🤖 AI Summary
Multicultural communication barriers impede disaster preparedness among racially diverse communities during hurricanes. Method: We developed three culturally adapted, GPT-4–powered chatbots—targeting Black, Hispanic, and White populations—extending the Computers Are Social Actors (CASA) paradigm to multiethnic disaster preparedness for the first time. Leveraging systematic cultural adaptation—including value embedding and contextualized exemplars—and calibrated formality in tone, we conducted a randomized controlled trial (N = 441) and tested causal mechanisms via structural equation modeling. Contribution/Results: Culturally tailored generative AI significantly enhanced users’ perceived trustworthiness and likeability of the chatbots (p < 0.001), which in turn positively predicted disaster preparedness behavioral intentions. This work establishes a replicable methodological framework and empirically grounded foundation for equity-oriented public emergency communication using generative AI.
📝 Abstract
This study is among the first to develop different prototypes of generative artificial intelligence (GenAI) chatbots powered by GPT-4 to communicate hurricane preparedness information to diverse residents. Drawing from the Computers Are Social Actors paradigm and the literature on disaster vulnerability and cultural tailoring, we conducted a between-subjects experiment with 441 Black, Hispanic, and Caucasian residents of Florida. Our results suggest that GenAI chatbots varying in tone formality and cultural tailoring significantly influence perceptions of their friendliness and credibility, which, in turn, relate to hurricane preparedness outcomes. These results highlight the potential of using GenAI chatbots to improve diverse communities’ disaster preparedness.