Bertram F. Malle

Extant models of moral judgment assume that an action’s intentionality precedes assignments of blame. Knobe (2003b) challenged this fundamental order and proposed instead that the badness or blameworthiness of an action directs (and thus unduly biases) people’s intentionality judgments. His and other researchers’ studies suggested that blameworthy actions are considered intentional even when the agent lacks skill (e.g., killing somebody with a lucky shot) whereas equivalent neutral actions are not (e.g., luckily hitting a bull’s-eye). The present five studies offer an alternative account of these provocative findings. We suggest that people see the morally significant action examined in previous studies (killing) as accomplished by a basic action (pressing the trigger) for which an unskilled agent still has sufficient skill. Studies 1 through 3 show that when this basic action is performed unskillfully or is absent, people are far less likely to view the killing as intentional, demonstrating that intentionality judgments, even about immoral actions, are guided by skill information. Studies 4 and 5 further show that a neutral action such as hitting the bull’s-eye is more difficult than killing and that difficult actions are less often judged intentional. When difficulty is held constant, people’s intentionality judgments are fully responsive to skill information regardless of moral valence. The present studies thus speak against the hypothesis of a moral evaluation bias in intentionality judgments and instead document people’s sensitivity to subtle features of human action.

Attribution theory has played a major role in social-psychological research. Unfortunately, the term attribution is ambiguous. According to one meaning, forming an attribution is making a dispositional (trait) inference from behavior; according to another meaning, forming an attribution is giving an explanation (especially of behavior). The focus of this paper is on the latter phenomenon of behavior explanations. In particular, I discuss a new theory of explanation that provides an alternative to classic attribution theory as it dominates the textbooks and handbooks—which is typically as a version of Kelley’s (1967) model of attribution as covariation detection. I begin with a brief critique of this theory and, out of this critique, develop a list of requirements that an improved theory has to meet. I then introduce the new theory, report empirical data in its support, and apply it to a number of psychological phenomena. I finally conclude with an assessment of how much progress we have made in understanding behavior explanations and what has yet to be learned.

People’s concept of free will is often assumed to be incompatible with the deterministic, scientific model of the universe. Indeed, many scholars treat the folk concept of free will as assuming a special form of nondeterministic causation, possibly the notion of uncaused causes. However, little work to date has directly probed individuals’ beliefs about what it means to have free will. The present studies sought to reconstruct this folk concept of free will by asking people to define the concept (Study 1) and by confronting them with a neuroscientific claim that free will is an illusion (Study 2), which invited them to either reconcile or contrast free will with determinism. The results suggest that the core of people’s concept of free will is a choice that fulfills one’s desires and is free from internal or external constraints. No evidence was found for metaphysical assumptions about dualism or indeterminism.

The human ability to represent, conceptualize, and reason about mind and behavior is one of the greatest achievements of human evolution and is made possible by a “folk theory of mind” — a sophisticated conceptual framework that relates different mental states to each other and connects them to behavior. This chapter examines the nature and elements of this framework and its central functions for social cognition. As a conceptual framework, the folk theory of mind operates prior to any particular conscious or unconscious cognition and provides the “framing” or interpretation of that cognition. Central to this framing is the concept of intentionality, which distinguishes intentional action (caused by the agent’s intention and decision) from unintentional behavior (caused by internal or external events without the intervention of the agent’s decision). A second important distinction separates publicly observable from publicly unobservable (i.e., mental) events. Together, the two distinctions define the kinds of events in social interaction that people attend to, wonder about, and try to explain. A special focus of this chapter is the powerful tool of behavior explanation, which relies on the folk theory of mind but is also intimately tied to social demands and to the perceiver’s social goals. A full understanding of social cognition must consider the folk theory of mind as the conceptual underpinning of all (conscious and unconscious) perception and thinking about the social world

It has been hypothesized that actors tend to attribute behavior to the situation whereas observers tend to attribute behavior to the person (Jones & Nisbett 1972). The authors argue that this simple hypothesis fails to capture the complexity of actual actor-observer differences in people’s behavioral explanations. A new framework is proposed in which reason explanations are distinguished from explanations that cite causes, especially stable traits. With this framework in place, it becomes possible to show that there are a number of distinct actorobserver asymmetries in explanation, each stemming from a distinct psychological process by which explanations are generated.

This article explores several entanglements between human judgments of intentionality and morality (blame and praise). After proposing a model of people’s folk concept of intentionality I discuss three topics. First, considerations of a behavior’s intentionality a ff ect people’s praise and blame of that behavior, but one study suggests that there may be an asymmetry such that blame is more affected than praise. Second, the concept of intentionality is constitutive of many legal judgments (e.g., of murder vs. manslaughter), and one study illustrates people’s subtle considerations of intentionality in making those judgments. Third, controversial recent studies suggest that moral considerations can affect judgments of intentionality, and an asymmetry may exist such that blame a ff ects those judgments more than praise. I report two new studies that may shed light on these recent findings, and I discuss several theoretical models that might account for the impact of moral considerations on intentionality judgments and for the relationship between the two more generally.

Robot ethics encompasses ethical questions about how humans should design, deploy, and treat robots; machine morality encompasses questions about what moral capacities a robot should have and how these capacities could be computationally implemented. Publications on both of these topics have doubled twice in the past 10 years but have often remained separate from one another. In an attempt to better integrate the two, I offer a framework for what a morally competent robot would look like (normally considered machine morality) and discuss a number of ethical questions about the design, use, and treatment of such moral robots in society (normally considered robot ethics). Instead of searching for a fixed set of criteria of a robot’s moral competence I identify the multiple elements that make up human moral competence and probe the possibility of designing robots that have one or more of these human elements, which include: moral vocabulary; a system of norms; moral cognition and affect; moral decision making and action; moral communication. Juxtaposing empirical research, philosophical debates, and computational challenges, this article adopts an optimistic perspective: if robotic design truly commits to building morally competent robots, then those robots could be trustworthy and productive partners, caretakers, educators, and members of the human community. Moral competence does not resolve all ethical concerns over robots in society, but it may be a prerequisite to resolve at least some of them.