Recorded Work Meetings and Algorithmic Tools: Anticipated Boundary Turbulence

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dc.contributor.authorCardon, Peter
dc.contributor.authorMa, Haibing
dc.contributor.authorFleischmann, A. Carolin
dc.contributor.authorAritz, Jolanta
dc.date.accessioned2020-12-24T19:00:06Z
dc.date.available2020-12-24T19:00:06Z
dc.date.issued2021-01-05
dc.description.abstractMeeting 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.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.022
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70633
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th 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.subjectartificial intelligence
dc.subjectfuture of work
dc.subjectlogarithms
dc.subjectonline meetings
dc.subjectrecorded meetings
dc.titleRecorded Work Meetings and Algorithmic Tools: Anticipated Boundary Turbulence
prism.startingpage196

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