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.
NIST’s guidance on “Managing Misuse Risk for Dual-Use Foundation Models” represents a significant step forward in establishing robust practices for mitigating catastrophic risks associated with advanced AI systems.
Surveillance has been used on citizen activists for decades. What can civil society do to fight back against the growing trend of widespread digital surveillance?
Public-private collaboration in standards development also increases the likelihood that companies are able to adopt the standards without being overly burdened.
To understand the range of governmental priorities for the bioeconomy, we spoke with key agencies represented on the National Bioeconomy Board to collect their perspectives.