Teamness and Trust in AI-Enabled Decision Support Systems: Current Challenges and Future Directions

Research output: Contribution to journalConference articlepeer-review

Abstract

Artificial intelligence-enabled decision support systems (AI-DSSs) can process highly complex information to recommend or execute decisions autonomously, but often at the cost of lacking transparency and explainability. The existence of inherent human limitations in understanding increasingly inexplicable AI-DSSs, however, raise the question of people’s roles in the high-stakes, rapid decision-making domains for which AI-DSSs are being developed. In this paper, we summarize the current state of human-AI teaming research in light of how emergent cognitive properties arise from human interactions with AI-DSSs. We also identify important open research questions in accounting for the teamness of AI-DSSs in light of current directions in trust research. Finally, we outline some anticipated challenges in methodological approaches and generalizability when attempting to design studies to answer these questions.

Original languageEnglish (US)
Pages (from-to)175-187
Number of pages13
JournalCEUR Workshop Proceedings
Volume3456
StatePublished - 2023
EventWorkshops at the 2nd International Conference on Hybrid Human-Artificial Intelligence, HHAI-WS 2023 - Munich, Germany
Duration: Jun 26 2023Jun 27 2023

Keywords

  • AI-DSS
  • Decision support systems
  • Human-AI teaming
  • Teamness
  • Trust

ASJC Scopus subject areas

  • General Computer Science

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