Leverage white-collar workers with AI

dc.contributor.authorJüngling, Stephan
dc.contributor.authorHofer, Angelin
dc.contributor.editorMartin, Andreas
dc.contributor.editorHinkelmann, Knut
dc.contributor.editorGerber, Aurona
dc.contributor.editorLenat, Doug
dc.contributor.editorClark, Peter
dc.date.accessioned2024-04-22T12:54:15Z
dc.date.available2024-04-22T12:54:15Z
dc.date.issued2019
dc.description.abstractBased on the example of automated meeting minutes taking, the paper highlights the potential of optimizing the allocation of tasks between humans and machines to take the particular strengths and weaknesses of both into account. In order to combine the functionality of supervised and unsupervised machine learning with rule-based AI or traditionally programmed software components, the capabilities of AI-based system actors need to be incorporated into the system design process as early as possible.
dc.description.urihttps://ceur-ws.org/Vol-2350/
dc.eventAAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019)
dc.event.end2019-03-27
dc.event.start2019-03-25
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/42491
dc.identifier.urihttps://doi.org/10.26041/fhnw-6456
dc.language.isoen
dc.relation.ispartofProceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.spatialPalo Alto
dc.subject.ddc330 - Wirtschaft
dc.titleLeverage white-collar workers with AI
dc.type04B - Beitrag Konferenzschrift
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Wirtschaftde_CH
fhnw.affiliation.institutInstitut für Wirtschaftsinformatikde_CH
fhnw.openAccessCategoryDiamond
fhnw.publicationStatePublished
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relation.isAuthorOfPublicationa0a07c02-c654-413c-8b66-f994bc95e9aa
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