Chris Russell

Amazon Web Services, Inc.

United States

SCHOLARLY PAPERS

4

DOWNLOADS
Rank 4,340

SSRN RANKINGS

Top 4,340

in Total Papers Downloads

12,836

SSRN CITATIONS
Rank 15,649

SSRN RANKINGS

Top 15,649

in Total Papers Citations

50

CROSSREF CITATIONS

21

Scholarly Papers (4)

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 4,797 (2,572)
Citation 179

Abstract:

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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

Computer Law & Security Review 41 (2021): 105567.
Number of pages: 72 Posted: 27 Mar 2020 Last Revised: 28 Sep 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 4,275 (3,124)
Citation 7

Abstract:

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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, Vol. 123, No. 3, 2021
Number of pages: 51 Posted: 03 Mar 2021 Last Revised: 19 Aug 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 2,879 (6,127)
Citation 7

Abstract:

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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 885 (37,218)
Citation 16

Abstract:

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