Mismatch between warning information and protective behavior: Why experts + AI < 2?
Qi Bian, Leyu Wang, Luning Xin, Ben Ma
Shandong University
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摘要与影响
Warning information plays a vital role in encouraging disaster preparedness among residents. Using survey experiment data from 619 respondents in China, this study examines how warning messages from AI, experts, and a combination of the two influence public disaster preparedness behaviors and whether the degree of impact differs between these sources. The findings reveal that warnings from AI, experts, and a combination of those two sources significantly affect disaster preparedness behaviors. Notably, and contrary to conventional expectations, the combined warnings from AI and experts do not result in a mutually strengthening effect. Instead, a crowding-out effect is observed, whereby the combined impact is less than the sum of individual effects ("Experts + AI < 2"). This outcome can be attributed to information fatigue, suggesting that information overload does not always benefit the public but instead often becomes a burden. Additionally, the influence of AI-driven warnings on preparedness varies substantially with respondents' educational levels. The insights provided by this study hold practical implications for government agencies in promoting public disaster preparedness.
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学术脉络
学科主题
社会科学Disaster Management and Resilience
Public Relations and Crisis Communication · Evacuation and Crowd Dynamics
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