Researchers discover that privacy-preserving tools leave private data anything but

BROOKLYN, New York, Wednesday, March 3, 2021 - Machine-learning (ML) systems are becoming pervasive not only in technologies affecting our day-to-day lives, but also in those observing them, including face expression recognition systems. Companies that make and use such widely deployed services rely on so-called privacy preservation tools that often use generative adversarial networks (GANs), typically produced by a third party to scrub images of individuals' identity. But how good are they?

Researchers at the END