Grants

Open Collective Foundation

To develop open-source software that facilitates widespread adoption of privacy-preserving methods in artificial intelligence

  • Amount $648,000
  • City Walnut, CA
  • Investigator Andrew Trask
  • Initiative Economic Analysis of Science and Technology (EAST)
  • Year 2021
  • Program Research
  • Sub-program Economic Institutions, Behavior, & Performance

Funds from this grant provide support for OpenMined, an online community of nearly 12,000 members from academia, industry, and government devoted to advancing privacy-preserving research methods in machine learning and AI development.   The OpenMined community is creating an ecosystem of advanced but accessible cryptographic tools designed to allow machine learning researchers to probe sensitive datasets without the need to copy, move or share any data.  Resources available on the OpenMined website (OpenMined.org) include a beginner’s guide, free classes and tutorials in a dozen languages, blogs and lectures from leading researchers in privacy-preserving research, and open-source coding repositories and projects on such topics as remote execution and federated learning, differential privacy, encrypted computation, and secure natural language processing.  Grant funds provide core operating support for the continued operation and expansion of the OpenMined community for a period of two years.

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