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

dc.contributor.author Cvetkovic, Izabel
dc.contributor.author Bittner, Eva
dc.date.accessioned 2021-12-24T17:17:08Z
dc.date.available 2021-12-24T17:17:08Z
dc.date.issued 2022-01-04
dc.description.abstract With 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.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.021
dc.identifier.isbn 978-0-9981331-5-7
dc.identifier.uri http://hdl.handle.net/10125/79351
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject AI and Future of Work
dc.subject ai
dc.subject delegation
dc.subject knowledge work
dc.subject task
dc.title Task Delegability to AI: Evaluation of a Framework in a Knowledge Work Context
dc.type.dcmi text
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