01956cam a2200253 i 4500003000700000005001700007008004100024010001500065020001800080020003100098020002600129050002500155100003800180245008300218264004900301300002900350504006900379520107200448650005601520650004501576650003901621650002301660650001901683PIMLIB20250418092406.0241218s2020    nyu      b    001 0 eng    a2020029036  a9780393868333  a9780393635829q(hardcover)  z9780393635836q(epub)00aQ334.7b.C488Ay2020  aChristian, Brian,d1984-eauthor.14aThe Alignment problem :bmachine learning and human values /cBrian Christian. 1aNew York, NY :bW.W. Norton & Company,c2020  axii, 476 pages ;c25 cm.  aIncludes bibliographical references (pages [401]-451) and index.  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"--cProvided by publisher. 0aArtificial IntelligencexMoral and ethical aspects. 0aArtificial IntelligencexSocial aspects. 0aMachine learningxSafety measures. 0aSoftware failures. 0aSocial values.