000 | 03543nam a22005655i 4500 | ||
---|---|---|---|
001 | 978-3-030-43582-0 | ||
003 | DE-He213 | ||
005 | 20240508091657.0 | ||
007 | cr nn 008mamaa | ||
008 | 200602s2020 sz | s |||| 0|eng d | ||
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 _d37812 |