Human-Machine Hybrid Decision Making with Applications in Auditing

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dc.contributor.authorHooshangi, Sara
dc.contributor.authorSibdari, Soheil
dc.date.accessioned2021-12-24T17:17:31Z
dc.date.available2021-12-24T17:17:31Z
dc.date.issued2022-01-04
dc.description.abstractThe decision making process in a variety of organizations faces substantial changes, largely as a result of advances in information technology and artificial intelligence (AI). A considerable number of decisions that were traditionally made by humans, are now made by machines. Consequently, many jobs that were held by experts in some fields are now occupied by data scientists who can build AI algorithms. In this paper, we address this change in work environments and suggest an innovative process for hybrid decision making between humans and machines. We focus on the auditing profession, but our method can be used in other human-intensive and critical fields such as healthcare, financial services public sectors, and humanitarian organizations.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.026
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79356
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.subjectApplications of Human-AI Collaboration: Insights from Theory and Practice
dc.subjectartificial intelligence
dc.subjectauditing
dc.subjectdecision making
dc.subjecthuman-machine
dc.titleHuman-Machine Hybrid Decision Making with Applications in Auditing
dc.type.dcmitext

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Applications of Human-AI Collaboration: Insights from Theory and Practice