the critics with a dire warning of his own: An oncoming " demographic inversion" will leave us with fewer people to do all kinds of jobs. In the presentations he makes around the world "evangelizing" about the future of robotics, Brooks shows slides based on a 2010 United Nations study: In 2050, the percentage of working-age people in the U.S. will fall from 80 percent today to 69 percent. In China, where Ford thinks perhaps millions of jobs could be threatened by Baxterlike bots, it's more dramatic. Eighty-seven percent of that country's population is now of working age; in 2050, it's projected to be just 67 percent. Europe's working-age population is projected to decline from 77 percent to 64 percent.

That's why Brooks isn't worried about robots taking away jobs in the U.S. or abroad, but is instead worried we won't have enough robots to pick up the slack.

Brooks is also worried about his own advancing age. This past summer he returned to Australia to visit his mother, now a widow, who lives in a retirement home in Adelaide. As he was driving around the city in his rental car, Brooks tuned the radio to a program called The 100 Classic Albums That Changed Your Life. Number 19 was playing: AC/DC's T.N.T., an album that came out December 1, 1975, less than a month before Brooks's 21st birthday. Back then Brooks had a full head of brown hair that came down to his shoulders. "So an advertisement comes on during this program," Brooks says. "It says, 'Finding a place to live as you get older is going to be difficult. You should be thinking about your end of life.'"

His jaw drops open for comic effect. "Uh-oh. The 100 Classic Albums That Changed Your Life audience is supposed to be thinking about the end of life? That's where we are now?"

This, incidentally, is the fourth time he's referred to his advancing age during our chats. It's clearly something that's on his mind. During a TED talk he gave last year in Long Beach, California, with a Baxter operating on a mock assembly line behind him, Brooks told the audience that "robotics gives people a chance to have dignity as they get older." With robots, he said, the elderly "won't have to rely on people that are getting scarcer to help them." By "elderly," he meant, in part, himself. Brooks thinks Baxter could be one of those eldercare robots if researchers can find ways to make him useful in the home.

That's not something Rethink is working on, but Brooks hopes some academics might. Of the several hundred Baxters that have been sold, many were purchased by academic institutions. At RPI, they're using Baxter to act as a robotic body for a quadriplegic. At other universities they're studying ways to make Baxter's hands more adept. For all their advances, robotic hands are still very basic pinchers and grippers. "To get the grand vision to happen, you've got to have a lot of people doing research," Brooks says. "So maybe with the research robots that are out there, people will come up with ways to use them to take care of the elderly. And that can help me someday. Because, you know what? I'm heading in that direction."

Machine Menagerie
Twenty-five years of Rodney Brooks-influenced robots.

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Machine Man: Rodney Brooks and His Fear of Not Enough Robots

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Brooks has spent his life creating intelligent machines that do our bidding. Some people, however, worry that robots like his will eventually supplant the human workforce. He has a different fear: that in the future, there won't be enough robots. The things I learn about Rodney Brooks before I first meet him make me nervous.

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The supercomputer Deep Blue takes on Garry Kasparov, a world chess champion, and beats him.

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Deep Blue vs Kasparov: How a computer beat best chess player in the world - BBC News

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The Trilobite Electolux is released, the first robotic vacuum cleaner in the world.

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ImageNet is released. This is a freely available database of 14 million images, labeled by thousands of humans, that can be used to train AI models. This doesn't sound glamorous, but ImageNet has been vital to the development of AI as we know it today.

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Siri becomes available on iPhone.

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IBM’s AI, Watson, takes on humans in Jeopardy. Watson needed to answer riddles and complicated questions - and beat its competition.

Since then Watson has been put to work in many businesses, and is being trained on different kinds of data.

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In an historic event, in February 2011 IBM's Watson computer competed on against the TV quiz show's two biggest all-time champions. Watson is a computer running software called Deep QA, developed by IBM Research. While the grand challenge driving the project was to win on Jeopardy!, the broader goal of Watson was to create a new generation of technology that can find answers in unstructured data more effectively than standard search technology.

Watson does a remarkable job of understanding a tricky question and finding the best answer. IBM's scientists have been quick to say that Watson does not actually think. "The goal is not to model the human brain," said David Ferrucci, who spent 15 years working at IBM Research on natural language problems and finding answers amid unstructured information. "The goal is to build a computer that can be more effective in understanding and interacting in natural language, but not necessarily the same way humans do it."

Computers have never been good at finding answers. Search engines don't answer a question-they deliver thousands of search results that match keywords. University researchers and company engineers have long worked on question answering software, but the very best could only comprehend and answer simple, straightforward questions (How many Oscars did Elizabeth Taylor win?) and would typically still get them wrong nearly one third of the time. That wasn't good enough to be useful, much less beat Jeopardy! champions.

