Recorded Work Meetings and Algorithmic Tools: Anticipated Boundary Turbulence

dc.contributor.author Cardon, Peter
dc.contributor.author Ma, Haibing
dc.contributor.author Fleischmann, A. Carolin
dc.contributor.author Aritz, Jolanta
dc.date.accessioned 2020-12-24T19:00:06Z
dc.date.available 2020-12-24T19:00:06Z
dc.date.issued 2021-01-05
dc.description.abstract Meeting recordings and algorithmic tools that process and evaluate recorded meeting data may provide many new opportunities for employees, teams, and organizations. Yet, the use of this data raises important consent, data use, and privacy issues. The purpose of this research is to identify key tensions that should be addressed in organizational policymaking about data use from recorded work meetings. Based on interviews with 50 professionals in the United States, China, and Germany, we identify the following five key tensions (anticipated boundary turbulence) that should be addressed in a social contract approach to organizational policymaking for data use of recorded work meetings: disruption versus help in relationships, privacy versus transparency, employee control versus management control, learning versus evaluation, and trust in AI versus trust in people.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2021.022
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/70633
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th 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 artificial intelligence
dc.subject future of work
dc.subject logarithms
dc.subject online meetings
dc.subject recorded meetings
dc.title Recorded Work Meetings and Algorithmic Tools: Anticipated Boundary Turbulence
prism.startingpage 196
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