Sequential Theory of Mind Modeling in Team Search and Rescue Tasks

Li, Huao; Le, Long; Chis, Max; Zheng, Keyang; Hughes, Dana; Lewis, Michael; Sycara, Katia

doi:10.1007/978-3-031-21671-8_10

Cited by 2 publications

(1 citation statement)

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“…To issue valid interventions to the team, artificial advisors need to maintain a cognitive model of humans to recognize and attribute their mental states, beliefs, desires, and intentions (Williams, Fiore, & Jentsch, 2022). Instead of modeling humans with black-box models, like neural networks (Li et al, 2022) or model-based reinforcement learning (Gao et al, 2019),Theory of Mind models can be used to reveal more internal information about human decision-making processes (Baker, Jara-Ettinger, Saxe, & Tenenbaum, 2017). We will use the term artificial social intelligence (ASI) to refer to agents that can process social signals from humans.…”

Section: Introductionmentioning

confidence: 99%

Sentiment analysis of Artificial Advisors in Search and Rescue Tasks

Li,

Chis,

Zheng

et al. 2023

Proceedings of the Human Factors and Ergonomics Society Annual

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The potential of Artificial Intelligence in assisting human teamwork has yet to be fully realized, despite its success in other domains. To ensure AI’s effectiveness and credibility as a team advisor, it must be able to effectively infer team dynamics and issue appropriate interventions. This study focuses on AI-mediated human teamwork in an simulated search and rescue (SAR) task, where a team of humans is monitored and guided by an artifical social intelligence (ASI). Six different ASIs are compared against a human baseline investigating the characteristics and effectiveness of their interventions. When adjusted for initial player competence ASIs performed on par with the human advisor although the human advisor was rated as more trustworthy and useful. Additionally, sentiment analysis of the interventions reveals that participants were more likely to accept interventions with negative emotions and resulted in improved team performance.

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