Bryce Huebner

The role of emotion in moral psychology

Recent work in the cognitive and neurobiological sciences indicates an important relationship between emotion and moral judgment. Based on this evidence, several researchers have argued that emotions are the source of our intuitive moral judgments. However, despite the richness of the correlational data between emotion and morality, we argue that the current neurological, behavioral, developmental and evolutionary evidence is insufficient to demonstrate that emotion is necessary for making moral judgments. We suggest instead, that the source of moral judgments lies in our causal-intentional psychology; emotion often follows from these judgments, serving a primary role in motivating morally relevant action.

The moral-conventional distinction in mature moral competence

Developmental psychologists have long argued that the capacity to distinguish moral and conventional transgressions develops across cultures and emerges early in life. Children reliably treat moral transgressions as more wrong, more punishable, independent of structures of authority, and universally applicable. However, previous studies have not yet examined the role of these features in mature moral cognition. Using a battery of adult-appropriate cases (including vehicular and sexual assault, reckless behavior, and violations of etiquette and social contracts) we demonstrate that these features also distinguish moral from conventional transgressions in mature moral cognition. Each hypothesized moral transgressions was treated as strongly and clearly immoral. However, our data suggest that although the majority of hypothesized conventional transgressions also form an obvious cluster, social conventions seem to lie along a continuum that stretches from mere matters of personal preference (e.g., getting tattoos or wearing black shoes with a brown belt) to transgressions that are treated as matters for legitimate social sanction (e.g., violating traffic laws or not paying your taxes). We use these findings to discuss issues of universality, domain-specificity, and the importance of using a wellstudied set of moral scenarios to examine clinical populations and the underlying neural architecture of moral cognition.

Intuitive Moral Judgments are Robust across Variation in Gender, Education, Politics and Religion: A Large-Scale Web-Based Study

Research on moral psychology has frequently appealed to three, apparently consistent patterns: (1) Males are more likely to engage in transgressions involving harm than females; (2) educated people are likely to be more thorough in their moral deliberations because they have better resources for rationally navigating and evaluating complex information; (3) political affiliations and religious ideologies are an important source of our moral principles. Here, we provide a test of how four factors ‐ gender, education, politics and religion ‐ affect intuitive moral judgments in unfamiliar situations. Using a large-scale sample of participants (n=8778) who voluntarily logged on to the internet-based Moral Sense Test (available online at http://moral.wjh.harvard.edu ), we analyzed responses to 145 unique moral and conventional scenarios that varied widely in content. Although each demographic or cultural factor sometimes yielded a statistically significant difference in the predicted direction (e.g., men giving more utilitarian judgments than women; religious individuals giving more deontological/rule-based judgments than atheists), these differences were consistently associated with extremely small effect sizes. We conclude that gender, education, politics and religion are likely to be relatively insignificant for moral judgments of unfamiliar scenarios. We discuss these results in light of current debates concerning the mechanisms underlying our moral judgments and, especially, the idea that we share a universal moral sense that constrains the range of cross-cultural variation.

The Linguistic Analogy: Motivations, Results, and Speculations

Inspired by the success of generative linguistics and transformational grammar, proponents of the linguistic analogy (LA) in moral psychology hypothesize that careful attention to folk-moral judgments is likely to reveal a small set of implicit rules and structures responsible for the ubiquitous and apparently unbounded capacity for making moral judgments. As a theoretical hypothesis, LA thus requires a rich description of the computational structures that underlie mature moral judgments, an account of the acquisition and development of these structures, and an analysis of those components of the moral system that are uniquely human and uniquely moral. In this paper we present the theoretical motivations for adopting LA in the study of moral cognition: (a) the distinction between competence and performance, (b) poverty of stimulus considerations, and (c) adopting the computational level as the proper level of analysis for the empirical study of moral judgment. With these motivations in hand, we review recent empirical findings that have been inspired by LA and which provide evidence for at least two predictions of LA: (a) the computational processes responsible for folk-moral judgment operate over structured representations of actions and events, as well as coding for features of agency and outcomes; and (b) folk-moral judgments are the output of a dedicated moral faculty and are largely immune to the effects of context. In addition, we highlight the complexity of the interfaces between the moral faculty and other cognitive systems external to it (e.g., number systems). We conclude by reviewing the potential utility of the theoretical and empirical tools of LA for future research in moral psychology.

