One thought too few: An adaptive rationale for punishing negligence.

Why do we punish negligence? Some current accounts raise the possibility that it can be explained by the kinds of processes that lead us to punish ordinary harmful acts, such as outcome bias, character inference, or antecedent deliberative choices. Although they capture many important cases, these explanations fail to account for others. We argue that, in addition to these phenomena, there is something unique to the punishment of negligence itself: People hold others directly responsible for the basic fact of failing to bring to mind information that would help them to avoid important risks. In other words, we propose that at its heart negligence is a failure of thought. Drawing on the current literature in moral psychology, we suggest that people find it natural to punish such failures, even when they do not arise from conscious, volitional choice. This raises a question: Why punish somebody for a mental event they did not exercise deliberative control over? Drawing on the literature on how thoughts come to mind, we argue that punishing a person for such failures will help prevent their future occurrence, even without the involvement of volitional choice. This provides new insight on the structure and function of our tendency to punish negligent actions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Computational Social Psychology.

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.

Actual and counterfactual effort contribute to responsibility attributions in collaborative tasks.

How do people judge responsibility in collaborative tasks? Past work has proposed a number of metrics that people may use to attribute blame and credit to others, such as effort, competence, and force. Some theories consider only the actual effort or force (individuals are more responsible if they put forth more effort or force), whereas others consider counterfactuals (individuals are more responsible if some alternative behavior on their or their collaborator's part could have altered the outcome). Across four experiments (N=717), we found that participants' judgments are best described by a model that considers both actual and counterfactual effort. This finding generalized to an independent validation data set (N=99). Our results thus support a dual-factor theory of responsibility attribution in collaborative tasks.

The common effect of value on prioritized memory and category representation.

The way we represent categories depends on both the frequency and value of the members of that category. Thus, for instance, prototype representations can be impacted by both information about what is statistically frequent and judgments about what is valuable. Notably, recent research on memory suggests that prioritized memory is also influenced by both statistical frequency and value judgments. Although work on conceptual representation and work on prioritized memory have so far proceeded almost entirely independently, the patterns of existing findings provide evidence for a link between these two phenomena. In particular, these patterns provide evidence for the hypothesis that the impact of value on conceptual representation arises from its co-dependent relationship with prioritized memory.

Teachers recruit mentalizing regions to represent learners' beliefs.

Teaching enables humans to impart vast stores of culturally specific knowledge and skills. However, little is known about the neural computations that guide teachers' decisions about what information to communicate. Participants (N = 28) played the role of teachers while being scanned using fMRI; their task was to select examples that would teach learners how to answer abstract multiple-choice questions. Participants' examples were best described by a model that selects evidence that maximizes the learner's belief in the correct answer. Consistent with this idea, participants' predictions about how well learners would do closely tracked the performance of an independent sample of learners (N = 140) who were tested on the examples they had provided. In addition, regions that play specialized roles in processing social information, namely the bilateral temporoparietal junction and middle and dorsal medial prefrontal cortex, tracked learners' posterior belief in the correct answer. Our results shed light on the computational and neural architectures that support our extraordinary abilities as teachers.

Representational exchange in social learning: Blurring the lines between the ritual and instrumental.

We propose that human social learning is subject to a trade-off between the cost of performing a computation and the flexibility of its outputs. Viewing social learning through this lens sheds light on cases that seem to violate bifocal stance theory (BST) - such as high-fidelity imitation in instrumental action - and provides a mechanism by which causal insight can be bootstrapped from imitation of cultural practices.

Diffusion of punishment in collective norm violations.

People assign less punishment to individuals who inflict harm collectively, compared to those who do so alone. We show that this arises from judgments of diminished individual causal responsibility in the collective cases. In Experiment 1, participants (N = 1002) assigned less punishment to individuals involved in collective actions leading to intentional and accidental deaths, but not failed attempts, emphasizing that harmful outcomes, but not malicious intentions, were necessary and sufficient for the diffusion of punishment. Experiments 2.a compared the diffusion of punishment for harmful actions with 'victimless' purity violations (e.g., eating a dead human's flesh as a group; N = 752). In victimless cases, where the question of causal responsibility for harm does not arise, diffusion of collective responsibility was greatly reduced-an outcome replicated in Experiment 2.b (N = 479). Together, the results are consistent with discounting in causal attribution as the underlying mechanism of reduction in proposed punishment for collective harmful actions.

Planning with Theory of Mind.

Understanding Theory of Mind should begin with an analysis of the problems it solves. The traditional answer is that Theory of Mind is used for predicting others' thoughts and actions. However, the same Theory of Mind is also used for planning to change others' thoughts and actions. Planning requires that Theory of Mind consists of abstract structured causal representations and supports efficient search and selection from innumerable possible actions. Theory of Mind contrasts with less cognitively demanding alternatives: statistical predictive models of other people's actions, or model-free reinforcement of actions by their effects on other people. Theory of Mind is likely used to plan novel interventions and predict their effects, for example, in pedagogy, emotion regulation, and impression management.

