Framing AI: A Content Analysis of Election-Year News Coverage

• In Event: Emerging Challenges to Digital Campaigning

Abstract

It is widely recognized that public perceptions of scientific advances and emerging technologies like artificial intelligence (AI) are shaped by news coverage of the issue. By choosing to emphasize or exclude specific aspects of AI in news coverage, the news media play a critical role in providing meaning and guiding how the public thinks about and understands the new technology – a phenomenon known as the framing effect. In this study, we conduct a content analysis of AI-related news coverage, focusing on how the news media frames AI-related risks and how this coverage varies over time. We compare coverage of AI-related risks in national newspapers (e.g., the Washington Post; the New York Times) to coverage in specialty publications (e.g., Wired; TechCrunch), focusing specifically on three types of news frames that have been shown to have a particularly powerful impact on public perceptions of technology: 1) risk vs benefit framing; 2) episodic vs. thematic framing; and 3) societal vs. personal impact framing. These frames are particularly important to understand because they influence perceptions of responsibility for AI-related risks, and therefore shape whether people view AI as an issue that calls for intervention at the policy-level. The results of this content analysis have important implications for understanding how AI is presented to the public and how this presentation may shape public perceptions of AI as a policy-related issue.

Authors

• Caroline Orr Bueno, University of Maryland

• Rhyner Washburn, University of Maryland