000			01943 a2200229 4500
003			OSt
005			20211105163848.0
008			211105b |||||||| |||| 00| 0 eng d
020			_a9781786494313
040			_cIIMV
082			_a174.90063 _bCHR
100	1		_aChristian, Brian _931262 _d1984-
245	1	4	_aThe alignment problem: _bmachine learning and human values/ _cby Brian Christian.
260			_bAtlantic Books, _c2020. _aLondon
300			_axii, 476p. ; _c25 cm
505			_aProphecy. Representation -- Fairness -- Transparency -- Agency. Reinforcement -- Shaping -- Curiosity -- Normativity. Imitation -- Inference -- Uncertainty.
520			_a"A 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	1		_aArtificial intelligence _xMoral and ethical aspects. _931264
650	1		_aArtificial intelligence _xSocial aspects. _931265
650	1		_aMachine learning _xSafety measures. _931266
942			_2ddc _cBK
999			_c5672 _d5672