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A computational framework for social valuation inference

  • Author(s): Quillien, Tadeg
  • Advisor(s): Cosmides, Leda
  • et al.

Organisms in a social species constantly need to make trade-offs between their own welfare and that of conspecifics. An emerging body of research suggests that the regulation of such trade-offs is an important function of social cognition. In particular, the mind has mechanisms designed to regulate tradeoffs between the welfare of the self and that of specific others, and in consequence, the mind also contains mechanisms designed to construct representations of the degree to which another individual values the welfare of the self.

Existing evidence suggests that such representations of “social valuation” play an important role in various cognitive processes such as reciprocity, partner choice, categorization and emotion. However, little is known about how people construct these representations. Because of its adaptive importance, I hypothesize that the process by which we infer social valuation is approximately consistent with normative standards of inference under uncertainty.

To test this hypothesis, I construct a Bayesian ideal observer for a simple task in which the observer, having seen the decisions made by a partner in a simple welfare-tradeoff game, needs to predict the decisions made by that partner in other rounds of the game. In a first set of studies, I find that people make predictions that closely track the predictions made by the ideal observer in that task. Additionally, participants’ reports of anger toward the partner are well-predicted by the social valuation inferences made by the ideal observer, even when the different partners inflict the same opportunity cost on the participant. I also find tentative evidence that anger ratings in that task are independently driven by deviations from expectations: individual differences in the amount by which the decisions of a partner deviated from the participant’s expectations track individual differences in anger toward that partner.

In a second set of studies, I study whether people are spontaneously curious about the situations which potentially contain the most information about another person’s valuation of the self. I present participants with pairs of dilemmas that another individual faced in a simple welfare-tradeoff game; for each pair, I ask them to choose the dilemma for which they would most like to see the decision that the individual had made. I find that on average, people spontaneously select the choices that have the potential to reveal the most information about the individual’s valuation of the participant, in the sense of allowing the ideal observer model to draw the richest inferences.

These results strengthen the thesis that representations of social valuation are a core component of the conceptual architecture of human social cognition.

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