A. Feder Cooper

Microsoft Research

Postdoctoral Researcher

New York, NY

Stanford University

Postdoctoral Affiliate

269 Campus Dr.

Yale University

Assistant Professor of Computer Science (starting 2026)

493 College St

New Haven, CT CT 06520

United States

SCHOLARLY PAPERS

10

DOWNLOADS
Rank 15,956

SSRN RANKINGS

Top 15,956

in Total Papers Downloads

6,207

TOTAL CITATIONS

15

Scholarly Papers (10)

1.

Talkin’ ‘Bout AI Generation: Copyright and the Generative-AI Supply Chain

Forthcoming, Journal of the Copyright Society 2024
Number of pages: 149 Posted: 01 Aug 2023 Last Revised: 04 Mar 2024
Cornell University - Department of Computer Science, Microsoft Research and Cornell Law SchoolCornell Tech
Downloads 3,444 (6,900)
Citation 7

Abstract:

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copyright, generative AI

2.

Report of the 1st Workshop on Generative AI and Law

Yale Law & Economics Research Paper
Number of pages: 39 Posted: 30 Nov 2023 Last Revised: 20 Feb 2024
Microsoft Research, Cornell University - Department of Computer Science, Cornell Law SchoolCornell Tech, Carnegie Mellon University, University of Pennsylvania - Department of Computer and Information Science, Google DeepMind, University of Washington - Paul G. Allen School of Computer Science & Engineering, affiliation not provided to SSRN, Cornell University, Ithaca, New York, Cornell University, Yale University - Law School, Google DeepMind, Cornell University - Department of Computer Science, Cambridge, Anthropic, Google, University of Sussex, Independent, University of Michigan, University of California, Davis - School of Law, University of Waterloo - David R Cheriton School of Computer Science, Stanford Law School, Microsoft Corporation, OpenAI, Electronic Frontier Foundation (EFF), Google DeepMind, Georgetown University Law Center, Google DeepMind, OpenAI, University of California, Berkeley - School of Law, Independent, Department of Electrical and Computer Engineering, University California, San Diego, Tidelift, Yeshiva University - Benjamin N. Cardozo School of Law and University of Nebraska Schools of Law and Engineering
Downloads 886 (54,334)

Abstract:

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Generative AI, law, copyright, privacy, intellectual property

3.

AI and Law: The Next Generation

Number of pages: 21 Posted: 19 Oct 2023
Cornell University - Department of Computer Science, Microsoft Research, Cornell Law SchoolCornell Tech and Carnegie Mellon University
Downloads 642 (82,732)
Citation 2

Abstract:

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generative AI, copyright

4.

The Files are in the Computer: On Copyright, Memorization, and Generative AI

Cornell Legal Studies Research Paper Forthcoming, Chicago-Kent Law Review, Forthcoming
Number of pages: 75 Posted: 22 Jul 2024
A. Feder Cooper, James Grimmelmann and James Grimmelmann
Microsoft Research and Cornell Law SchoolCornell Tech
Downloads 543 (102,238)

Abstract:

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copyright, generative AI, memorization

5.

Regulating Accuracy-Efficiency Trade-Offs in Distributed Machine Learning Systems

Number of pages: 13 Posted: 13 Aug 2020 Last Revised: 10 Mar 2021
A. Feder Cooper, Karen Levy and Christopher De Sa
Microsoft Research, Cornell University and Cornell University - Department of Computer Science
Downloads 190 (313,471)
Citation 4

Abstract:

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machine learning systems, law

6.

Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain (The Short Version)

3rd ACM Symposium on Computer Science and Law 48 (2024)
Number of pages: 16 Posted: 17 Apr 2024
Cornell University - Department of Computer Science, Microsoft Research and Cornell Law SchoolCornell Tech
Downloads 170 (346,185)

Abstract:

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copyright, generative AI

7.

Fast or Accurate? Governing Conflicting Goals in Highly Autonomous Vehicles

20 Colorado Technology Law Journal 249 (2022)
Number of pages: 29 Posted: 06 Aug 2022
A. Feder Cooper and Karen Levy
Microsoft Research and Cornell University
Downloads 136 (415,762)
Citation 2

Abstract:

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automation, efficiency, autonomous vehicles, speed, governance, artificial intelligence, AI, regulation

8.

Non-Determinism and the Lawlessness of Machine Learning Code

Number of pages: 9 Posted: 16 Sep 2024
A. Feder Cooper, Jonathan Frankle and Christopher De Sa
Microsoft Research, Cambridge and Cornell University - Department of Computer Science
Downloads 69 (650,797)

Abstract:

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machine learning, non-determinism, stochasticity, arbitrariness

9.

Between Randomness and Arbitrariness: Some Lessons for Reliable Machine Learning at Scale (The Short Version)

Number of pages: 22 Posted: 17 Jun 2024
A. Feder Cooper
Microsoft Research
Downloads 64 (675,775)

Abstract:

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10.

Between Randomness and Arbitrariness: Some Lessons for Reliable Machine Learning at Scale

Number of pages: 360 Posted: 12 Sep 2024
A. Feder Cooper
Microsoft Research
Downloads 63 (680,996)

Abstract:

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machine learning, law and policy, artificial intelligence