This report presents a broad look at the American public’s attitudes toward artificial intelligence (AI) and AI governance, based on findings from a nationally representative survey of 2,000 American adults. As the study of the public opinion toward AI is relatively new, we aimed for breadth over depth, with our questions touching on: workplace automation; attitudes regarding international cooperation; the public’s trust in various actors to develop and regulate AI; views about the importance and likely impact of different AI governance challenges; and historical and cross-national trends in public opinion regarding AI. Our results provide preliminary insights into the character of US public opinion regarding AI.

An interview with Allan Dafoe.

Artificial intelligence (AI) has widespread societal implications, yet social scientists are only beginning to study public attitudes toward the technology. Existing studies find that the public’s trust in institutions can play a major role in shaping the regulation of emerging technologies. Using a large-scale survey (N=2000), we examined Americans’ perceptions of 13 AI governance challenges as well as their trust in governmental, corporate, and multistakeholder institutions to responsibly develop and manage AI. While Americans perceive all of the AI governance issues to be important for tech companies and governments to manage, they have only low to moderate trust in these institutions to manage AI applications.

What resources and technologies are strategic? This question is often the focus of policy and theoretical debates, where the label “strategic” designates those assets that warrant the attention of the highest levels of the state. But these conversations are plagued by analytical confusion, flawed heuristics, and the rhetorical use of “strategic” to advance particular agendas. We aim to improve these conversations through conceptual clarification, introducing a theory based on important rivalrous externalities for which socially optimal behavior will not be produced alone by markets or individual national security entities. We distill and theorize the most important three forms of these externalities, which involve cumulative-, infrastructure-, and dependency strategic logics. We then employ these logics to clarify three important cases: the Avon 2 engine in the 1950s, the U.S.-Japan technology rivalry in the late 1980s, and contemporary conversations about artificial intelligence.