Algorithmic Disgorgement: Destruction of Artificial Intelligence Models as the FTC's Newest Enforcement Tool for Bad Data

51 Pages Posted: 14 Mar 2023

See all articles by Joshua A. Goland

Joshua A. Goland

University of Virginia School of Law

Date Written: March 1, 2023

Abstract

The Federal Trade Commission has recently begun to require algorithmic disgorgement in its enforcement of data protection laws – the deletion of not just the improperly obtained data itself, but artificial intelligence models and algorithms built using such data. This Article provides a brief overview of machine learning models and algorithms and the basic function and use of artificial intelligence and describes the FTC’s role in the regulation and enforcement of data collection rules. It then discusses recent enforcement actions brought by the FTC that utilized algorithmic disgorgement, analyzes the legality of the FTC’s authority to order destruction of computer data models and algorithms, and discusses the likelihood and possibility of future use of the new remedy, as well as the shape that any future use is likely to take. Finally, it deliberates on the legal, policy, and practical implications of algorithmic disgorgement and proposes some possible alternatives to and restraints on the FTC’s use of algorithmic destruction orders.

Keywords: Algorithmic disgorgement, artificial intelligence, AI, model destruction, machine learning, data protection, data collection, data privacy, FTC

Suggested Citation

Goland, Joshua A., Algorithmic Disgorgement: Destruction of Artificial Intelligence Models as the FTC's Newest Enforcement Tool for Bad Data (March 1, 2023). Richmond Journal of Law and Technology, Vol. XXIX, Issue 2 (2023), Available at SSRN: https://ssrn.com/abstract=4382254 or http://dx.doi.org/10.2139/ssrn.4382254

Joshua A. Goland (Contact Author)

University of Virginia School of Law ( email )

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