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020			_a9780393868333
040			_aIIITD
082			_a174.90 _bCHR-A
100			_aChristian, Brian
245			_aThe alignment problem : _bmachines learning and human values _cby Brian Christian
260			_aNew York : _bW.W. Norton & Company, _c©2020
300			_axvi, 476 p. ; _c20 cm.
504			_aIncludes bibliographical references and index.
505			_tI.Prophecy
505			_tII.Agency
505			_tIII.Normativity
520			_aA jaw-dropping exploration of everything that goes wrong when we build AI systems-and the movement to fix them. 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. 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 autonomous vehicles on our streets can injure or kill. When 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. In best-selling author Brian Christian's riveting account, we meet the alignment problem's "first-responders," and learn their ambitious plan to solve it before our hands are completely off the wheel-- Provided by publisher.
650			_aArtificial intelligence -- Moral and ethical aspects
650			_aMachine learning -- Safety measures
650			_aSoftware failures
942			_cBK _2ddc
999			_c208667 _d208667