Legal Taxonomies of Machine Bias: Revisiting Direct Discrimination-Reference-Cited by-同舟云学术

Legal Taxonomies of Machine Bias: Revisiting Direct Discrimination

Published:2023-06-12 Issue: Volume: Page:
ISSN:
Container-title:2023 ACM Conference on Fairness, Accountability, and Transparency
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Author:

Binns Reuben¹^ORCID,Adams-Prassl Jeremias²^ORCID,Kelly-Lyth Aislinn²^ORCID

Affiliation:

1. Computer Science, University of Oxford, United Kingdom

2. Law, University of Oxford, United Kingdom

Funder

European Research Council under the European Union?s Horizon 2020 research and innovation programme

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3593013.3594121

Reference41 articles.

1. Adams‐Prassl , Jeremias , Reuben Binns , and Aislinn Kelly‐Lyth . "Directly discriminatory algorithms." The Modern Law Review 86.1 ( 2022 ): 144-175 . Adams‐Prassl, Jeremias, Reuben Binns, and Aislinn Kelly‐Lyth. "Directly discriminatory algorithms." The Modern Law Review 86.1 (2022): 144-175.

2. Big Data's Disparate Impact;Barocas Solon;California Law Review,2016

3. Bailey and Norbury(eds). 2020. Bennion on Statutory Interpretation . ( 8 th ed). LexisNexis . Bailey and Norbury(eds). 2020. Bennion on Statutory Interpretation. (8th ed). LexisNexis.

4. Bower , Amanda , Sarah N . Kitchen , Laura Niss , Martin J. Strauss , Alexander Vargas , and Suresh Venkatasubramanian . " Fair Pipelines ." arXiv e-prints ( 2017 ): arXiv-1707 Bower, Amanda, Sarah N. Kitchen, Laura Niss, Martin J. Strauss, Alexander Vargas, and Suresh Venkatasubramanian. "Fair Pipelines." arXiv e-prints (2017): arXiv-1707

5. Causally Interpreting Intersectionality Theory

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