Emotion prediction as computation over a generative theory of mind

How rational inference about authority debunking can curtail, sustain, or spread belief polarization

In polarized societies, divided subgroups of people have different perspectives on a range of topics. Aiming to reduce polarization, authorities may use debunking to lend support to one perspective over another. Debunking by authorities gives all observers shared information, which could reduce disagreement. In practice, however, debunking may have no effect or could even contribute to further polarization of beliefs. We developed a cognitively inspired model of observers' rational inferences from an authority's debunking. After observing each debunking attempt, simulated observers simultaneously update their beliefs about the perspective underlying the debunked claims and about the authority's motives, using an intuitive causal model of the authority's decision-making process. We varied the observers' prior beliefs and uncertainty systematically. Simulations generated a range of outcomes, from belief convergence (less common) to persistent divergence (more common). In many simulations, observers who initially held shared beliefs about the authority later acquired polarized beliefs about the authority's biases and commitment to truth. These polarized beliefs constrained the authority's influence on new topics, making it possible for belief polarization to spread. We discuss the implications of the model with respect to beliefs about elections.

Children use disagreement to infer what happened

In a rapidly changing and diverse world, the ability to reason about conflicting perspectives is critical for effective communication, collaboration, and critical thinking. The current pre-registered experiments with children ages 7 to 11 years investigated the developmental foundations of this ability through a novel social reasoning paradigm and a computational approach. In the inference task, children were asked to figure out what happened based on whether two speakers agreed or disagreed in their interpretation. In the prediction task, children were provided information about what happened and asked to predict whether two speakers will agree or disagree. Together, these experiments assessed children's understanding that disagreement often results from ambiguity about what happened, and that ambiguity about what happened is often predictive of disagreement. Experiment 1 (N = 52) showed that children are more likely to infer that an ambiguous utterance occurred after learning that people disagreed (versus agreed) about what happened and found that these inferences become stronger with age. Experiment 2 (N = 110) similarly found age-related change in children's inferences and also showed that children could reason in the forward direction, predicting that an ambiguous utterance would lead to disagreement. A computational model indicated that although children's ability to predict when disagreements might arise may be critical for making the reverse inferences, it did not fully account for age-related change.

Social cues influence perception of others' pain

BACKGROUND

Accurately perceiving other people's pain is important in both daily life and healthcare settings. However, judging other's pain is inherently difficult and can be biased by various social and cultural factors. Here, we examined whether perception of others' pain and pain management recommendations are socially influenced by seeing the opinions of other raters.

METHODS

In Experiment 1 (N = 50), participants rated pictures depicting injured hands or feet of pre-selected high, medium and low intensities. Each picture was preceded by cues indicating ratings of 10 previous participants. Cues were randomized to indicate low (SocialLOW) or high (SocialHIGH) pain judgements and were not predictive of actual normative pain intensity. In Experiment 2 (N = 209), participants viewed facial video clips of patients with chronic shoulder pain making painful movements. They estimated patients' pain intensity and provided pain management recommendations.

RESULTS

Experiment 1 revealed that perceivers' pain estimates were significantly and substantially higher for stimuli following SocialHIGH than SocialLOW cues (Cohen's d = 1.26, p < 0.001) and paralleled by increased skin conductance responses. Experiment 2 replicated the effect of social cues on pain judgements (d = 0.58, p < 0.001). However, social cues did not influence post-study pain management recommendations, potentially due to memory limitations.

CONCLUSIONS

Together, these studies reveal that judgements of others' pain are robustly modulated by information about others' opinions. Future research could test the prevalence and strength of such effects in clinical settings.

SIGNIFICANCE

The present study shows that even arbitrary opinions of other raters influence the perception of others' pain. This finding adds new insight into the growing evidence of social and cultural biases in pain estimation.

Calculated Feelings: How Children Use Probability to Infer Emotions

Developing the ability to accurately infer others' emotions is crucial for children's cognitive development. Here, we offer a new theoretical perspective on how children develop this ability. We first review recent work showing that with age, children increasingly use probability to infer emotions. We discuss how these findings do not fit with prominent accounts of how children understand emotions, namely the script account and the theory of mind account. We then outline a theory of how probability allows children to infer others' emotions. Specifically, we suggest that probability provides children with information about how much weight to put on alternative outcomes, allowing them to infer emotions by comparing outcomes to counterfactual alternatives.