Can AI Protect Privacy and Still Explain Its Decisions?

When we train models on sensitive data, we often ask how much accuracy we lose by protecting privacy. But what happens to the explanations? This is the question behind our new paper, Pushing the (Decision) Boundaries, with Michael Khavkin and

New paper: Self-Defeating Privacy: Privacy Coins as a Blockchain Liability

We are happy to share that our paper, “Self-Defeating Privacy: Privacy Coins as a Blockchain Liability,” by Danielle Movsowitz Davidow and Eran Toch, has been accepted as a short paper to the 25th Workshop on Privacy in the Electronic Society