With the support of grants from the National Science Foundation and the Department of Energy, FPF is building a Research Coordination Network (RCN) for Privacy-Preserving Data Sharing and Analytics starting in July 2024 and running through June 2027. The RCN will advance the Biden-Harris Executive Order on Artificial Intelligence by analyzing and promoting the trustworthy adoption of Privacy Enhancing Technologies (PETs) in the context of artificial intelligence (AI) and other key technologies. Our goal is to support the development, deployment, and scaling of PETs in support of socially beneficial data sharing and analytics.
The RCN will convene a multidisciplinary, cross-sector, and international primary network (Expert Group) of scholars and practitioners who use and develop PETs and understand the risks of data sharing and analytics for marginalized and vulnerable groups, civil rights, and civil liberties. A secondary sub-network of high-level regulators worldwide (Regulator Sub-Group) will inform and respond to the primary network, addressing legal frameworks relevant to PETs adoption.
If this sounds like you, let us know. We’re actively recruiting for the Expert and Regulator groups now. Complete the form below.
The RCN will assess and converge on PETs governance as we progress to facilitate national and international data sharing and collaboration for scientific discovery, industry, and trustworthy AI. We will develop and share new guidance to accelerate progress toward a privacy-preserving data-sharing and analytics ecosystem that advances democratic values. This work will be successful when we see broad PETs use via new technology, laws and regulations, standards, or certifications.
The RCN’s specific focus is PETs that support privacy-preserving machine learning and PETs that U.S. Federal agencies may need to support equitable AI uses.
The work of this grant is led by an expert steering committee, which includes:
- John Verdi (PI), FPF
- Jules Polonetsky, FPF
- Marjory Blumenthal, FPF
- Annie Antón, Georgia Tech
- Margaret Hu, William & Mary Law School/Penn State Institute for Computational and Data Sciences Research
- Khaled El Emam, Replica Analytics, University of Ottawa School of Epidemiology/Electronic Health Information Laboratory
- Caroline Louveaux, MasterCard.
More information about the RCN is available here.
The Research Coordination Network (RCN) for Privacy-Preserving Data Sharing and Analytics is supported by the U.S. National Science Foundation under Award #2413978 and the U.S. Department of Energy, Office of Science under Award #DE-SC0024884.
