Abstract
Algorithmic disgorgement, also known as algorithmic destruction or model destruction, is the ordered deletion of computer data models or algorithms that were developed with improperly obtained data. It is a relatively new remedy that the Federal Trade Commission (FTC) has used several times since 2019 under its broad authority to “order relief reasonably tailored to the violation of the law.” Historically, FTC commissioners have “voted to allow data protection law violators to retain algorithms and technologies that derive much of their value from ill-gotten data,” with the remedy for violating data collection laws being only the deletion of the data itself and possible monetary fines. However, in what former FTC Commissioner Rohit Chopra called an “important course correction,” the FTC has recently begun to require algorithmic disgorgement in its settlements—that is, the deletion of not just the improperly obtained data itself, but any models and algorithms built using such data.
Last Page
51
Recommended Citation
Joshua A. Goland,
Algorithmic Disgorgement: Destruction of Artificial Intelligence Models as the FTC's Newest Enforcement Tool for Bad Data,
29
Rich. J.L. & Tech
1
(2024).
Available at:
https://scholarship.richmond.edu/jolt/vol29/iss2/1