Conclusion: Answering the machinery question

Date: 23-06-2016
Source: The Economist

Glimpses of an AI-enabled future




The debates about whether AI will destroy jobs, and whether it might destroy humanity, are really arguments about the rate of change

What does all this tell us today? Historical analogies are never perfect, but they can be informative. Artificial intelligence is now prompting many of the same concerns as mechanisation did two centuries ago. The 19th-century experience of industrialisation suggests that jobs will be redefined, rather than destroyed; that new industries will emerge; that work and leisure will be transformed; that education and welfare systems will have to change; and that there will be geopolitical and regulatory consequences.

employment UK by IndustryIn many ways, the two big debates about AI—whether it will destroy jobs, and whether it might destroy humanity—are really arguments about the rate of change. If you believe that AI is improving so rapidly that human-level artificial general intelligence (AGI) is just around the corner, you are more likely to worry about unexpected and widespread job losses and the possibility that the technology may suddenly get out of control. It seems more probable, however, that AI will improve steadily, and that its impact over the next decade or two, while significant, will not be on the same scale as the epochal shift from a mostly agricultural to a mostly industrial economy.

AGI is probably still a couple of decades away, perhaps more, so the debate about what it might or might not be able to do, and how society should respond to it, is still entirely theoretical. This special report has therefore focused on the practical effects of AI in the nearer term. These are likely to be a broadening and quickening of the spread of computers into the workplace and everyday life, requiring people to update their skills faster and more frequently than they do at the moment. Provided educational systems are upgraded and made more flexible, which is beginning to happen, that should be entirely feasible.

So far the debate has been dominated by the gloomy possibilities of massive job losses and rogue AIs. More positive scenarios, in which AI dramatically changes the world for the better, tend to attract less attention. So here are three examples.

First, AI could transform transport and urban life, starting with self-driving vehicles. Being able to summon one at will could remove the need to own a car, greatly reduce the number of vehicles on the roads and all but eliminate road deaths. Urban environments will enjoy a renaissance as pollution declines and space previously devoted to parking is reallocated to parks, housing and bicycle paths.

Second, AI could soon enable people to converse with a wide range of things: their home and their car, most obviously, just as people talk to a disembodied computer in “Star Trek”, but also AI avatars of companies and other organisations, information services, AI advisers and tutors. A host of AI-powered personal assistants, such as Alexa, Cortana, Siri and Viv, are already jostling for position, and could become an important new way to interact with computers and access information, like the web browser and touchscreen before them. Speech alone is not always the best way to interact with a computer, so such conversations will often be accompanied by graphics (perhaps in the form of “augmented reality” overlays on people’s vision). AI also has huge potential to help humans talk to one another, by facilitating real-time translation between people using different languages. Basic versions of this technology exist today, and will get better.

The indefatigable helper
Third, AI could make a big difference by turbocharging scientific and medical research. “The thing that excites me the most is using AI to help speed up scientific breakthroughs,” says Demis Hassabis of DeepMind. An AI could act as a relentless research assistant, he reckons, in fields from cancer research to climate change, helping solve problems by sifting through data, reading thousands of scientific papers and suggesting hypotheses or pointing out correlations that might be worth investigating. IBM is already working in this area, using its Watson AI technology to analyse large volumes of medical data. Deep learning will be used to analyse the data from the “100,000 Genomes” project now under way in England’s National Health Service; the same techniques can help physicists sift reams of data from particle colliders for new discoveries.

After years of frustration with AI’s slow rate of progress, it is ironic that many now think it is moving too quickly. Yet a sober assessment suggests that AI should be welcomed, not feared. In the 1840s John Stuart Mill wrote that “the proof of the ultimate benefit to labourers of mechanical inventions…will hereafter be seen to be conclusive.” A future economist may say the same of the benefits of AI, not just for labourers but for everyone.


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