Search Results - "Selbst, Andrew D."

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  1. 1

    Big Data's Disparate Impact by Barocas, Solon, Selbst, Andrew D.

    Published in California law review (01-06-2016)
    “…Advocates of algorithmic techniques like data mining argue that these techniques eliminate human biases from the decision-making process. But an algorithm is…”
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    Journal Article
  2. 2

    Unfair artificial intelligence: How FTC intervention can overcome the limitations of discrimination law by Selbst, Andrew D, Barocas, Solon

    Published in University of Pennsylvania law review (01-04-2023)
    “…Discriminatory artificial intelligence is unfair. Until very recently, the Federal Trade Commission, the United States federal agency charged with regulating…”
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    Journal Article
  3. 3

    Meaningful information and the right to explanation by Selbst, Andrew D, Powles, Julia

    Published in International data privacy law (01-11-2017)
    “…In May 2018, Europe’s new General Data Protection Regulation (GDPR) will apply across all European Union Member States.1 The GDPR is an ambitious, complicated,…”
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  4. 4

    NEGLIGENCE AND AI'S HUMAN USERS by Selbst, Andrew D

    Published in Boston University law review (01-09-2020)
    “…Negligence law is often asked to adapt to new technologies. So it is with artificial intelligence ("AI"). Though AI often conjures images of autonomous robots,…”
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  5. 5

    AN INSTITUTIONAL VIEW OF ALGORITHMIC IMPACT ASSESSMENTS by Selbst, Andrew D

    Published in Harvard journal of law & technology (22-09-2021)
    “…Scholars and advocates have proposed algorithmic impact assessments ("AIAs") as a regulatory strategy for addressing and correcting algorithmic harms. An…”
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  6. 6

    The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons by Barocas, Solon, Selbst, Andrew D, Raghavan, Manish

    Published 10-12-2019
    “…Counterfactual explanations are gaining prominence within technical, legal, and business circles as a way to explain the decisions of a machine learning model…”
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  7. 7

    The Fallacy of AI Functionality by Raji, Inioluwa Deborah, Kumar, I. Elizabeth, Horowitz, Aaron, Selbst, Andrew D

    Published 01-07-2022
    “…2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT '22) Deployed AI systems often do not work. They can be constructed haphazardly,…”
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