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The impact of different task contexts on emergency responders' trust and usage intention of artificial intelligence
Xiangying Zou1, Pei-Luen Patrick Rau1, Zhangfei Bai2
1Department of Industrial Engineering, Tsinghua University, Beijing, China.
Abstract:
Proper use of artificial intelligence (AI) can significantly enhance emergency responders' performance. However, they do not always trust or appropriately use AI. This study examined emergency responders' trust in AI and usage intention under different rescue pressures and uncertainty from the perspective of perceived capability. This study was conducted in two phases: first, questionnaire data were collected from 99 firefighters; second, semi-structured interviews were conducted with 12 participants. Results revealed that rescue pressure affected perceived AI capability, whereas uncertainty influenced perceived self-capability. Rescue pressure affected perceived AI capability, which subsequently impacted trust, and ultimately, usage intention. These findings explain the process through which rescue pressure impacts willingness to use AI. This study also explores the psychological mechanisms of trust and usage and provides valuable recommendations for designers to develop AI systems suitable for emergency responders.
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