Search engines, spreadsheets, and databases are good examples of such complementary forms of information technology. Turing himself, and other technology pioneers such as Douglas Engelbart and Norbert Wiener, understood that computers would be most useful to business and society when they augmented and complemented human capabilities, not when they competed directly with us. It also comes from a fundamental mismatch between the needs of business and the way AI is currently being conceived by many in the technology sector-a mismatch that has its origins in Alan Turing’s pathbreaking 1950 “imitation game” paper and the so-called Turing test he proposed therein.Īt best, this was only one way of articulating machine intelligence. This disappointing performance is not merely due to the relative immaturity of AI technology. Amid all the hype, US businesses have been slow in adopting the most advanced AI technologies, and there is little evidence that such technologies are contributing significantly to productivity growth or job creation. The one group everyone assumes will benefit is business, but the data seems to disagree. Glen Weyl is Founder of the RadicalxChange Foundation, Microsoft’s Office of the Chief Technology Officer Political Economist and Social Technologist (OCTOPEST) and co-author with Eric Posner of Radical Markets: Uprooting Capitalism and Democracy for a Just Society.įears of Artificial intelligence fill the news: job losses, inequality, discrimination, misinformation, or even a superintelligence dominating the world. His research interests include machine learning, optimization, and control theory.Į. Jordan is the Pehong Chen Distinguished Professor in the Department of EECS and the Department of Statistics at the University of California, Berkeley. He is the author of five books, including New York Times bestseller Why Nations Fail and The Narrow Corridor: States, Societies, and the Fate of Liberty (both with James A. Daron Acemoglu is an Institute Professor at MIT.
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