In August, Meta, formerly known as Facebook, launched the Building Tools to Enhance Transparency in Fairness and Privacy request for proposals (RFP). Today, we’re announcing the winners of this award.
Through this RFP, we hope to support academics in building the trusted tools to more effectively monitor systems that help spot concerns in fairness, privacy, and safety.
“Improving fairness and privacy across the internet is an ambitious goal, and one that requires a consistent investment in new ideas and researchers who can bring them to life,” said Will Bullock, Meta Statistics and Privacy Director. “We’re excited to support these leading scholars, and eagerly anticipate their breakthroughs in the years to come."
The RFP attracted 50 proposals from 40 universities and institutions around the world. Thank you to everyone who took the time to submit a proposal, and congratulations to the winners.
Principal investigators are listed first unless otherwise noted.
A tool to study the efficacy of fairness algorithms on specific bias types
Hoda Heidari, Haiyi Zhu, Steven Wu (Carnegie Mellon University)
Analyzing the accuracy, transparency and privacy of profiling algorithms
Ruben Cuevas Rumin, Angel Cuevas Rumin, Patricia Callejo Pinardo, Pelayo Vallina Rodriguez (University Carlos III de Madrid)
Comprehensive privacy auditing in machine learning
Reza Shokri, Vincent Bindschaedler (National University of Singapore)
Galaxy: a library for safeguarding deep neural networks against unknowns
Sharon Li (University of Wisconsin–Madison)
High-confidence long-term safety and fairness guarantees
Philip Thomas, Yuriy Brun (University of Massachusetts Amherst)
Towards ML governance with accountability and auditing
Nicolas Papernot (University of Toronto)