A National AI for Good Initiative

Authors: Anna Mitchell, Jasmine Sun, Jonathan Mak, and Nick Rose


Artificial intelligence (AI) and machine learning (ML) models can solve well-specified problems, like automatically diagnosing disease or grading student essays, at scale. But applications of AI and ML for major social and scientific problems are often constrained by a lack of high-quality, publicly available data—the foundation on which AI and ML algorithms are built.

The Biden-Harris Administration should launch a multi-agency initiative to coordinate the academic, industry, and government research community to support the identification and development of datasets for applications of AI and ML in domain-specific, societally valuable contexts. The initiative would include activities like generating ideas for high-impact datasets, linking siloed data into larger and more useful datasets, making existing datasets easier to access, funding the creation of real-world testbeds for societally valuable AI and ML applications, and supporting public-private partnerships related to all of the above.

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About the Authors

Anna Mitchell is a Senior Associate Product Manager at Schmidt Futures, where she works on projects related to advancing and protecting free societies using technology. Her writing has been published by The Atlantic and Stanford Law School as well as the Stanford Review, where she was Editor-in-Chief. Anna holds a B.S. in computer science with a concentration in artificial intelligence from Stanford University.

Jasmine Sun is a Research Intern at Schmidt Futures and a fourth-year undergraduate at Stanford University. She has led curricula and instruction for multiple Stanford computer-science courses in civic technology and has previously worked at Bridgewater Associates, One