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FCW : February 2016
The robots are coming. They don’t want our jobs exactly, but work as we know it will be transformed nonetheless. So argues computer scientist Jerry Kaplan, who’s been immersed in the intersection of technology, artificial intelligence and traditionally human tasks for nearly 40 years. The author of “Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence,” Kaplan argues that huge changes are indeed underway — they’re just not the ones that are often discussed. First of all, “we don’t automate jobs — we automate tasks,” Kaplan said during a mid-January discussion at Mitre organized by Hooks Book Events. And that process, he argued, has been underway since at least the Industrial Revolution. According to Kaplan, the problem is that too much attention is being paid to the idea of ever-smarter machines and software — that sentient computer systems are evolving rapidly enough to replace humans in all sorts of roles. The term “artificial intelligence,” he said, distorts the public discourse. “Machines don’t think,” Kaplan declared — certainly not in the way that humans do — and “it’s really little more than an analogy to say they think at all.” And although there have certainly been advances in machine learning, he added, “there’s very little evidence that machines are on the path to becoming thinking, sentient beings.” To argue that current AI shows we’re headed in that direction “is like climbing a tree and claiming progress in getting to the moon.” “That narrative of the field is both misguided and counterproductive,” Kaplan said. “The real issue is that, when it comes to work, human intelligence is somewhat overrated.” And that reality has huge implications that are being overshadowed by the popular discourse about AI. “If you have enough data, you can solve tasks that used to require intelligence,” he said. And just because machines can perform tasks that humans use intelligence for, that doesn’t mean machines have to think in order to do so. Kaplan cited translation and text analysis as two classic examples. “Machine translation bears almost no resemblance to the human process,” he said, but the results can be remarkably accurate. And in jobs ranging from truck driver to surgeon, he argued, much of what humans do with thought, training and expertise really boils down to serving as a human sensor to connect inputs with appropriate responses. “Our ability to interpret data Are we thinking about AI all wrong? BY TROY K. SCHNEIDER Computer scientist Jerry Kaplan wants to talk about automation and its implications for many government functions 30 February 2016 FCW.COM Bookshelf 0216fcw_030-031.indd 30 1/27/16 3:35 PM
March 15, 2016