Moral judgments about altruistic self-sacrifice: When philosophical and folk intuitions clash

Altruistic self-sacrifice is rare, supererogatory, and not to be expected of any rational agent; but, the possibility of giving up ones life for the common good has played an important role in moral theorizing. For example, Judith Jarvis Thomson (2008) has argued in a recent paper that intuitions about altruistic self-sacrifice suggest that something has gone wrong in philosophical debates over the trolley problem. We begin by showing that her arguments face a series of significant philosophical objections; however, our project is as much constructive as critical. Building on Thomsons philosophical argument, we report the results of a study that was designed to examine commonsense intuitions about altruistic self-sacrifice. We find that a surprisingly high proportion of people judge that they should give up their lives to save a small number of unknown strangers. We also find that the willingness to engage in such altruistic self-sacrifice is predicted by a persons religious commitments. Finally, we show that folk-moral judgments are sensitive to agent-relative reasons in a way that diverges in important ways from Thomsons proposed intuitions about the trolley problem. With this in mind, we close with a discussion of the relative merits of folk intuitions and philosophical intuitions in constructing a viable moral theory.

Do You See What We See? An Investigation of an Argument Against Collective Representation

Collectivities (states, club, unions, teams, etc.) are often fruitfully spoken of as though they possessed representational capacities. Despite this fact, many philosophers reject the possibility that collectivities might be thought of as genuinely representational. This paper addresses the most promising objection to the possibility of collective representation, the claim that there is no explanatory value to positing collective representations above and beyond the representational states of the individuals that compose a particular collectivity. I claim that this argument either proves too much, also giving us reason to abandon person-level representations, or it proves too little, demonstrating precisely the sort of continuity between individual and collective representations that would warrant the positing of genuine collective representations. I conclude with a brief sketch of two promising cases of collective representation that lend credence to my claim that individual representations and collective representations are analogous in a way that warrants the study of collective mentality from within the cognitive sciences.

Critiquing Empirical Moral Psychology

Thought experimental methods play a central role in empirical moral psychology. Against the increasingly common interpretation of recent experimental data, I argue that such methods cannot demonstrate that moral intuitions are produced by reflexive computations that are implicit, fast, and largely automatic. I demonstrate, in contrast, that evaluating thought experiments occurs at a near-glacial pace relative to the speed at which reflexive information processing occurs in a human brain. So, these methods allow for more reflective and deliberative processing than has commonly been assumed. However, these methods may still provide insight into some human strategies for navigating unfamiliar moral dilemmas.

Troubles with Stereotypes for Spinozan minds

Some people succeed in adopting feminist ideals in spite of the prevalence of asymmetric power relations. However, those who adopt such ideals face a number of psychological difficulties in inhibiting stereotype-based judgments. I argue that a Spinozan theory of belief fixation offers a more complete understanding of the mechanisms that underwrite our intuitive stereotype-based judgments. I also argue that a Spinozan theory of belief fixation offers resources for avoiding stereotype-based judgments where they are antecedently recognized to be pernicious and insidious.

Socially embedded cognition

Material facts about the arrangement of supermarkets and the design of churches, as well as rules of evidence and other social practices, play a critical role in structuring everyday human cognition. This much is hard to deny. I argue that such insights are best accommodated by a view that treats human beings as socially embedded agents that exploit the material aspects of their normatively rich environment. Further, I argue that a socially embedded approach to cognition is preferable to Gallaghers socially extended approach.

