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Journal article

The role of decision confidence in advice-taking and trust formation

Abstract:
In a world where ideas flow freely across multiple platforms, people must often rely on others’ advice and opinions without an objective standard to judge whether this information is accurate. The present study explores the hypothesis that an individual’s internal decision confidence can be used as a signal to learn the accuracy of others’ advice, even in the absence of feedback. According to this “agreement-in-confidence” hypothesis, people can learn about an advisor’s accuracy across multiple interactions according to whether the advice offered agrees with their own initial opinions, weighted by the confidence with which these initial opinions are held. We test this hypothesis using a judge-advisor system paradigm to precisely manipulate the profiles of virtual advisors in a perceptual decision-making task. We find that when advisors’ and participants’ judgments are independent, people can correctly learn advisors’ features, like their accuracy and calibration, whether or not objective feedback is available. However, when their judgments (and thus errors) are correlated—as is the case in many real social contexts—predictable distortions in trust can be observed between feedback and feedback-free scenarios. Using agent-based simulations, we explore implications of these individual-level heuristics for network-level patterns of trust and belief formation.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1037/xge0000960

Authors

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Role:
Author
ORCID:
0000-0002-8826-2202
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Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
ORCID:
0000-0003-1905-2129


Publisher:
American Psychological Association
Journal:
Journal of Experimental Psychology: General More from this journal
Volume:
150
Issue:
3
Pages:
507–526
Publication date:
2020-10-01
Acceptance date:
2020-06-29
DOI:
ISSN:
0096-3445


Language:
English
Keywords:
Pubs id:
1060370
Local pid:
pubs:1060370
Deposit date:
2020-07-09
ARK identifier:

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