As artificial intelligence (AI) policy has begun to take shape in recent years, policy actors have worked to influence policymakers by strategically promoting issue frames that define the problems and solutions policymakers should attend to. Three such issue frames are especially prominent, surrounding AI’s economic, geopolitical, and ethical dimensions. Relatedly, while technology policy is traditionally expert-dominated, new governance paradigms are encouraging increased public participation along with heightened attention to social and ethical dimensions of technology. This study aims to provide insight into whether members of the public and the issue frames they employ shape—or fail to shape—policymaker agendas, particularly for highly contested and technical policy domains. To assess this question, the study draws on a dataset of approximately five million Twitter messages from members of the public related to AI, as well as corresponding AI messages from the 115th and 116th US Congresses. After using text analysis techniques to identify the prevalence of issue frames, the study applies autoregressive integrated moving average and vector autoregression modeling to determine whether issue frames used by the public appear to influence the subsequent messaging used by federal US policymakers. Results indicate that the public does lead policymaker attention to AI generally. However, the public does not have a special role in shaping attention to ethical implications of AI, as public influence occurs only when the public discusses AI’s economic dimensions. Overall, the results suggest that calls for public engagement in AI policy may be underrealized and potentially circumscribed by strategic considerations.

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框架争论和公众对政策制定者的影响：来自美国人工智能政策话语的证据

近年来，随着人工智能（AI）政策开始形成，政策制定者一直致力于通过战略性地推动定义政策制定者应关注的问题和解决方案的问题框架来影响政策制定者。围绕人工智能的经济、地缘政治和道德维度的三个此类问题框架尤其突出。与此相关的是，虽然技术政策传统上是专家主导的，但新的治理范式正在鼓励公众更多参与，同时更加关注技术的社会和道德层面。本研究旨在深入了解公众成员及其采用的问题框架是否塑造（或未能塑造）政策制定者议程，特别是在竞争激烈的技术性政策领域。为了评估这个问题，该研究利用了大约 500 万条与人工智能相关的公众 Twitter 消息以及来自第 115 届和第 116 届美国国会的相应人工智能消息的数据集。在使用文本分析技术确定问题框架的普遍性后，该研究应用自回归综合移动平均和向量自回归模型来确定公众使用的问题框架是否会影响美国联邦政策制定者随后使用的消息传递。结果表明，公众确实普遍引导政策制定者关注人工智能。然而，公众在关注人工智能的伦理影响方面并没有发挥特殊作用，因为只有当公众讨论人工智能的经济维度时，公众影响力才会产生。总体而言，结果表明，公众参与人工智能政策的呼吁可能没有得到充分认识，并且可能受到战略考虑的限制。