Artificial Intelligence in 2024: A Thematic Analysis of Media Coverage

Abstract

This thesis investigates how three agenda-setting U.S. newspapers — The New York Times, The Wall Street Journal, and The Washington Post — framed artificial intelligence (AI) during the year 2024. Using an inductive thematic analysis grounded in Braun and Clarke's six-phase procedure, 300 randomly-selected articles (100 per outlet) were analyzed and interpreted as media frames. Eight dominant frames emerged: AI Boom vs. Bubble, Misuse and Misinformation, Ethical and Moral Challenges, Policy and Governance, Societal and Cultural Impact, Work and Automation, Environmental Impact, and Technological Advancements and Future Risks. Across coverage, fear narratives centered on disinformation, job displacement, algorithmic bias, environmental costs, and existential risk. Results suggest that U.S. legacy media have moved beyond early techno-optimism towards a more nuanced discourse that simultaneously fuels investment and adoption, demands regulation and safeguards, and shapes public perception. These findings document how narratives evolve in response to rapid technological change and provide information for scholars, policymakers, and technologists seeking to understand how media discourse may steer AI governance and adoption.