Human-AI Teamwork Interface Design Using Patterns of Interactions

Increasingly capable Artificial Intelligence (AI) agents are reaching new performance levels and humans need to work effectively with them in a variety of collaborative team structures. Of particular interest is "shared control collaboration", where actions taken by the team depend on the blended combination of inputs from all team entities. We conducted an experiment where participants played a game and maneuvered a spacecraft while working in concert with an AI agent and simultaneously performing a secondary task. The experiment results (i) show different patterns of interactions across user interface designs, agent capabilities, and participants' game experience, (ii) underscore the importance of providing information about the shared control collaborative task to humans who are working with a less-capable agent, and (iii) imply the potential of real-time communication about agent's state to achieve better teamwork. Our findings are expected to be transferable to other shared control collaboration settings, including AI-enabled autopilots.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2024-08-26
DOI
https://doi.org/10.1080/10447318.2024.2389350
Citations
5
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
3.22
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article

Human-AI Teamwork Interface Design Using Patterns of Interactions

Rahul Mehta, Kazuhiko Momose, Josias Moukpe, Troy R. Weekes et al.
5 citations
International Journal of Human-Computer Interaction
Human-Automation Interaction and Safety
3.22
article

Human-AI Teamwork Interface Design Using Patterns of Interactions

Rahul Mehta, Kazuhiko Momose, Josias Moukpe, Troy R. Weekes, Thomas C. Eskridge
article en
5 citations

Abstract

Increasingly capable Artificial Intelligence (AI) agents are reaching new performance levels and humans need to work effectively with them in a variety of collaborative team structures. Of particular interest is "shared control collaboration", where actions taken by the team depend on the blended combination of inputs from all team entities. We conducted an experiment where participants played a game and maneuvered a spacecraft while working in concert with an AI agent and simultaneously performing a secondary task. The experiment results (i) show different patterns of interactions across user interface designs, agent capabilities, and participants' game experience, (ii) underscore the importance of providing information about the shared control collaborative task to humans who are working with a less-capable agent, and (iii) imply the potential of real-time communication about agent's state to achieve better teamwork. Our findings are expected to be transferable to other shared control collaboration settings, including AI-enabled autopilots.

International Journal of Human-Computer InteractionVol. 41(11)
Florida Institute of Technology (US)
Openalex Percentile: Top 8%
Human-Automation Interaction and Safety
3.22
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Human-AI Teamwork Interface Design Using Patterns of Interactions — Rahul Mehta, Kazuhiko Momose, et al. · International Journal of Human-Computer Interaction (2024) | TGRS Research Map | TGRS