Characterizing Interaction Uncertainty in Human-Machine Teams
Document Type
Conference Proceeding
Publication Date
1-1-2024
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.
Identifier
85197373800 (Scopus)
ISBN
[9798350315790]
Publication Title
2024 IEEE 4th International Conference on Human-Machine Systems, ICHMS 2024
External Full Text Location
https://doi.org/10.1109/ICHMS59971.2024.10555605
Recommended Citation
Wenskovitch, John; Fallon, Corey; Miller, Kate; and Dasgupta, Aritra, "Characterizing Interaction Uncertainty in Human-Machine Teams" (2024). Faculty Publications. 966.
https://digitalcommons.njit.edu/fac_pubs/966