Extortion, intuition, and the dark side of reciprocity.

Extortion occurs when one person uses some combination of threats and promises to extract an unfair share of benefits from another. Although extortion is a pervasive feature of human interaction, it has received relatively little attention in psychological research. But, we argue, extortion is structured quite similarly to far better-studied "reciprocal" social behaviors, such as conditional cooperation and retributive punishment. All of these strategies function to elicit some desirable behavior from a social partner and do so by constructing conditional incentives. The main difference is that the desired behavioral response is an unfair or unjust allocation of resources during extortion, whereas it is typically assumed to be a fair or just distribution of resources in studies of reciprocal cooperation and punishment. Thus, we propose that a common set of psychological mechanisms may render these strategies successful. We know from prior work that prosocial forms of reciprocity often work best when implemented inflexibly and intuitively, rather than deliberatively. This both affords long-term commitment to the reciprocal strategy, and also signals this commitment to social partners. We argue that, for the same reasons, extortion is likely to depend largely upon inflexible, intuitive psychological processes. Several existing lines of circumstantial evidence support this conjecture.

The role of episodic simulation in motivating commonplace harms.

Every day, people face choices which could produce negative outcomes for others, and understanding these decisions is a major aim of social psychology. Here, we show that episodic simulation - a key psychological process implicated in other types of social and moral decision-making - can play a surprising role. Across six experiments, we find that imagining performing actions which adversely affect others makes people report a higher likelihood of performing those actions in the future. This effect happens, in part, because when people construe the actions as morally justified (as they often do spontaneously), imagining doing it makes them feel good. These findings stand in contrast to traditional accounts of harm aversion in moral psychology, and instead contribute to a growing body of evidence that people often cast harming others in a positive light.

The role of causal structure in implicit evaluation.

Causal relationships, unlike mere co-occurrence, allow humans to obtain rewards and avoid punishments by intervening on their environment. Accordingly, explicit (controlled) evaluations of stimuli encountered in the environment are known to be sensitive to causal relationships above and beyond mere co-occurrence. In this project, we conduct stringent tests of whether implicit (automatic) evaluation also reflects causal relationships and begin to probe the representational mechanisms underlying such sensitivity. Participants (N = 4836) observed causal events during which two stimuli were equally contingent with positive or negative outcomes but only one of them was causally responsible for these outcomes. Across 6 studies, varying in design and amount of verbal scaffolding provided, differences in causal status consistently guided not only explicit measures of evaluation (Likert and slider scales; Bayes Factor meta-analysis: Cohen's d = 0.28, BF10 > 1046) but also their implicit counterparts (Implicit Association Tests; Bayes Factor meta-analysis: Cohen's d = 0.22, BF10 > 1029). However, unlike their explicit counterparts, implicit evaluations were not sensitive to causal relationships that had to be flexibly derived by combining disparate past experiences. Taken together, these studies suggest that implicit evaluations are sensitive to causal information. Such sensitivity seems to be mediated via precompiled, causally informed value representations rather than online computations over a causal model.

Actual knowledge.

This response argues that when you represent others as knowing something, you represent their mind as being related to the actual world. This feature of knowledge explains the limits of knowledge attribution, how knowledge differs from belief, and why knowledge underwrites learning from others. We hope this vision for how knowledge works spurs a new era in theory of mind research.

Generating Options and Choosing Between Them Depend on Distinct Forms of Value Representation.

Humans have a remarkable capacity for flexible decision-making, deliberating among actions by modeling their likely outcomes. This capacity allows us to adapt to the specific features of diverse circumstances. In real-world decision-making, however, people face an important challenge: There are often an enormous number of possibilities to choose among, far too many for exhaustive consideration. There is a crucial, understudied prechoice step in which, among myriad possibilities, a few good candidates come quickly to mind. How do people accomplish this? We show across nine experiments (N = 3,972 U.S. residents) that people use computationally frugal cached value estimates to propose a few candidate actions on the basis of their success in past contexts (even when irrelevant for the current context). Deliberative planning is then deployed just within this set, allowing people to compute more accurate values on the basis of context-specific criteria. This hybrid architecture illuminates how typically valuable thoughts come quickly to mind during decision-making.

Communication in action: Planning and interpreting communicative demonstrations.

Theory of mind enables an observer to interpret others' behavior in terms of unobservable beliefs, desires, intentions, feelings, and expectations about the world. This also empowers the person whose behavior is being observed: By intelligently modifying her actions, she can influence the mental representations that an observer ascribes to her, and by extension, what the observer comes to believe about the world. That is, she can engage in intentionally communicative demonstrations. Here, we develop a computational account of generating and interpreting communicative demonstrations by explicitly distinguishing between two interacting types of planning. Typically, instrumental planning aims to control states of the environment, whereas belief-directed planning aims to influence an observer's mental representations. Our framework extends existing formal models of pragmatics and pedagogy to the setting of value-guided decision-making, captures how people modify their intentional behavior to show what they know about the reward or causal structure of an environment, and helps explain data on infant and child imitation in terms of literal versus pragmatic interpretation of adult demonstrators' actions. Additionally, our analysis of belief-directed intentionality and mentalizing sheds light on the sociocognitive mechanisms that underlie distinctly human forms of communication, culture, and sociality. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Effect of Cognitive Load on Intent-Based Moral Judgment.

