SPEAKER_00: Amazing, fascinating stories of inventions, ideas and innovations. Yes, this is the podcast about the things that have helped to shape our lives. Podcasts from the BBC World Service are supported by advertising.
SPEAKER_02: 50 Things That Made the Modern Economy with Tim Harford
SPEAKER_01: It's about the size and shape of an office photocopier. With a gentle whirring noise, it traverses the warehouse floor while its two arms raise or lower themselves on scissor lifts ready for the next task. Each arm has a camera on its knuckle. The left arm eases a cardboard box forward on the shelf, the right arm reaches in and extracts a bottle. Like many new robots, this one comes from Japan. The Hitachi Corporation showcased it in 2015, with hopes to be selling it by 2020. It's not the only robot that can pick a bottle off a shelf, but it's as close as robots have yet come to performing this seemingly simple task as speedily and dexterously as a good old-fashioned human. One day, robots like this might replace warehouse workers altogether. For now, humans and machines are running warehouses together. In Amazon's depots, the company's Kiva robots scurry around, not picking things off shelves, but carrying the shelves to humans for them to pick things off. By saving the time workers would otherwise spend trudging up and down aisles, Kiva robots can improve efficiency up to fourfold. Robots and humans are working side by side in factories, too. Factories have had robots for decades, of course, since 1961, when General Motors installed the first Unimate, a one-armed robot resembling a small tank that was used for tasks like welding. But until recently, they were strictly segregated from the human workers, partly to stop the humans coming to any harm, and partly to stop them confusing the robots, whose working conditions had to be strictly controlled. With some new robots, that's no longer necessary. A charming example by the name of Baxter can generally avoid bumping into humans or falling over if humans bump into it. Baxter has cartoon eyes that help indicate to human co-workers where it's about to move, and if someone knocks a tool out of Baxter's hand, it won't dopily try to continue the job. Historically, industrial robots needed specialist programming. Baxter can learn new tricks from co-workers showing it what to do. For years, there's been a trend to offshore manufacturing to emerging markets, where workers are cheaper. But now, the trend is to reshore, and robots are part of that. Robots are doing more and more things. They're lettuce pickers, bartenders, hospital porters. Still, let's face it, they're not yet doing as much as we once expected. In 1962, a year after the Unimate, the American cartoon, the Jetsons, imagined Rosie, a robot maid, doing all the household chores. Half a century on, where's Rosie? Despite recent progress, she's not coming any time soon. That progress is partly thanks to robot hardware. In particular, better and cheaper sensors. In human terms, that's like improving a robot's eyes, the touch of its fingertips, or its inner ear, and sense of balance. But it's also thanks to software. In human terms, robots are getting better brains. And it's about time. Machine thinking is another area where early expectations were disappointed. Attempts to invent artificial intelligence are generally dated to 1956, and a summer workshop at Dartmouth College for scientists with a pioneering interest in machines that use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. At the time, machines with human-like intelligence were often predicted to be about 20 years away. Now, they're often predicted to be, well, about 20 years away. It's only in the last few years that progress in artificial intelligence has really started to accelerate. Specifically in what's known as narrow AI, algorithms that can do one thing very well, like playing Go, or filtering email spam, or recognizing faces in your Facebook photos. Processors have got faster, data sets bigger, and programmers better at writing algorithms that can learn to improve their own functioning, in ways that often remain opaque to their human creators. That capacity for self-improvement causes some thinkers to worry what will happen if we create artificial general intelligence, a system which could apply itself to any problem, like humans can. Will it rapidly turn itself into a superintelligence? How could we keep it under control? That's not an imminent concern, at least. It's reckoned human-level artificial general intelligence is still, oh, about 20 years away. But narrow AI is already transforming the economy. For years, algorithms have been taking over white-collar drudgery in areas such as bookkeeping and customer service. And more prestigious jobs are far from safe. Software is getting to be as good as experienced lawyers at predicting what lines of argument are most likely to win a case. Robo-advisors are dispensing investment advice. And algorithms are routinely churning out news reports on subjects like the financial markets and sports. Although, luckily for me, it seems they can't yet write radio features on economics. Some economists reckon robots and AI explain a curious economic trend. Eric Brynjolfsson and Andrew McAfee argue there's been a great decoupling between jobs and productivity. That's a measure of how efficiently an economy takes inputs, such as people and capital, and turns them into useful stuff. Historically, as you'd expect, better productivity meant more jobs and higher wages. But since the turn of the century, that's not been the case. At least by some measures, productivity is improving but jobs aren't being created and wages are stagnating. Some economists worry that we're experiencing secular stagnation, where there's not enough demand to spur economies into growing, even with interest rates down to zero or below. Technology destroying jobs is nothing new. It's why 200 years ago, the Luddites went around destroying technology. Luddite has become a term of mockery because technology has always, eventually, created new jobs to replace the ones it destroyed. Better jobs. Or at least, different jobs. What happens this time remains debatable. It's at least conceivable that some of the jobs humans will be left doing will actually be worse. That's because technology seems to be making more progress at thinking than doing. Robots' brains are improving faster than their bodies. Martin Ford, the author of Rise of the Robots, points out that robots can land aeroplanes and trade shares on Wall Street, but they still can't clean toilets. So you can guess which jobs we'll be left with. So perhaps for a glimpse of the future, we should look not to Rosie the robot, but to another device now being used in warehouses, the Jennifer unit. It's a headset that tells human workers what to do, down to the smallest detail. So if you have to pick 19 identical items from a shelf, it'll tell you to pick five, then five, then five, then four. That leads to fewer errors than saying, pick 19. If robots beat humans at thinking, but humans beat robots at picking things off shelves, why not control a human body with a robot brain? It may not be a fulfilling career choice, but you can't deny the logic. The starting point for our journey into a
SPEAKER_02: robot future was The Second Machine Age by Erik Brynjolfsson and Andrew McAfee. For a full list of our sources, please see bbcworldservice.com slash 50 things. Just before you go, I'd like
SPEAKER_01: to recommend another podcast series from the BBC World Service. The Inquiry, one pressing question from the news, four expert witnesses and some challenging answers.
