Few industries are safe; legal Armenia Email List clerks and translators are as vulnerable as supermarket cashiers and long-haul truckers. We told that mass technological unemployment will necessitate a universal basic income. We have also heard the opposing view: that humans have absorbed waves of automation before, and that we have used the time liberated by technology to generate new, more stimulating professions that have improved our standard of living. But what if neither of these scenarios is accurate? What if automation displaces millions from their jobs while at the same time improving healthcare diagnostics and slowing climate change? How do we thrive in this kind of hybrid environment? Striding into this middle ground is Kevin Rose, a technology columnist at the New York Times. He describes himself as a “sub optimist” about AI.
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On a 10-point scale, with 1 being not at gulf email list all fussed and 10 being convinced of a coming AI-driven apocalypse, he stands at “a 2 or a 3” about the technology, but “an 8.5 or a 9” on the people behind it. For the past three years, Rose has handed out Good Tech Awards to people and organizations that have harnessed the power of technology to tackle major problems. Winners include an atmospheric scientist, Christa Hasenkopf, who founded an open-source platform that records air quality around the world, and the owners of VI sabot, a Facebook messenger chatbot that helps immigrants through the visa application and extension process. He believes that his award winners are outnumbered and overshadowed by executives. Who see technology as a conduit for maximizing profits. Unless we challenge them, he argues, the labor market will become more precarious, more discriminatory, and less enjoyable.
Pushing back against technology is hard
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In Futureproof, with honesty and good humor, he attempts to correct some faults in how we think about AI and suggests ways we can make the most of our advantages. The first half of the book contains some revealing insights. Rose thinks it is wrong to expect AI to eliminate whole categories of jobs. Almost every role contains tasks that tech could do better than people and requirements that are very human. In journalism, robots could be taught to summarize an earnings report for a newswire, but not conduct an investigation into public-sector corruption. AI can scan X-rays for abnormalities, but it can’t reassure worried parents about their child’s prognosis. We should also challenge our assumptions about what robots are capable of. Designers are struggling to replicate the actions of a human hand, which makes shelf-stacking hard to automate.
