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financial resources to hire the most talented workers in the field, enhancing their power even further. We have been giving away valuable data for the sake of freebies like Gmail and Facebook, but as the journalist and author John Lanchester has pointed out in the London Review of Books, if it is free, then you are the product. Their real customers are the ones who pay them for access to knowledge about us, so that they can persuade us to buy their products or otherwise influence us. One way around the monopolistic control of data is to split the ownership of data away from firms that use them. Individuals would instead own and control access to their personal data (a model that would encourage competition, since people would be free to move their data to a company that offered better services). Finally, abuse of data is not limited to corporations: In totalitarian states, or even nominally democratic ones, governments know things about their citizens that Orwell could not have imagined. The use they make of this information may not always be transparent or possible to counter. The prospect of AI for military purposes is frightening. One can imagine intelligent systems being designed to act autonomously based on real-time data and able to act faster than the enemy, starting catastrophic wars. Such wars may not necessarily be conventional or even nuclear wars. Given how essential computer networks are to modern society, it is much more likely that AI wars will be fought in cyberspace. The consequences could be just as dire. Despite this loss of control, we continue to march inexorably into a world in which AI will be everywhere: Individuals won’t be able to resist its convenience and power, and corporations and governments won’t be able to resist its competitive advantages. But important questions arise about the future of work. Computers have been responsible for considerable losses in blue-collar jobs in the last few decades, but until recently many white-collar jobs—jobs that “only humans can do”—were thought to be safe. Suddenly that no longer appears to be true. Accountants, many legal and medical professionals, financial analysts and stockbrokers, travel agents—in fact, a large fraction of white-collar jobs—will disappear as a result of sophisticated machine-learning programs. We face a future in which factories churn out goods with very few employees and the movement of goods is largely automated, as are many services. What’s left for humans to do? In 1930—long before the advent of computers, let alone AI—John Maynard Keynes wrote, in an essay called “Economic Possibilities for our Grandchildren,” that as a result of improvements in productivity, society could produce all its needs with a fifteen-hour work week. He also predicted, along with the growth of creative leisure, the end of money and wealth as a goal: We shall be able to afford to dare to assess the money-motive at its true value. The love of money as a possession—as distinguished from the love of money as a means to the enjoyments and realities of life—will be recognised for what it is, a somewhat disgusting morbidity, one of those semi-criminal, semi-pathological propensities which one hands over with a shudder to the specialists in mental disease. 130 HOUSE_OVERSIGHT_016350