The extent of algorithm aversion in decision-making situations with varying gravity

Ibrahim Filiz; Jan René Judek; Marco Lorenz; Markus Spiwoks

PLOS ONE · 2023-02-21
Research article · Version of record · CC BY 4.0 · 9,109 words

Original source: Volume 18 · Issue 2 · e0278751

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Title: The extent of algorithm aversion in decision-making situations with varying gravity
Human authorship: Ibrahim Filiz; Jan René Judek; Marco Lorenz; Markus Spiwoks
Source: Complete manuscript edition 2026-10-29
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Original authors / creators: Ibrahim Filiz; Jan René Judek; Marco Lorenz; Markus Spiwoks
Original publication: PLOS ONE · Public Library of Science · 2023-02-21
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doi:10.1371/journal.pone.0278751
License & retained notices: CC BY 4.0
Original authors retain the copyright stated in the source. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Article-specific license href: http://creativecommons.org/licenses/by/4.0/
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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Article-specific license href: http://creativecommons.org/licenses/by/4.0/
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Evidence limits: Student sample of 143; algorithm superiority stipulated by lottery, not field evidence. Context and perceived gravity vary together; their independent causal effects are not isolated. Real-world error costs, rights and uncertainty are broader than the incentive task.
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