Ram Shankar Siva Kumar

Microsoft Corporation

One Microsoft Way

Redmond, WA 98052

United States

Harvard University - Berkman Klein Center for Internet & Society

Harvard Law School

23 Everett, 2nd Floor

Cambridge, MA 02138

United States

SCHOLARLY PAPERS

5

DOWNLOADS

330

SSRN CITATIONS

2

CROSSREF CITATIONS

1

Scholarly Papers (5)

1.

Legal Risks of Adversarial Machine Learning Research

International Conference on Machine Learning (ICML) 2020 Workshop on Law & Machine Learning
Number of pages: 14 Posted: 29 Jul 2020
Ram Shankar Siva Kumar, Jon Penney, Bruce Schneier and Kendra Albert
Microsoft Corporation, , Harvard University - Berkman Klein Center for Internet & Society and Harvard Law School
Downloads 107 (307,591)

Abstract:

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Adversarial machine learning, security, machine learning, artificial intelligence, law, AI, computer fraud and abuse act, CFAA, legal risks, chilling effects, ML

2.

Adversarial Machine Learning - Industry Perspectives

Number of pages: 7 Posted: 06 Mar 2020
Microsoft Corporation, Microsoft Corporation, Microsoft Corporation, Microsoft Corporation, Microsoft Corporation, Microsoft Corporation, Microsoft Corporation and Microsoft Corporation
Downloads 99 (323,926)
Citation 3

Abstract:

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Machine Learning, Security, Adversarial Machine Learning

3.

Politics of Adversarial Machine Learning

Towards Trustworthy ML: Rethinking Security and Privacy for ML Workshop, Eighth International Conference on Learning Representations (ICLR) 2020
Number of pages: 6 Posted: 27 Mar 2020 Last Revised: 11 May 2020
Kendra Albert, Jon Penney, Bruce Schneier and Ram Shankar Siva Kumar
Harvard Law School, , Harvard University - Berkman Klein Center for Internet & Society and Microsoft Corporation
Downloads 86 (353,883)

Abstract:

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Artificial Intelligence, AI, Machine Learning, Ml, Security, Socio-Technical Systems, Adversarial Machine Learning, Privacy, Security, Human Rights, Spyware, Politics of Technology, Politics of Machine Learning

4.

Ethical Testing in the Real World: Evaluating Physical Testing of Adversarial Machine Learning

Workshop on Dataset Curation and Security // Workshop on Navigating the Broader Impacts of AI Research -- Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS 2020)
Number of pages: 8 Posted: 05 Feb 2021
Kendra Albert, Maggie Delano, Jon Penney, Afsaneh Rigot and Ram Shankar Siva Kumar
Harvard Law School, Engineering Department, Swarthmore College, , ARTICLE 19 and Microsoft Corporation
Downloads 26 (587,610)
Citation 1

Abstract:

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Artificial Intelligence, AI, Machine Learning, ML Adversarial Machine Learning, Ethics, Physical Testing, Physical Domain, Methodology, ML attacks, FRT, Facial Recognition Technology, Invisibility, Algorithms, Research Ethics, Design, Security, Privacy, Human Rights

5.

Reflecting on Paradise Lost via Reinforcement Learning and Resistance AI Literature

Resistance AI Workshop at NeurIPS 2020 Conference - https://sites.google.com/view/resistance-ai-neurips-20/home
Number of pages: 5 Posted: 18 Feb 2021
Ram Shankar Siva Kumar
Microsoft Corporation
Downloads 12 (685,964)

Abstract:

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John Milton, Artificial Intelligence, Machine Learning, Paradise Lost