What concept does the word ‘belief’ express, and how does it fit into the Theory of Mind? In its repertoire of syntactic niches (some not noticed in the literature) and in its range from stereotypical to marginal cases, "believe" is quite a typical word. The analysis offered here reveals striking grammatical and semantic parallels to expressions that denote depictions, such as "picture," "map," and "performance." These parallels provide unexpected solutions to classical philosophical puzzles about "belief." The analysis is extended to other propositional attitude predicates, to speech–act predicates, to predicates of actional attitude such as "intend" and "vow," and to commitment to norms of all sorts. These conclusions provide a sense of the richness of folk psychology and of how detailed linguistic analysis can uncover it, presenting challenges for future research.

The belief–action gap was originally conceptualized by psychologists who aimed to ground behaviour in beliefs but found that their models had little predictive value. The recurrent use of this concept often comes with the assumption that human behaviour is somewhat irrational or weirdly misaligned with their beliefs. This gap is particularly striking in the environmental domain, where many people seemingly think one way but act another. In this chapter, we review a number of factors that hinder general beliefs from translating into actual behaviors. We emphasize the existence of measurement issues, information deficits about the exact impact of one’s actions, structural factors, and psychological factors that together impact the robustness of the association between beliefs and actions. In particular, socio-cognitive factors have a massive impact on people’s decisions to act in ways that are aligned with their deep-seated beliefs. Once all these factors are properly taken into account, it becomes clear that the belief–action gap is not a token of human irrationality but should in fact be expected.

One bad act can permanently stain perceptions of someone’s character. Being labeled a criminal potentially has such an enduring stigma because of people’s willingness to believe that people have an internal, unchanging essence leading them to transgress. In Study 1, we developed a novel scale to assess individual differences in essentialist beliefs about criminality and found that these beliefs predicted punitiveness. Study 2 replicated these findings and also revealed that participants’ attitudes toward people who had committed crimes mediated this link. Study 3 found that participants who held essential beliefs about criminality were more likely to choose retributive punishments over those that prevented future harm. These results illustrate the importance of essentialist beliefs in the context of the legal system.

Scientific ideas are difficult to teach, difficult to learn, and difficult to accept as true because they contradict our intuitive theories of the world, constructed in childhood but retained across the lifespan, influencing our thinking even as adults. In this chapter, I discuss what intuitive theories are, where they come from, and why they blind us to more accurate theories of the world. I explore two case studies – projectile motion and evolutionary adaptation – to illustrate how intuitive theories are historically entrenched, culturally widespread, resistant to counterevidence, maladaptive for behavior, and seemingly inerasable. I conclude by considering the impact of intuitive theories on human belief and behavior more generally.

Beliefs have been studied across disciplines using a variety of approaches. In the human memory literature, expectations and beliefs drawn from prior knowledge are characterized and studied as schematic knowledge. In this chapter, we will discuss the role schematic knowledge plays in guiding the formation and retrieval of memories. A central focus will be placed upon understanding why retrieved memories are biased toward prior beliefs or schematic knowledge. Through a review of computational models and empirical findings, this chapter will convey that even though prior beliefs generate memory biases, these memory biases ultimately maximize the average memory accuracy – giving rise to optimal behavior. In the last section of the chapter, I will connect these modeling frameworks to more recent empirical results on the role of schematic knowledge, identifying potential future directions for updating the models and venues for conducting new experiments.

Research in judgment and decision making has made a lot of progress on the front of the identification of biases, and, more recently, on their correction, by suggesting feasible interventions to reduce their prevalence. Despite initial mixed results, more recent research has revealed that training is a promising debiasing tool. One-shot training interventions can reduce the incidence of several cognitive biases up to three months post training. These effects generalize to decisions and problems that were not featured in the training but are susceptible to the same biases. They were also observed in a field setting when trainees were not able to connect the decision problems to the training. Although the complexity of the decision strategies taught and the propensity of trainees to see themselves as immune to bias may pose boundary conditions to the occurrence of these effects, training has notable advantages in comparison to other debiasing tools such as incentives, accountability, and nudges.