Surprisal and Valuation in the Predictive Brain

Clark (in press) argues that perception and action depend on “hierarchical predictive coding” systems, which attempt to reduce surprisal (a measure of the implausibility of a state given a model of the world). But, his appeal to surprisal-reduction does not explain the motivation to seek change, initiate motion, or engage in exploration. As he notes, “staying still inside a darkened room would afford easy and nigh-perfect prediction of our own neural states” (Clark, in press, p. 37). Clark claims that inborn expectations yield instinctual and tropistic behavior; and, he is right that surprisal-reduction mechanisms could modify behavior and reduce discrepancies between outcomes and these expectations. But, biological organisms must also recognize that strategies can be better and worse; and, they must be able to update their goals when the value of a reward changes (e.g., as they become sated or hungry). Even on the assumption that cortical processing aims to minimize prediction-errors, processes like learning, motivation, and decision-making also require valuation. The location and stability of food and water are often uncertain. So, intelligent foraging requires evaluative strategies that can determine which practices are likely to yield the best payoffs relative to the costs of acting (Montague et al., 2012). Savvy organisms should act when the benefits are likely to outweigh the costs of seeking change and engaging in exploration (Montague and King-Casas, 2007). But, this situation is complicated by the fact that dangerous and unforeseen situations often require making rapid decisions that are sensitive to the cost of acting as well as the value of the payoff that can be expected in pursuing a reward. This is why savvy organisms must possess mechanisms that facilitate reward-seeking where payoffs are better than previously experienced. But, this requires treating outcomes and strategies as better and worse, which requires more than just minimizing prediction-errors. Although there is debate over the precise mechanisms responsible for valuation, a broad consensus has emerged that one core mechanism is implemented by a network of midbrain dopaminergic neurons that compute prediction-error signals for expected rewards. This network computes a bi-directional teaching signal, which monitors the extent to which outcomes are better or worse-than-expected. Spiking rates in the basal ganglia, for example, increase when rewards are better-than-expected, decrease when they are worse-than-expected, and are unaffected when the time and quantity of rewards is accurately predicted (Montague et al., 1996). These evaluative error signals are computed for primary rewards; and, they can be attuned to respond to almost any reward-predicting stimuli – suggesting that they compute a polysensory and multimodal signal that can direct attention, learning, and action-selection in light of various valuable outcomes (Schultz, 1998, 2010). Curiously, these mechanisms also respond to novel events independently of their value; but, there is reason to suppose that this is because dopaminergic signals motivate exploration by treating novelty as its own reward (Liljeholm and O’Doherty, 2012). Similar evaluative mechanisms seem to be found throughout the brain. For example, mechanisms in the ventral striatum compute expectations when the distribution and likelihood of a reward is uncertain; and there are distinct circuits in the ventral striatum and anterior insula that evaluate risk and compute risk-prediction-error signals (Preuschoff et al., 2006, 2008; Quartz, 2009). Similar mechanisms in ventral caudate seem to implement “fictive error” signals, which compare actual outcomes against “things that could have been,” thus allowing organisms to update their expectations in light of imagined feedback (Lohrenz et al., 2007). Finally, evaluative mechanisms in orbitofrontal cortex represent reward values – in concert with mechanisms in the basal ganglia – in a way that seems to facilitate making choices on the basis of the probability of a positive outcome, given recent patterns of gains and losses (Frank and Claus, 2006). Together, these types of evaluative mechanisms appear to implement the learning signals and motivational “umph” required to get Pavlovian, habitual, and goal-directed learning off the ground (Rangel et al., 2008; Liljeholm and O’Doherty, 2012). I contend that we also need evaluative processes to understand how cultural practices “stack the dice so that we can more easily minimize costly prediction-errors” (Clark, in press, p. 43). Evaluative mechanisms can facilitate cultural attunement by treating norm compliance as rewarding and norm violation as aversive (Montague, 2006). And, perceived deviations from social norms appear to evoke neural responses that are similar to prediction-error signals (Klucharev et al., 2009, 2011). But, why would these prediction-error signals ever lead us to revise social institutions and social practices, as opposed to leading us to recalibrate our judgments? A purely calibrational mechanism can make sense of the conservative aspects of habitual learning and cultural attunement, but they leave the (relatively rare) cases where people attempt to reconfigure their environments in ways that better suit their interests mysterious. We need an account of valuational mechanisms to understand these practices of social niche construction. The decision to change your environment is always risky. And, risky decisions require not only the ability to predict rewards, but also to evaluate the likelihood of success and the value of achieving your goals. It may be possible to get genuine norm compliance from a system that doesn’t represent value – though I am skeptical. But, deciding to reject a norm, to challenge a social institution, or to develop better practices requires evaluating the likely outcomes as better and worse. Surprisal-reduction mechanisms cannot represent things as better and worse, they can only represent and reduce deviations from our expectations. However, constructing a world that stacks the dice in our favor sometimes requires pursuing a world that is better than the one we expect.