@inproceedings{3b8af1b2c0d54cb0b7b38944c705ea82,
title = "Characterizing Interaction Uncertainty in Human-Machine Teams",
abstract = "With the increasing use and adoption of artificial intelligence (AI), the reliability of modern data systems will be driven by a tighter teaming between human experts and intelligent machine teammates. As in the case of human-human teams, the success of human-machine teams will also rely on clear communication about mutual goals and actions. In this paper, we combine related literature from cognitive psychology, human-machine teaming, uncertainty in data analysis, and multi-agent systems to propose a new form of uncertainty: interaction uncertainty for characterizing bidirectional communication in human-machine teams. We map the causes and effects of interaction uncertainty and outline potential ways to mitigate uncertainty for mutual trust in a high-consequence real-world scenario.",
keywords = "data analytics, human-machine teaming, interaction, trust, uncertainty",
author = "John Wenskovitch and Corey Fallon and Kate Miller and Aritra Dasgupta",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 4th IEEE International Conference on Human-Machine Systems, ICHMS 2024 ; Conference date: 15-05-2024 Through 17-05-2024",
year = "2024",
doi = "10.1109/ICHMS59971.2024.10555605",
language = "English (US)",
series = "2024 IEEE 4th International Conference on Human-Machine Systems, ICHMS 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Ming Hou and Falk, {Tiago H.} and Arash Mohammadi and Antonio Guerrieri and David Kaber",
booktitle = "2024 IEEE 4th International Conference on Human-Machine Systems, ICHMS 2024",
address = "United States",
}