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020 _a9783030435820
_9978-3-030-43582-0
024 7 _a10.1007/978-3-030-43582-0
_2doi
050 4 _aQ175.4-.55
072 7 _aJF
_2bicssc
072 7 _aSOC026000
_2bisacsh
072 7 _aJB
_2thema
082 0 4 _a303.483
_223
100 1 _aGrant, Thomas D.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aOn the path to AI
_h[electronic resource] :
_bLaw’s prophecies and the conceptual foundations of the machine learning age /
_cby Thomas D. Grant, Damon J. Wischik.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Palgrave Macmillan,
_c2020.
300 _aXXII, 147 p. 4 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPrologue: Starting with logic -- CHAPTER 1: Two Revolutions -- CHAPTER 2: Getting past logic -- CHAPTER 3: Experience and data as input -- CHAPTER 4: Finding patterns as the path from input to output -- CHAPTER 5: Output as prophecy -- CHAPTER 6: Explanations of machine learning -- CHAPTER 7: Juries and other reliable predictors -- CHAPTER 8: Poisonous datasets, poisonous trees -- CHAPTER 9: From Holmes to AlphaGo -- CHAPTER 10:Conclusion -- EPILOGUE: Lessons in two directions.
506 0 _aOpen Access
520 _aThis open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age—prediction based on datasets. On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data. .
650 0 _aScience
_xSocial aspects.
650 0 _aHuman geography.
650 0 _aInformation technology
_xLaw and legislation.
650 0 _aMass media
_xLaw and legislation.
650 0 _aArtificial intelligence.
650 1 4 _aScience and Technology Studies.
650 2 4 _aHuman Geography.
650 2 4 _aIT Law, Media Law, Intellectual Property.
650 2 4 _aArtificial Intelligence.
700 1 _aWischik, Damon J.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030435813
776 0 8 _iPrinted edition:
_z9783030435837
856 4 0 _uhttps://doi.org/10.1007/978-3-030-43582-0
912 _aZDB-2-SLS
912 _aZDB-2-SXS
912 _aZDB-2-SOB
999 _c37812
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