The National Science Foundation Division of Computer and Network Systems awarded Massachusetts Institute of Technology $417,261 on January 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to conduct empirical research on the downstream implications of privacy-preserving analytics development and deployment.
The project investigates the organizational, managerial, and real-world impacts of mathematical and statistical techniques—including differential privacy and federated learning—designed to protect privacy while permitting data analysis. The research bridges theoretical computer science and social science by studying how privacy-preserving analytics affect consumer products, research efforts, and policy-making across multiple use cases. Deliverables include empirical studies of organizational considerations behind these tools' development and assessments of their performance in practical applications, intended to provide policy makers and organizations with lessons learned and generalizable best practices for privacy-preserving analytics deployment.
Performance occurs in Cambridge, Massachusetts, with an ultimate completion date of October 31, 2027.