Implications for Governance in Public Perceptions of Societal-scale AI Risks
Ross Gruetzemacher, Toby D. Pilditch, Huigang Liang, Christy Manning,, Vael Gates, David Moss, James W. B. Elsey, Willem W. A. Sleegers, and Kyle, Kilian

TL;DR
This study compares perceptions of AI risks between experts and US voters, revealing differences in perceived likelihood and impact, and suggests policy approaches for better risk mitigation and consensus building.
Contribution
It provides empirical data on societal perceptions of AI risks and policy preferences, highlighting gaps between expert and public views and proposing balanced mitigation strategies.
Findings
Voters perceive AI risks as more likely and impactful than experts.
Both groups favor international oversight over national or corporate governance.
Policy interventions should balance mitigation efforts across all societal-scale risks.
Abstract
Amid growing concerns over AI's societal risks--ranging from civilizational collapse to misinformation and systemic bias--this study explores the perceptions of AI experts and the general US registered voters on the likelihood and impact of 18 specific AI risks, alongside their policy preferences for managing these risks. While both groups favor international oversight over national or corporate governance, our survey reveals a discrepancy: voters perceive AI risks as both more likely and more impactful than experts, and also advocate for slower AI development. Specifically, our findings indicate that policy interventions may best assuage collective concerns if they attempt to more carefully balance mitigation efforts across all classes of societal-scale risks, effectively nullifying the near-vs-long-term debate over AI risks. More broadly, our results will serve not only to enable more…
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Taxonomy
TopicsEthics and Social Impacts of AI · Innovation, Sustainability, Human-Machine Systems
