On privacy and machine unlearning: A discussion with Jevan Hutson
A conversation on what unlearning techniques are available and how they can add to the tool belts of practitioners and regulators alike.
Published
Contributors:
Jedidiah Bracy
Editorial Director
IAPP
It's no secret that large language models and artificial intelligence systems require massive amounts of data, which often run up against fundamental privacy principles like purpose limitation and data minimization. Privacy and data protection laws — like the EU General Data Protection Regulation — feature concepts like the right to be forgotten and data subject access requests. But these are often in tension with modern AI systems.
Some tools, however, are emerging. One of those methods is "machine unlearning," a suite of approaches to help remedy deletion requests of information that has already been used to train an AI model.
University of Washington Technology Law and Public Policy Clinic Director and acting Assistant Professor Jevan Hutson, AIGP, CIPP/A, CIPP/E, CIPP/US, CIPM, CIPT, FIP, recently co-wrote a law review article on machine unlearning and its implications for privacy law.
In this episode, Hutson discusses with IAPP Editorial Director Jedidiah Bracy the concept of machine unlearning and how its suite of techniques can add to the tool belts of practitioners and regulators alike.
Some tools, however, are emerging. One of those methods is "machine unlearning," a suite of approaches to help remedy deletion requests of information that has already been used to train an AI model.
University of Washington Technology Law and Public Policy Clinic Director and acting Assistant Professor Jevan Hutson, AIGP, CIPP/A, CIPP/E, CIPP/US, CIPM, CIPT, FIP, recently co-wrote a law review article on machine unlearning and its implications for privacy law.
In this episode, Hutson discusses with IAPP Editorial Director Jedidiah Bracy the concept of machine unlearning and how its suite of techniques can add to the tool belts of practitioners and regulators alike.
This content is eligible for Continuing Professional Education credits. Please self-submit according to CPE policy guidelines.
Submit for CPEsContributors:
Jedidiah Bracy
Editorial Director
IAPP
