NIPS 2016
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Symposium

Machine Learning and the Law

Adrian Weller · Thomas D. Grant · Conrad McDonnell · Jatinder Singh

111 + 112

Advances in machine learning and artificial intelligence mean that predictions and decisions of algorithms are already in use in many important situations under legal or regulatory control, and this is likely to increase dramatically in the near future. Examples include deciding whether to approve a bank loan, driving an autonomous car, or even predicting whether a prison inmate is likely to offend again if released. This symposium will explore the key themes of privacy, liability, transparency and fairness specifically as they relate to the legal treatment and regulation of algorithms and data. Our primary goals are (i) to inform our community about important current and ongoing legislation (e.g. the EU’s GDPR https://en.wikipedia.org/wiki/GeneralDataProtection_Regulation which introduces a "right to explanation"); and (ii) to bring together the legal and technical communities to help form better policy in the future.

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