A National AI for Good Initiative
Summary
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.
As Congress considers broader packages to advance critical minerals production and supply chain resilience, science diplomacy vehicles must be part of that conversation, not as an afterthought, but as an intentional and foundational pillar of any strategy.
“Structured partnerships with our allies on critical minerals innovation can ensure that the best science and the best talent are working together towards shared security and economic prosperity.”
This is a bipartisan, commonsense measure to reauthorize the Technology Modernization Fund (TMF) before it expires in September 2026.
Many states are introducing AI policies and task forces, but lack the “AI-native” personnel to build and maintain initiatives. To address this in the short term, states should establish AI Resilience Cohorts to embed early-career technologists in key offices to support state AI initiatives. Right now, Virginia and New Jersey have the opportunity to take […]