Narratives and expert information in agenda‐setting: Experimental evidence on state legislator engagement with artificial intelligence policy

立法者 叙述的 公共关系 政治学 奖学金 框架(结构) 公共行政 法学 立法 工程类 语言学 结构工程 哲学
作者
Daniel Schiff,Kaylyn Jackson Schiff
出处
期刊:Policy Studies Journal [Wiley]
卷期号:51 (4): 817-842 被引量:14
标识
DOI:10.1111/psj.12511
摘要

Abstract 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.
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