The questions on this show are full of subtlety, puns and wordplay-the sorts of things that delight humans but choke computers. "What is The Black Death of a Salesman?" is the correct response to the Jeopardy! clue, "Colorful fourteenth century plague that became a hit play by Arthur Miller." The only way to get to that answer is to put together pieces of information from various sources, because the exact answer is not likely to be written anywhere.

Watson runs on a cluster of Power 750™ computers-ten racks holding 90 servers, for a total of 2880 processor cores running DeepQA software and storage. It can hold the equivalent of about one million books worth of information. Over a period of years, Watson was fed mountains of information, including text from commercial sources, such as the World Book Encyclopedia, and sources that allow open copying of their content, such as Wikipedia and books from Project Gutenberg.

When a question is put to Watson, more than 100 algorithms analyze the question in different ways, and find many different plausible answers-all at the same time. Yet another set of algorithms ranks the answers and gives them a score. For each possible answer, Watson finds evidence that may support or refute that answer. So for each of hundreds of possible answers it finds hundreds of bits of evidence and then with hundreds of algorithms scores the degree to which the evidence supports the answer. The answer with the best evidence assessment will earn the most confidence. The highest-ranking answer becomes the answer. However, during a Jeopardy! game, if the highest-ranking possible answer wasn't rated high enough to give Watson enough confidence, Watson decided not to buzz in and risk losing money if it was wrong. The Watson computer does all of this in about three seconds.

By late 2010, in practice games at IBM Research in Yorktown Heights, NY, Watson was good enough at finding the correct answers to win about 70 percent of games against former Jeopardy! champions. Then in February 2011, Watson went up against Jeopardy! superstars Ken Jennings and Brad Rutter and won.

Watson's question-answering technology is expected to evolve into a commercial product. "I want to create something that I can take into every other retail industry, in the transportation industry, you name it," John Kelly, who runs IBM Research, told The New York Times. "Any place where time is critical and you need to get advanced state-of-the-art information to the front decision-makers. Computers need to go from just being back-office calculating machines to improving the intelligence of people making decisions."

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IBM's supercomputer, Watson, leverages Question-Answering technology to understand the nuance of language and deliver precise answers confidently. February 2011, Watson makes history as the first computer to compete on Jeopardy!.

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A chatbot called Eugene Goostman, which simulates a 13-year-old Ukrainian boy, is said to pass the Turing test for the first time. There are many people that say this wasn't a proper test though, and that the test was too short. So, the jury is still out on this one, but most people feel that the Turing test hasn't been passed officially yet.

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A computer program called Eugene Goostman, which simulates a 13-year-old Ukrainian boy, is said to have passed the Turing test at an event organised by the University of Reading.

The test investigates whether people can detect if they are talking to machines or humans.

The experiment is based on Alan Turing's question-and-answer game Can Machines Think?

No computer has passed the test before under these conditions, it is reported.

However, some artificial intelligence experts have disputed the victory, suggesting the contest had been weighted in the chatbot's favour.

The 65-year-old Turing Test is successfully passed if a computer is mistaken for a human more than 30% of the time during a series of five-minute keyboard conversations.

On 7 June Eugene convinced 33% of the judges at the Royal Society in London that it was human.

Other artificial intelligence (AI) systems also competed, including Cleverbot, Elbot and Ultra Hal.

Judges included actor Robert Llewellyn, who played an intelligent robot in BBC Two's science-fiction sitcom Red Dwarf, and Lord Sharkey, who led the successful campaign for Alan Turing's posthumous pardon, over a conviction for homosexual activity, in 2013.

Eugene was created by Vladimir Veselov, who was born in Russia and now lives in the United States, and Ukrainian-born Eugene Demchenko, who now lives in Russia.

Transcripts of the conversations are currently unavailable, but may appear in a future academic paper.

The judges and hidden human control groups were kept apart throughout the test.

The event was organised by Reading University's School of Systems Engineering in partnership with RoboLaw, an EU-funded organisation examining the regulation of emerging robotic technologies.

Alan Turing was an English mathematician, wartime code-breaker and pioneer of computer science.

Historic

The event has been labelled as "historic" by the organisers, who claim no computer has passed the test before.

"Some will claim that the Test has already been passed," said Kevin Warwick, a visiting professor at the University of Reading and deputy vice-chancellor for research at Coventry University.

"The words Turing test have been applied to similar competitions around the world. However, this event involved the most simultaneous comparison tests than ever before, was independently verified and, crucially, the conversations were unrestricted.

"A true Turing test does not set the questions or topics prior to the conversations. We are therefore proud to declare that Alan Turing's test was passed for the first time on Saturday."