When making a moral judgment, people largely care about two factors: Who did it (causal responsibility), and did they intend to (intention)? Since Piaget's seminal studies, we have known that as children mature, they gradually place greater emphasis on intention, and less on mere bad outcomes, when making moral judgments. Today, we know that this developmental shift has several signature properties. Recently, it has been shown that when adults make moral judgments under cognitive load, they exhibit a pattern similar to young children; that is, their judgments become notably more outcome based. Here, we show that all of the same signature properties that accompany the outcome-to-intent shift in childhood characterize the "intent-to-outcome" shift obtained under cognitive load in adults. These findings hold important implications for current theories of moral judgment.

Reasoning supports utilitarian resolutions to moral dilemmas across diverse measures.

Sacrificial moral dilemmas elicit a strong conflict between the motive to not personally harm someone and the competing motive to achieving the greater good, which is often described as the "utilitarian" response. Some prior research suggests that reasoning abilities and deliberative cognitive style are associated with endorsement of utilitarian solutions, but, as has more recently been emphasized, both conceptual and methodological issues leave open the possibility that utilitarian responses are due instead to a reduced emotional response to harm. Across 8 studies, using self-report, behavioral performance, and neuroanatomical measures, we show that individual differences in reasoning ability and cognitive style of thinking are positively associated with a preference for utilitarian solutions, but bear no relationship to harm-relevant concerns. These findings support the dual-process model of moral decision making and highlight the utility of process dissociation methods. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Punishment is Organized around Principles of Communicative Inference.

Humans use punishment to influence each other's behavior. Many current theories presume that this operates as a simple form of incentive. In contrast, we show that people infer the communicative intent behind punishment, which can sometimes diverge sharply from its immediate incentive value. In other words, people respond to punishment not as a reward to be maximized, but as a communicative signal to be interpreted. Specifically, we show that people expect harmless, yet communicative, punishments to be as effective as harmful punishments (Experiment 1). Under some situations, people display a systematic preference for harmless punishments over more canonical, harmful punishments (Experiment 2). People readily seek out and infer the communicative message inherent in a punishment (Experiment 3). And people expect that learning from punishment depends on the ease with which its communicative intent can be inferred (Experiment 4). Taken together, these findings demonstrate that people expect punishment to be constructed and interpreted as a communicative act.

The logic of universalization guides moral judgment.

To explain why an action is wrong, we sometimes say, "What if everybody did that?" In other words, even if a single person's behavior is harmless, that behavior may be wrong if it would be harmful once universalized. We formalize the process of universalization in a computational model, test its quantitative predictions in studies of human moral judgment, and distinguish it from alternative models. We show that adults spontaneously make moral judgments consistent with the logic of universalization, and report comparable patterns of judgment in children. We conclude that, alongside other well-characterized mechanisms of moral judgment, such as outcome-based and rule-based thinking, the logic of universalizing holds an important place in our moral minds.

Knowledge before belief.

Research on the capacity to understand others' minds has tended to focus on representations of beliefs, which are widely taken to be among the most central and basic theory of mind representations. Representations of knowledge, by contrast, have received comparatively little attention and have often been understood as depending on prior representations of belief. After all, how could one represent someone as knowing something if one does not even represent them as believing it? Drawing on a wide range of methods across cognitive science, we ask whether belief or knowledge is the more basic kind of representation. The evidence indicates that nonhuman primates attribute knowledge but not belief, that knowledge representations arise earlier in human development than belief representations, that the capacity to represent knowledge may remain intact in patient populations even when belief representation is disrupted, that knowledge (but not belief) attributions are likely automatic, and that explicit knowledge attributions are made more quickly than equivalent belief attributions. Critically, the theory of mind representations uncovered by these various methods exhibits a set of signature features clearly indicative of knowledge: they are not modality-specific, they are factive, they are not just true belief, and they allow for representations of egocentric ignorance. We argue that these signature features elucidate the primary function of knowledge representation: facilitating learning from others about the external world. This suggests a new way of understanding theory of mind - one that is focused on understanding others' minds in relation to the actual world, rather than independent from it.

Rationalization as representational exchange: Scope and mechanism.

The commentaries suggest many important improvements to the target article. They clearly distinguish two varieties of rationalization - the traditional "motivated reasoning" model, and the proposed representational exchange model - and show that they have distinct functions and consequences. They describe how representational exchange occurs not only by post hoc rationalization but also by ex ante rationalization and other more dynamic processes. They argue that the social benefits of representational exchange are at least as important as its direct personal benefits. Finally, they construe our search for meaning, purpose, and narrative - both individually and collectively - as a variety of representational exchange. The result is a theory of rationalization as representational exchange both wider in scope and better defined in mechanism.