Document Type

Conference Paper

Publication Date

2022

Publication Title

Proceedings of the 55th Hawaii International Conference on System Sciences

Pages

7607-7616

Conference Name

55th Hawaii International Conference on System Sciences, Virtual/Maui, Hawaii, January 3-7, 2022

Abstract

Human-machine interaction (HMI) has become an essential part of the daily routine in organizations. Although the machines are designed with state-of-the-art Artificial Intelligence applications, they are limited in their ability to mimic human behavior. The human-human interaction occurs between two or more humans; when a machine replaces a human, the interaction dynamics are not the same. The results indicate that a machine that interacts with a human can increase the mental uncertainty that a human experiences. Developments in decision sciences indicate that using quantum probability theory (QPT) improves the understanding of human decision-making than merely using classical probability theory (CPT). In this paper, we examine the HMI from a QPT perspective. Applying QPT to studying HMI for decision-making shows improvement in understanding the decision process when interacting with machines because it provides insights into the mental uncertainty of a human that is not apparent in CPT.

Comments

Bibliographic information: Series: Proceedings of the Annual Hawaii International Conference on System Sciences

ISBN: 978-0-9981331-5-7

ISSN: 2572-6862

Original Publication Citation

Canan, M., Demir, M., & Kovacic, S. (2022). A probabilistic perspective of human-machine interaction. In T. X. Bui (Ed.) Proceedings of the 55th Hawaii International Conference on System Sciences (pp. 7607-7616). HICSS. http://hdl.handle.net/10125/80256

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