Acceptance of AI for delegating emotional intelligence: Results from an experiment

dc.contributor.author Aysolmaz, Banu
dc.contributor.author Leyer, Michael
dc.contributor.author Iren, Deniz
dc.date.accessioned 2020-12-24T20:18:52Z
dc.date.available 2020-12-24T20:18:52Z
dc.date.issued 2021-01-05
dc.description.abstract Detecting emotions of other humans is challenging for us humans. It is however important in many social contexts so that many individuals seek help in this regard. As technology is evolving, more and more AI-based options emerge that promise to detect human emotions and support decision making. We focus on the full delegation of detecting emotions to AI to contribute to our understanding how such AI is perceived and why it is accepted. For this, we conduct an online scenario-based experiment in which participants have the choice to delegate emotion detection to another human in one group and to an AI tool in the other group. Our results show that the delegation rates are higher for a human, but surprisingly high for AI. The results provide insights that should be considered when designing AI-based emotion-detection tools to build trustworthy and accepted designs.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2021.761
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/71381
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 Promises and Perils of Artificial Intelligence and Machine Learning: Disruption, Adoption, Dehumanisation, Governance, Risk, and Compliance
dc.subject artificial intelligence
dc.subject attachment theory
dc.subject emotion detection
dc.subject emotions
dc.subject experiment
dc.title Acceptance of AI for delegating emotional intelligence: Results from an experiment
prism.startingpage 6307
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