Suchergebnisse

We examined initial newspaper coverage of the COVID-19 outbreak (January–May 2020) in the United States and China, countries with contrasting media systems and pandemic experiences. We join the context-rich media systems literature and the longitudinal nature of the issue-attention literature to expand each by providing more system-level context for explaining how media cover an issue over time. U.S. coverage peaked later and stayed consistently high, while Chinese coverage was more variable. The most prominent topics in Chinese coverage were related to domestic outbreak response, while U.S. coverage focused on politics, highlighting how issue-attention cycles differ across countries.

Using data from a nationally representative survey of U.S. adults, this study explores how trust in key actors to responsibly manage artificial intelligence (AI) develops among members of the U.S. population and how trust, along with other key factors, shapes public attitudes toward AI. Greater trust is linked to stronger support for AI, both directly and indirectly (through risk and benefit perceptions). Furthermore, the strength or direction of the link between trust and support—as well as media diets and trust—differs significantly for liberals and conservatives, suggesting that Americans are indeed beginning to process AI-related information through a political lens.

The use of artificial intelligence-based algorithms for the curation of news content by social media platforms like Facebook and Twitter has upended the gatekeeping role long held by traditional news outlets. This has caused some US policymakers to argue that platforms are skewing news diets against them, and such claims are beginning to take hold among some voters. In a nationally representative survey experiment, we explore whether traditional models of media bias perceptions extend to beliefs about algorithmic news bias. We find that partisan cues effectively shape individuals' attitudes about algorithmic news bias but have asymmetrical effects. Specifically, whereas in-group directional partisan cues stimulate bias perceptions for members of both parties, Democrats, but not Republicans, also respond to out-group cues. We conclude with a discussion about the implications for the formation of attitudes about new technologies and the potential for polarization.