Selective observation following betrayal shapes the social inference landscape

Despite limited access to others' actions and outcomes, humans excel at inferring hidden intentions. Given only partial access, how do they decide what to observe, and how does selective observation shape inference? Here, we examined how choosing what to observe can bias the inference about others' intentions. Participants played a game where they pursued a fleeing target while a computerized opponent acted competitively or cooperatively. Participants overestimated the opponent's competitiveness after the opponent acted more competitively than expected, whereas no such bias occurred when the opponent was more cooperative than expected. This asymmetry depended on the sequence of events, resembling hysteresis, a form of path dependence observed in physical systems. We found that these biases became stronger when participants chose to observe the opponent instead of their own avatar, and this choice came at the cost of losing precise control over their avatar. Our findings highlight the trade-off in selecting what to observe, as the resulting inference biases propagate differently depending on the interaction history.

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Publication Details

Journal
PLoS Computational Biology
Published
2026-04-24
DOI
https://doi.org/10.1371/journal.pcbi.1014200
Primary Topic
Free Will and Agency
Type
article
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article

Selective observation following betrayal shapes the social inference landscape

Seng Bum Michael Yoo, Sangkyu Son
PLoS Computational Biology
Free Will and Agency
article

Selective observation following betrayal shapes the social inference landscape

Seng Bum Michael Yoo, Sangkyu Son
article en

Abstract

Despite limited access to others' actions and outcomes, humans excel at inferring hidden intentions. Given only partial access, how do they decide what to observe, and how does selective observation shape inference? Here, we examined how choosing what to observe can bias the inference about others' intentions. Participants played a game where they pursued a fleeing target while a computerized opponent acted competitively or cooperatively. Participants overestimated the opponent's competitiveness after the opponent acted more competitively than expected, whereas no such bias occurred when the opponent was more cooperative than expected. This asymmetry depended on the sequence of events, resembling hysteresis, a form of path dependence observed in physical systems. We found that these biases became stronger when participants chose to observe the opponent instead of their own avatar, and this choice came at the cost of losing precise control over their avatar. Our findings highlight the trade-off in selecting what to observe, as the resulting inference biases propagate differently depending on the interaction history.

PLoS Computational BiologyVol. 22(4)
Baylor College of Medicine (US), Institute for Basic Science (KR), Sungkyunkwan University (KR)
Reduced inequalities
Openalex Percentile: Top 5%
Free Will and Agency
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Selective observation following betrayal shapes the social inference landscape — Seng Bum Michael Yoo, Sangkyu Son · PLoS Computational Biology (2026) | TGRS Research Map | TGRS