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Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse
Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse
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Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse
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Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse
Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse

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Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse
Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse
Journal Article

Framing contestation and public influence on policymakers: evidence from US artificial intelligence policy discourse

2024
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Overview
Abstract 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.