A Probabilistic Perspective of Human-Machine Interaction

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dc.contributor.authorCanan, Mustafa
dc.contributor.authorDemir, Mustafa
dc.contributor.authorKovacic, Samual
dc.date.accessioned2021-12-24T18:29:31Z
dc.date.available2021-12-24T18:29:31Z
dc.date.issued2022-01-04
dc.description.abstractHuman-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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.914
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/80256
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCyber Systems: Their Science, Engineering, and Security
dc.subjecthuman
dc.subjectinteraction
dc.subjectmachine
dc.subjectprobability
dc.titleA Probabilistic Perspective of Human-Machine Interaction
dc.type.dcmitext

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