ArticleScientific reports2024
Individual and team profiling to support theory of mind in artificial social intelligence.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Digital humanistic program to manage premature frailty in young breast cancer survivors with gender perspective.NPJ digital medicine · 2025Article
- Artificial social intelligence in teamwork: how team traits influence human-AI dynamics in complex tasks.Frontiers in robotics and AI · 2025Article
- Towards fluid human-agent collaboration: From dynamic collaboration patterns to models of theory of mind reasoning.Frontiers in robotics and AI · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We describe an approach aimed at helping artificial intelligence develop theory of mind of their human teammates to support team interactions. We show how this can be supported through the provision of quantifiable, machine-readable, a priori information about the human team members to an agent. We first show how our profiling approach can capture individual team member characteristic profiles that can be constructed from sparse data and provided to agents to support the development of artificial theory of mind. We then show how it captures features of team composition that may influence team performance. We document this through an experiment examining factors influencing the performance of ad-hoc teams executing a complex team coordination task when paired with an artificial social intelligence (ASI) teammate. We report the relationship between the individual and team characteristics and measures related to task performance and self-reported perceptions of the ASI. The results show that individual and emergent team profiles were able to characterize features of the team that predicted behavior and explain differences in perceptions of ASI. Further, the features of these profiles may interact differently when teams work with human versus ASI advisors. Most strikingly, our analyses showed that ASI advisors had a strong positive impact on low potential teams such that they improved the performance of those teams across mission outcome measures. We discuss these findings in the context of developing intelligent technologies capable of social cognition and engage in collaborative behaviors that improve team effectiveness.
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Registered trials
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