Kaylyn Jackson Schiff

Law enforcement agencies are increasingly adopting artificial intelligence (AI)‐powered tools. While prior work emphasizes the technological features driving public opinion, we investigate how public trust and support for AI in government vary with the institutional context. We administer a pre‐registered survey experiment to 4200 respondents about AI use cases in policing to measure responsiveness to three key institutional factors: bureaucratic proximity (i.e., local sheriff versus national Federal Bureau of Investigation), algorithmic targets (i.e., public targets via predictive policing versus detecting officer misconduct through automated case review), and agency capacity (i.e., necessary resources and expertise). We find that the public clearly prefers local over national law enforcement use of AI, while reactions to different algorithmic targets are more limited and politicized. However, we find no responsiveness to agency capacity or lack thereof. The findings suggest the need for greater scholarly, practitioner, and public attention to organizational, not only technical, prerequisites for successful government implementation of AI.

Are narratives as influential in gaining the attention of policymakers as expert information, including for complex, technical policy domains such as artificial intelligence (AI) policy? This pre‐registered study uses a field experiment to evaluate legislator responsiveness to policy entrepreneur outreach. In partnership with a leading AI think tank, we send more than 7300 U.S. state legislative offices emails about AI policy containing an influence strategy (providing a narrative, expert information, or the organization's background), along with a prominent issue frame about AI (emphasizing technological competition or ethical implications). To assess engagement, we measure link clicks to further resources and webinar registration and attendance. Although AI policy is a highly technical domain, we find that narratives are just as effective as expert information in engaging legislators. Compared to control, expert information and narratives led to 28 and 34 percent increases in policymaker engagement, respectively. Furthermore, higher legislature professionalism and lower state‐level prior AI experience are associated with greater engagement with both narratives and expert information. Finally, we find that policymakers are equally engaged by an ethical framing of AI policy as they are with an economic one. The findings advance efforts to bridge scholarship on policy narratives, policy entrepreneurship, and agenda‐setting.