Alondra Nelson

Policy-makers around the world are grappling with how to govern increasingly powerful artificial intelligence (AI) technology. Some jurisdictions, like the European Union (EU), have made substantial progress enacting regulations to promote responsible AI. Others, like the administration of US President Donald Trump, have prioritized “enhancing America’s dominance in AI.” Although these approaches appear to diverge in their fundamental values and objectives, they share a crucial commonality: Effectively steering outcomes for and through AI will require thoughtful, evidence-based policy development (1). Though it may seem self-evident that evidence should inform policy, this is far from inevitable in the inherently messy policy process. As a multidisciplinary group of experts on AI policy, we put forward a vision for evidence-based AI policy, aimed at addressing three core questions: (i) How should evidence inform AI policy? (ii) What is the current state of evidence? (iii) How can policy accelerate evidence generation?

Response of the AI Policy and Governance Working Group to the Envoy on Technology Call for Papers on Global AI Governance. The AI Policy and Governance Working Group, convened by the Institute for Advanced Study, submits this white paper in response to the United Nations Secretary-General’s Envoy on Technology’s Call for Papers on Global AI Governance.

Comment of the AI Policy and Governance Working Group on the NTIA Request for Comment on Dual Use Foundation Artificial Intelligence Models with Widely Available Model Weights Docket NTIA-240216-0052 The AI Policy and Governance Working Group recommends that the Biden-Harris Administration call for the development of a range of practical approaches to open foundation model release with accompanying case studies and pilot studies developed with relevant stakeholders.

Comment of the AI Policy and Governance Working Group on the NTIA AI Accountability Policy Request for Comment Docket NTIA-230407-0093 In response to the National Telecommunications and Information Administration’s (NTIA) request for comment on AI accountability policy, the AI Policy and Governance Working Group here provides 1) overarching considerations, both to offer context for our specific recommendations and to help inform federal AI policy strategy, and 2) recommendations for sociotechnical AI accountability mechanisms based on evaluation, access, and disclosure that can begin to build justified public trust in AI as an essential predicate to adequately and effectively “aligning” these technological systems and tools with democratic and human values.