Task Delegability to AI: Evaluation of a Framework in a Knowledge Work Context

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dc.contributor.authorCvetkovic, Izabel
dc.contributor.authorBittner, Eva
dc.date.accessioned2021-12-24T17:17:08Z
dc.date.available2021-12-24T17:17:08Z
dc.date.issued2022-01-04
dc.description.abstractWith the increased research focus on ways to use AI for augmentation rather than automation of knowledge-intensive work, a myriad of questions on how this should be accomplished arises. To break down the complexity of Human-AI collaboration, this paper pursues the identification of factors that contribute to the delegation of tasks to AI in such a setting, and consequently gain insights into requirements for meaningful task allocation. To address this research gap, we carried out an empirical study on an existing task delegability framework in a knowledge work context. We employed several statistical approaches such as confirmatory factor analysis, linear regression, and analysis of covariance. Results show that an adapted framework with fewer factors fits the data better. As for the framework factors, we show that the factor trust predicts delegability best. Furthermore, we find a significant impact of task on delegability decision. Finally, we derive theoretical and design implications.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.021
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79351
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.subjectAI and Future of Work
dc.subjectai
dc.subjectdelegation
dc.subjectknowledge work
dc.subjecttask
dc.titleTask Delegability to AI: Evaluation of a Framework in a Knowledge Work Context
dc.type.dcmitext

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