Design Choices: Mechanism Design and Platform Capitalism (currently under review)
Traces the disciplinary drift of mechanism design from social welfare economics, where it was developed to address social coordination and problems of social cost, into algorithmic platform settings, where it is used to reiteratively tune and optimize platform settings for exchange. Argues this disciplinary drift lends insight into the normative contradictions and tensions at the heart of this method’s use in online settings.
– Accepted to the 2020 Privacy Law Scholars Workshop.
– Accepted for oral presentation at the 2020 Workshop on Mechanism Design for Social Good.
The Promise and Limits of Lawfulness: Inequality, Law, and the Techlash (currently under review)
Argues for more sophisticated understanding of the relationship between law and legitimacy in current calls for regulation from the AI Ethics community, which posits law as a more robust alternative to non-legal ethical responses. Like non-regulatory ethics responses, legal solutions may undermine or express the demands of justice that motivate their implementation. Law, like ethics, is a terrain of contestation, upon which the degree and substance of new forms of discipline for the technology industry may be determined.
– Accepted for presentation at the Inaugural 2020 Law and Political Economy Conference (delayed due to Covid-19).
Democratic Data: A Relational Theory For Data Governance, Yale Law Journal (Forthcoming in Vol 131)
Data Market Discipline: From Financial Regulation to Data Governance, Journal of International and Comparative Law (Forthcoming 2021) (with S. Benthall)
Algorithmic Realism: Expanding the Boundaries of Algorithmic Thought, ACM Conference on Fairness, Accountability, and Transparency (ACM FAT*) (2020) (with B. Green)
– Note on venue: in computer science, conferences are the primary publishing venues. These papers undergo double-blind peer review and are published within conference proceedings as full papers equivalent to journal publications other fields.
PDF | Publisher’s Version
Law and Adversarial Machine Learning, Conference on Neural Information Processing Systems 2018, Workshop on Security in Machine Learning (NeurIPS) (2018) (with R. Shankar, D. O’Brien, and K. Albert).
– Accepted for oral presentation.
PDF | arXiv
“Data Relations,” Logic Magazine, Issue 13: Distribution, May 2021.
“Ferment is Abroad: Techlash, Legal Institutions, and the Limits of Lawfulness,” LPE Blog, April 20, 2021.
“Data Governance for a Society of Equals” LPE Blog, March 22, 2021.
“Data as Property?” Phenomenal World, Jain Family Institute, October 16, 2020.
“Privacy vs. Health is a False Trade off,” Jacobin, April 17, 2020.
“The Promise and Pitfalls of the California Consumer Privacy Act,” Critical Reflections, Cornell Tech, April 11, 2020.
“Facebook’s Surveillance is Nothing Compared with Comcast, AT&T, and Verizon” The Guardian, April 6, 2018.