Chapter 9: AI bias, news framing, and mixed-methods approach
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Media frame often affects public attitudes toward an emerging scientific field and technology. Bias, which refers to the unfair outcomes based on demographic features, has become the focus of news coverage of artificial intelligence (AI). To understand how AI bias was framed and whether media differed in their framing strategy, this study employs the inductive mixed-method computational approach (ANMTN) proposed by Walter and Ophir (2019) to systematically analyze the news transcripts on AI fairness published by six major television networks in the United States in the past three decades (ABC, CBS, CNN, Fox News, MSNBC, and NBC). The study identifies three dominant frames: benefit and risk, conflict and regulation, and digital journalism. Results show that the conflict and regulation frame becomes the dominant frame in the news coverage after “competing” with the benefit and risk frame in the early stage. Moreover, television networks demonstrate drastically different framing patterns across the three decades. Future directions of media framing research on AI are discussed.

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