Affiliation:
1. Johns Hopkins University, Baltimore, MD, USA
Abstract
Human cognitive and decision-making abilities depreciate under pressure, motivating the emergence of artificial intelligence (AI) systems as decision support tools to assist people in performing tasks under stress. In this work, we study human decision-making behavior and task performance under time pressure---induced from limitedinitial observation time (time to perform the task before providing an initial response without AI input) andfinal decision time (time to weigh an AI's suggestion before reaching a collective human-AI team answer)---for spatial reasoning and count estimation tasks. Our results show that, while the impact of initial observation time on AI-assisted decision-making was dependent on task nature, participants were more likely to follow AI suggestions when they were provided with longer final decision time; moreover, although participants generally tended to adhere to their initial responses, they had more agency when they were more logically engaged in a task. Our results offer a nuanced understanding of human-AI collaboration under time pressure in different phases of the decision-making process.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)
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