Prof Noel Sharkey, a leading expert in robotic technology and artificial intelligence, said: "It is indeed a great achievement for Eugene. It was very clever ruse to pretend to be a 13-year-old Ukranian boy, which would constrain the conversation. But these competitions are really great to push developments."

But others have criticised the claim.

"It's nonsense," Prof Stevan Harnad told the Guardian newspaper. "We have not passed the Turing test. We are not even close."

Hugh Loebner, creator of another Turing Test competition, has also criticised the University of Reading's experiment for only lasting five minutes.

"That's scarcely very penetrating," he told the Huffington Post, noting that Eugene had previously been ranked behind seven other systems in his own 25-minute long Loebner Prize test.

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A computer program called Eugene Goostman, which simulates a 13-year-old Ukrainian boy, is said to have passed the Turing test at an event organised by the University of Reading. The test investigates whether people can detect if they are talking to machines or humans. The experiment is based on Alan Turing's question-and-answer game Can Machines Think?

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Google's driverless car passes a self-driving test in Nevada and Google invests in self-driving cars. From here on, intelligent machines start becoming an everyday reality.

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Google's DeepMind beats Lee Sedol at the ancient Asian game Go.

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Sofia, a realistic humanoid robot, is unveiled. She would go on to become the world's first robot citizen - getting citizenship in Saudi Arabia. Hanson Robotics has since also created Grace, a robot to help care for the elderly.

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Creators of famous Sophia robot reveal AI robotics for children, elderly | Nightline

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Google Duplex demos their assistant that can make phone calls for you.

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Google Duplex: A.I. Assistant Calls Local Businesses To Make Appointments

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Elon Musk unveils a pig with a chip in its brain. The chip can sense the electrical signals in the brain and this can be seen on a computer. This is only the beginning of Elon Musk's plans - his ambitious company, Neuralink, wants to transfer information to and from the human brain via implants.

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Musk's team implanted a chip in the brain of a pig to create a machine interface.

Elon Musk has unveiled a pig called Gertrude with a coin-sized computer chip in her brain to demonstrate his ambitious plans to create a working brain-to-machine interface.

"It's kind of like a Fitbit in your skull with tiny wires," the billionaire entrepreneur said on a webcast.

His start-up Neuralink applied to launch human trials last year.

The interface could allow people with neurological conditions to control phones or computers with their mind.

Mr Musk argues such chips could eventually be used to help cure conditions such as dementia, Parkinson's disease and spinal cord injuries.

But the long-term ambition is to usher in an age of what Mr Musk calls "superhuman cognition", in part to combat artificial intelligence so powerful he says it could destroy the human race.

Gertrude was one of three pigs in pens that took part in Friday's webcast demo. She took a while to get going, but when she ate and sniffed straw, the activity showed up on a graph tracking her neural activity. She then mostly ignored all the attention around her.

The processor in her brain sends wireless signals, indicating neural activity in her snout when looking for food.

Meet Elon Musk, the man who inspired Robert Downey Jr's take on Iron Man

Mr Musk said the original Neuralink device, revealed just over a year ago, had been simplified and made smaller.

"It actually fits quite nicely in your skull. It could be under your hair and you wouldn't know."

Founded in 2017, Neuralink has worked hard to recruit scientists, something Mr Musk was still advertising for on Twitter last month and which he said was the purpose of Friday's demo.

Getting the human brain to communicate with machines is an ambitious goal

The device the company is developing consists of a tiny probe containing more than 3,000 electrodes attached to flexible threads thinner than a human hair, which can monitor the activity of 1,000 brain neurons.

Ahead of the webcast, Ari Benjamin, at the University of Pennsylvania's Kording Lab, had told BBC News the real stumbling block for the technology could be the sheer complexity of the human brain.

"Once they have the recordings, Neuralink will need to decode them and will someday hit the barrier that is our lack of basic understanding of how the brain works, no matter how many neurons they record from.

"Decoding goals and movement plans is hard when you don't understand the neural code in which those things are communicated."

Mr Musk's companies SpaceX and Tesla have captured the public imagination with his attempts to drive progress in spaceflight and electric vehicles respectively.

But both also demonstrate the entrepreneur's habit of making bold declarations about projects that end up taking much longer to complete than planned.

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Neuralink: Elon Musk unveils pig with chip in its brain

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Gertrude the pig is a prototype of a brain-to-machine interface.

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GPT-3 AI from the OpenAI nonprofit research institute founded by Elon Musk. It's an AI system that has a highly sophisticated understanding of language. It was trained using 175 billion parameters (data from the internet) meaning that it has enough knowledge to answer SAT questions, hold conversations and can even write a newspaper article.

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Wu-Dao 2.0 (meaning enlightenment) is developed in China. It's more advanced than GPT-3 and can even sing! It's being used to power China's first AI virtual student.