Jan Hausfeld

Human societies rely on rules to coordinate behaviour, sustain cooperation, and maintain social order. Yet compliance can be fragile when rules are weakly enforced and individuals observe others violating them. Prior research shows that rule violations and other antisocial behaviours can spread through social influence, but less is known about how the severity of violations shapes these dynamics. In many real-world settings, rule breaking occurs in degrees, from minor infractions to major violations, and individuals may not only imitate others but sometimes exceed the violations they observe. Here we combine simulations and a behavioural experiment (N = 750) to study how the magnitude of observed rule violations shapes subsequent violations, and how this can generate escalation dynamics. Our simulations show that when individuals occasionally escalate beyond observed violations, even rare escalation can trigger a rapid shift from widespread compliance to collective rule breaking. In our pre-registered experiment, observing major violations strongly increased rule breaking, especially when committed by socially close others. Observing minor violations prompted many participants to follow suit and a minority to escalate beyond the violations they observed. Parameterizing the simulations with these behavioural responses shows that such escalators can disproportionately undermine collective compliance. These results highlight how asymmetric responses to rule violations and rare escalatory behaviour can transform small deviations into large-scale breakdowns of rule compliance.

Defaults are powerful: whereas wisely set defaults increase prosocial choices, poorly set defaults promote self-serving decisions. We propose a distracted-from-doing-good hypothesis: compared with distraction-free environments, distracting environments lead people to rely more on the default options, particularly self-serving ones. In a preregistered experiment, participants made repeated allocation decisions involving monetary trade-offs between personal gain and charity donations. We manipulated the default type (prosocial vs. self-serving), the presence (vs. absence) of distractions and measured individual differences in mind wandering and social value orientation. Results did not support the hypothesis but offered valuable insights: On average, participants were more likely than chance to accept prosocial defaults, and they accept more prosocial than self-serving defaults. We found evidence that some individuals use self-serving defaults to justify selfish decisions, particularly those with a prosocial orientation. Interestingly, the aggregate effects were driven by 60 percent of participants; the remaining 40 percent were uninfluenced by defaults, acting according to their social preferences. Individual differences in mind wandering—how easily one is distracted—further moderate the default effects. We discuss how the results inform our understanding of prosocial behaviors in combination with individual heterogeneity and how defaults are a good tool to promote overall prosociality.

How do people attribute responsibility when an outcome is not caused by an individual but results from a decision chain involving several people? We study this question in an experiment, in which five voters sequentially decide on how to distribute money between them and five recipients. The recipients can reward or punish each voter, which we use as measures of responsibility attribution. In the aggregate, we find that responsibility is attributed mostly according to the voters’ choices and the pivotality of the decision, but not for being the initial voter. On the individual level, we find substantial heterogeneity with three overall patterns: Little to no responsibility attribution, pivotality-driven, and focus on choices. These patterns are similar when praising voters for good outcomes and blaming voters for bad outcomes.

It is a widely held belief that people’s choices are less sensitive to changes in value as value increases. For example, the subjective difference between $11 and $12 is believed to be smaller than between $1 and $2. This idea is consistent with applications of the Weber-Fechner Law and divisive normalization to value-based choice and with psychological interpretations of diminishing marginal utility. According to random utility theory in economics, smaller subjective differences predict less accurate choices. Meanwhile, in the context of sequential sampling models in psychology, smaller subjective differences also predict longer response times. Based on these models, we would predict decisions between high-value options to be slower and less accurate. In contrast, some have argued on normative grounds that choices between high-value options should be made with less caution, leading to faster and less accurate choices. Here, we model the dynamics of the choice process across three different choice domains, accounting for both discriminability and response caution. Contrary to predictions, we mostly observe faster and more accurate decisions (i.e., higher drift rates) between high-value options. We also observe that when participants are alerted about incoming high-value decisions, they exert more caution and not less. We rule out several explanations for these results, using tasks with both subjective and objective values. These results cast doubt on the notion that increasing value reduces discriminability. Significance What information about economic value is incorporated into decision-makers’ choices? Across the decision sciences, several prominent models ignore average value, assuming that only value differences are incorporated into the decision-making process, while others assume diminishing sensitivity to value, suggesting that it should be more difficult to choose between high-value options. Other models suggest that high-value decisions should, if anything, be treated as less important (holding value difference constant). Across three experiments with very different types of choices (food, art, and learned stimuli), we find violations of these predictions. Contrary to expectations, the presence of high-value options makes decisions easier while also inducing more effort to get them right.

The act of punishing unfair behavior by unaffected observers (i.e., third‐party punishment) is a crucial factor in the functioning of human societies. In everyday life, we see different types of individuals who punish. While some individuals initiate costly punishment against an unfair person independently of what other observers do (independent punishers), others condition their punishment engagement on the presence of another person who punishes (conditional punishers). Still others do not want to partake in any sort of punishment (nonpunishers). Although these distinct behavioral types have a divergent impact on human society, the sources of heterogeneity are poorly understood. We present novel laboratory evidence on the existence of these three types. We use anatomical brain characteristics in combination with stated motives to characterize these types. Findings revealed that independent punishers have larger gray matter volume in the right temporo‐parietal junction compared to conditional punishers and nonpunishers, an area involved in social cognition. Conditional punishers are characterized by larger gray matter volume in the right dorsolateral prefrontal cortex, a brain area known to be involved in behavioral control and strategic reasoning, compared to independent punishers and nonpunishers. Finally, both independent punishers and nonpunishers are characterized by larger gray matter volume in an area involved in the processing of social and monetary rewards, that is, the bilateral caudate. By using a neural trait approach, we were able to differentiate these three types clearly based on their neural signatures, allowing us to shed light on the underlying psychological mechanisms.

There are many situations where resources are distributed between two parties and where the deciding party has information about the initial distribution and can change its outcome, for example, the allocation of budget for funds or bonuses, where the deciding party might have self-interested motives. Although the neural underpinnings of distributional preferences of resources have been extensively studied, it remains unclear if there are different types of distributional preferences and if these types underlie different disposing neural signatures. We used source-localized resting EEG in combination with a data-driven clustering approach to participants' behavior in a distribution game in order to disentangle the neural sources of the different types of distributional preferences. Our findings revealed four behavioral types: Maximizing types always changed initial distributions to maximize their personal outcomes, and compliant types always left initial distributions unchanged. Disadvantage-averse types only changed initial distributions if they received less than the other party did, and equalizing types primarily changed initial distributions to fair distributions. These behavioral types differed regarding neural baseline activation in the right inferior frontal gyrus. Maximizing and compliant types showed the highest baseline activation, followed by disadvantage-averse types and equalizing types. Furthermore, maximizing types showed significantly higher baseline activation in the left orbitofrontal cortex compared to compliant types. Taken together, our findings show that different types of distributional preferences are characterized by distinct neural signatures, which further imply differences in underlying psychological processes in decision-making.