Warning people about the risk of AI error mitigates human acquisition of AI bias

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dc.contributor.authorVicente, Lucía
dc.contributor.authorMatute, Helena
dc.date.accessioned2026-05-20T07:02:32Z
dc.date.available2026-05-20T07:02:32Z
dc.date.issued2026-04-30
dc.date.updated2026-05-20T07:02:32Z
dc.description.abstractEmpirical evidence has demonstrated the power of AI to influence human decisions and the risk of humans acquiring AI biases. Therefore, there is a clear need to develop strategies to mitigate such threat. In three experiments, set in a medical context, we tested whether warning individuals about AI biases and errors could mitigate the negative impact of AI biases on their decisions and reduce the transmission of AI biases to humans. In Experiment 1, participants received explicit information about the percentage of erroneous AI recommendations but with two different framings: in terms of AI accuracy or AI risk of error. Our results showed that emphasising the risk of AI errors, more than its accuracy, reduced people’s tendency to follow incorrect AI suggestions and to acquire biases from AI. In Experiment 2, a more general warning message alerting of possible AI errors and biases was also effective in reducing bias acquisition. Experiment 3 showed that, although the warning message provided some protection against bias, participants who received AI support still made more errors than participants who completed the classification task without any assistance. Experiments 2 and 3 also investigated whether the type of error made by the AI, a false positive or a false negative, influenced participants’ tendency to adhere to its suggestions, and the effect of the warning message. However, no significant effects were found. Overall, our results highlight the importance of informing users about the risk of AI error rather than focusing solely on accuracy.en
dc.description.sponsorshipSupport for this research was provided by Grant PID2021-126320NB-I00 funded by Agencia Estatal de Investigación, MCIN/AEI/https://doi.org/10. 13039/501100011033 and by ERDF A way of making Europe, as well as Grant IT1696-22 funded by Basque Government, both awarded to HM.en
dc.identifier.citationVicente, L., & Matute, H. (2026). Warning people about the risk of AI error mitigates human acquisition of AI bias. Cognitive Research: Principles and Implications, 11(1). https://doi.org/10.1186/S41235-026-00726-W
dc.identifier.doi10.1186/S41235-026-00726-W
dc.identifier.eissn2365-7464
dc.identifier.urihttps://hdl.handle.net/20.500.14454/6014
dc.language.isoeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.rights© The Author(s) 2026
dc.subject.otherArtificial intelligence (AI)
dc.subject.otherBias
dc.subject.otherDecision-making
dc.subject.otherHuman-AI interaction
dc.titleWarning people about the risk of AI error mitigates human acquisition of AI biasen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.issue1
oaire.citation.titleCognitive Research: Principles and Implications
oaire.citation.volume11
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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