Local US officials' views on the impacts and governance of AI: Evidence from 2022 and 2023 survey waves

TL;DR

This study surveys US local policymakers' evolving views on AI's societal impacts and regulation, revealing mixed attitudes, partisan differences, and a need for capacity-building to shape cohesive AI governance.

Contribution

It provides new insights into local policymakers' changing perspectives on AI impacts and regulation post-2022, highlighting partisan shifts and policy implications.

Findings

Policymakers anticipate societal risks like surveillance and misinformation.

Majority support government regulation on AI issues.

Partisan support for AI regulation increased among Republicans from 2022 to 2023.

Abstract

This paper presents a survey of local US policymakers' views on the future impact and regulation of AI. Our survey provides insight into US policymakers' expectations regarding the effects of AI on local communities and the nation, as well as their attitudes towards specific regulatory policies. Conducted in two waves (2022 and 2023), the survey captures changes in attitudes following the release of ChatGPT and the subsequent surge in public awareness of AI. Local policymakers express a mix of concern, optimism, and uncertainty about AI's impacts, anticipating significant societal risks such as increased surveillance, misinformation, and political polarization, alongside potential benefits in innovation and infrastructure. Many also report feeling underprepared and inadequately informed to make AI-related decisions. On regulation, a majority of policymakers support government oversight and favor specific policies addressing issues such as data privacy, AI-related unemployment, and AI safety and fairness. Democrats show stronger and more consistent support for regulation than Republicans, but the latter experienced a notable shift towards majority support between 2022 and 2023. Our study contributes to understanding the perspectives of local policymakers-key players in shaping state and federal AI legislation-by capturing evolving attitudes, partisan dynamics, and their implications for policy formation. The findings highlight the need for capacity-building initiatives and bi-partisan coordination to mitigate policy fragmentation and build a cohesive framework for AI governance in the US.