Social Science

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?