Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us–and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem.
Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole–and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands.
From the AI program which cheats at computer games to the sexist algorithm behind Google Translate, Brian Christian explains how, as AI develops, we rapidly approach a collision between artificial intelligence and ethics. If we stand by, we face a future with unregulated algorithms that propagate our biases – and worse – violate our most sacred values. Urgent and fascinating, this is an accessible primer to the most important issue facing AI researchers today.
Brian Christian is the author of the acclaimed bestsellers “The Most Human Human,” a New York Times editors’ choice and a New Yorker favourite book of the year, and “Algorithms to Live By” (with Tom Griffiths), a #1 Audible bestseller, Amazon best science book of the year and MIT Technology Review best book of the year. His new book is The Alignment Problem: How Can Machines Learn Human Values?
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