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.
It is in the interests of the United States to appropriately protect information that needs to be protected while maintaining our participation in new discoveries to maintain our competitive advantage.
Our analysis of federal AI governance across administrations shows that divergent compliance procedures and uneven institutional capacity challenge the government’s ability to deploy AI in ways that uphold public trust.
To secure the U.S. bio-infrastructure, maintain global leadership in biotechnology, and safeguard American citizens from emerging threats to their privacy, the federal government must modernize its approach to human genetic and biological data.
From use to testing to deployment, the scaffolding for responsible integration of AI into high-risk use cases is just not there.