Punishment is a cost imposed on a target, in response to an un- desirable action. Yet choosing to punish also reveals information about the authority’s own motives and values. We propose that observers jointly infer the wrongness of the action and the authority’s motivations. Using hypothetical scenarios in un- familiar societies, we experimentally manipulated observers’ prior beliefs and measured human observers’ inferences after observing punishment. These inferences were recapitulated in a formal model that inverts an intuitive causal model of authorities who make rational choices about punishment by weighing its costs and benefits (i.e. utilities). An essential component of this model, driving these inferences, is that legitimate authorities consider the utility of a proportional response to harmful actions, which depends on the balance between the wrongness of the act and the severity of the punishment.

When deciding whether and how to punish, people consider not only the potential direct consequences, but also, how their choice will affect observers’ judgements about the values and motives underlying the choice. We formalize the decision to punish as a rational communicative social action (RCSA). The model generates rational decisions to punish, incorporating anticipated observers’ judgements obtained from a recursive model of inference using an intuitive theory of mind. Using this model, we synthesize patterns of human punishment from recently published papers. RCSA thus offers a formal model of the cognitive process that humans use to balance preferences for how they are perceived, with other goals for punishing.

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 authoritys debunking. After observing each debunking attempt, simulated observers simultaneously update their beliefs about the perspective underlying the debunked claims and about the authoritys motives, using an intuitive causal model of the authoritys 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 authoritys biases and commitment to truth. These polarized beliefs constrained the authoritys 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.

The criteria for guiding endogenous attention are largely unknown. A prominent view is that humans preferentiallyengage with information of intermediate complexity, and minimize engagement with too simple or too complex events.Here, we operationalize the notions of engagement and complexity to test this hypothesis. We asked participants toengage with differentially complex sequences of symbols shown one-by-one and disengage when they 1) could predictthe next element of the sequence, or 2) felt the sequence was unpredictable. We define sequence complexity as a functionof the probability of obtaining that sequence from a particular Hidden Markov Model. This extends previous measuresof complexity to respect sequential structure and closely relates to the algorithmic complexity of sequence-generatingprograms. We construct different measures using this operationalization of sequence complexity to predict the probabilityof disengagement at each event. We assess under which definitions intermediate complexity is preferred.

The way two people choose to share food reveals how close their relationship is. Very close relationships alleviate the discomfort of exchanging saliva. We measure human inferences about relationships from observed food sharing actions with variable risks of saliva exchange; and then use a formal model of inverse planning to quantitatively capture these inferences. The model that best fits human judgments construes food sharing as a rational communicative social action, according to which actions are chosen both to maximize comfort given a relationship, and to communicate about the relationship itself.