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Andrew Selbst
Andrew Selbst
UCLA School of Law
Verified email at law.ucla.edu - Homepage
Title
Cited by
Cited by
Year
Big Data's Disparate Impact
S Barocas, AD Selbst
California Law Review 104 (3), 671-732, 2016
43052016
Fairness and Abstraction in Sociotechnical Systems
AD Selbst, danah boyd, S Friedler, S Venkatasubramanian, J Vertesi
ACM Conference on Fairness, Accountability, and Transparency (FAT*), 2018
9412018
The Intuitive Appeal of Explainable Machines
AD Selbst, S Barocas
Fordham Law Review 87, 1085-1139, 2018
5972018
Meaningful Information and the Right to Explanation’(2017)
AD Selbst, J Powles
International Data Privacy Law 7, 233, 0
594*
Disparate Impact in Big Data Policing
AD Selbst
Georgia Law Review 52, 109-195, 2017
4412017
The hidden assumptions behind counterfactual explanations and principal reasons
S Barocas, AD Selbst, M Raghavan
Proceedings of the 2020 conference on fairness, accountability, and …, 2020
2312020
Negligence and AI's Human Users
AD Selbst
Boston University Law Review 100, 1315-1376, 2020
1642020
The fallacy of AI functionality
ID Raji, IE Kumar, A Horowitz, A Selbst
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
1292022
An Institutional View of Algorithmic Impact Assessments
AD Selbst
Harvard Journal of Law & Technology 35 (1), 2021
892021
Contextual Expectations of Privacy
AD Selbst
Cardozo Law Review 35, 643-709, 2013
612013
Unfair Artificial Intelligence: How FTC Intervention Can Overcome the Limitations of Discrimination Law
AD Selbst, S Barocas
University of Pennsylvania Law Review 171, 1023-1093, 2023
162023
A Mild Defense of Our New Machine Overlords
AD Selbst
Vanderbilt Law Review En Banc 70, 87-104, 2017
142017
Deconstructing design decisions: Why courts must interrogate machine learning and other technologies
AD Selbst, S Venkatasubramanian, IE Kumar
Ohio State Law Journal, 23-22, 2024
6*2024
The Journalism Ratings Board: An Incentive-Based Approach to Cable News Accountability
A Selbst
U. Mich. JL Reform 44, 467, 2010
52010
Clock division as a power saving strategy in a system constrained by high transmission frequency and low data rate
AD Selbst
Massachusetts Institute of Technology, 2005
42005
Angwin, Julia ua: Machine Bias. There’s software used across the country to predict future criminals. And it’s biased against blacks, ProPublica 2016, abrufbar unter:< www …
W Aspray, S Barocas, AD Selbst, AM Barry-Jester, B Casselman, ...
LAW & TECHNOLOGY
D Karshtedt, MA Lemley, SB Seymore, AD Selbst, CYN Smith
HARVARD JOURNAL OF LAW & TECHNOLOGY
D Karshtedt, MA Lemley, SB Seymore, AD Selbst, CYN Smith
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