Chris Russell

Amazon Web Services, Inc.

United States

  • Amazon Web Services, Inc.

SCHOLARLY PAPERS

4

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9,126

SSRN CITATIONS
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SSRN RANKINGS

Top 15,748

in Total Papers Citations

50

CROSSREF CITATIONS

20

Scholarly Papers (4)

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1.

Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR

Harvard Journal of Law & Technology, 31 (2), 2018
Number of pages: 47 Posted: 02 Nov 2017 Last Revised: 22 Apr 2019
Sandra Wachter, Brent Mittelstadt and Chris Russell
University of Oxford - Oxford Internet Institute, University of Oxford - Oxford Internet Institute and Amazon Web Services, Inc.
Downloads 4,122 (2,725)
Citation 103

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accountability, algorithms, artificial intelligence, auditing, automated decision-making, counterfactuals, data ethics, data protection, explainability, GDPR, interpretability, machine learning, right to explanation, transparency

2.

Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI

Number of pages: 72 Posted: 27 Mar 2020 Last Revised: 29 Mar 2021
Sandra Wachter, Brent Mittelstadt and Chris Russell
University of Oxford - Oxford Internet Institute, University of Oxford - Oxford Internet Institute and Amazon Web Services, Inc.
Downloads 2,837 (5,197)
Citation 7

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AI, EU, Non-Discrimination Law, Fairness, Discrimination, Bias, Algorithms, Law, Demographic Parity, Machine Learning, Artificial Intelligence, Algorithms

3.

Bias Preservation in Machine Learning: The Legality of Fairness Metrics Under EU Non-Discrimination Law

West Virginia Law Review, Forthcoming
Number of pages: 51 Posted: 03 Mar 2021
Sandra Wachter, Brent Mittelstadt and Chris Russell
University of Oxford - Oxford Internet Institute, University of Oxford - Oxford Internet Institute and Amazon Web Services, Inc.
Downloads 1,381 (16,619)
Citation 1

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artificial intelligence, machine learning, law, discrimination, non-discrimination, anti-discrimination, algorithms, European Union, bias, fairness, automated decision-making, fairness metrics, equality, substantive equality, formal equality, auditing

4.

Explaining Explanations in AI

Proceedings of FAT* ’19: Conference on Fairness, Accountability, and Transparency (FAT* ’19), January 29–31, 2019, Atlanta, GA, USA. ACM, New York, NY, USA, doi/10.1145/3287560.3287574, ISBN: 978-1-4503-6125-5
Number of pages: 10 Posted: 27 Nov 2018
Brent Mittelstadt, Chris Russell and Sandra Wachter
University of Oxford - Oxford Internet Institute, Amazon Web Services, Inc. and University of Oxford - Oxford Internet Institute
Downloads 786 (37,607)
Citation 16

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interpretability, explanations, accountability, philosophy of science, data ethics, machine learning, artificial intelligence, automated decision-making