The empirical study of belief is emerging at a rapid clip, uniting work from all corners of cognitive science. Reliance on belief in understanding and predicting behavior is widespread. Examples can be found, inter alia, in the placebo effect, attribution theory, theory of mind, and comparative psychological literatures. Research on belief also provides evidence for robust generalizations, including about how we fix, store, and change our beliefs. This article provides the first detailing of the psychofunctionalist account of belief. The picture of belief that emerges is one where belief fixation is automatic and effortless, and independent of controlled and effortful belief rejection. Belief is then stored in fragmented networks of causally isolated, context-sensitive databases. Finally, beliefs can be changed by two distinct updating systems, with one hewing to more or less normatively appropriate methods of Bayesian updating, and the other relying on a psychological immune system, which functions to guard our most centrally held beliefs from potential inconsistency with newly formed beliefs. Understanding belief’s role in our cognitive economy allows us to illuminate broader real-world issues such as how fake news, propaganda, and brainwashing exploit our psychology of belief, and how best to construct our modern informational world.

In this chapter we summarize how economists conceptualize beliefs. Moving both backward and forward in time, we review the way that mainstream economics currently deals with beliefs, as well as, briefly, the history of economists’ thinking about beliefs. Most importantly, we introduce the reader to a recent, transformational movement in economics that focuses on belief-based utility. This approach challenges the standard economic assumption that beliefs are only an input to decision making and examines implications of the intuitive idea that people derive pleasure and pain directly from their beliefs. We also address the question of when and why people care about what other people believe. We close with a discussion of the implications of these insights for contemporary social issues such as political polarization and fake news.

The accelerating development of technological power over ourselves and our environment raises the stakes of getting our beliefs right. I suggest that we can significantly improve our processes of belief formation by increasing actively open-minded thinking (AOT). Actively open-minded thinking helps us form more accurate and well-rounded beliefs by increasing the depth and – more importantly – the breadth of information search and inference. Because individuals do not always have time for adequate investigation, AOT is also a valuable indicator of which epistemic authorities are most likely to have reached accurate conclusions via effective methods. It is associated with better reasoning across a wide variety of contexts, leading to beliefs that are more accurate, more complete, and less biased. Yet it is not regularly taught in schools, nor is it a feature of typical public discourse. I suggest several strategies for increasing this cognitive habit in school and society.

Belief is often formalized using tools of probability theory. However, probability theory often focuses on simple examples – like coin flips or basic parametric distributions – and these do not describe much about actual human thinking. I highlight some basic examples of the complexity and richness of human mental representations and review some work which attempts to marry plausible types of representations with probabilistic models of belief, one of the most exciting current directions in psychology and machine learning.

In this chapter, we consider a cultural evolutionary psychological framework for understanding the origin, maintenance and diffusion of beliefs, and illustrate the utility of such a framework with two case studies – religious belief systems and conspiracy theory beliefs. A cultural evolutionary psychology of belief considers four broad sets of interacting factors: the content of a belief, a belief’s fit with individual conditions, the social dynamics surrounding a belief, and the socioecological conditions that promote or suppress a belief. A cultural evolutionary psychology of belief overcomes the limitations to what we call standard evolutionary psychology, a school of thought that emphasizes the activation of innate cognitive modules for understanding the generation and spread of beliefs. With this chapter, then, we aim to show how social and cognitive science researchers can approach the study of beliefs from an evolutionary perspective without committing to the controversial assumptions of standard evolutionary psychology.

My first course in social psychology in 1972 or 1973 was with Elliot Aronson, a premier social psychologist of his era. He mesmerized the class. The first edition of his book The Social Animal had just been published and it was our textbook for the course. My most vivid memory was learning about cognitive dissonance theory and T-groups (then popular Sensitivity Training Groups). Elliot was a big proponent of both. In front of a class of several hundred, he would hold up his book and ask: “Doesn’t it read like a novel?” The class burst into applause. Some women shouted out “We love you Elliot!” He an extraordinarily charismatic lecturer, setting a high bar that was only exceeded in my experience when I heard Phil Zimbardo give a lecture in a class I was a T.A.-ing for his wife, Christina Maslach at Berkeley. During that guest lecture, students broke into applause several times during the lecture, and thunderously at the end. With these introductions to social psychology, nothing seemed more fascinating to me than social interactions and the prospect of uncovering our underlying social psychological machinery.

In the sixty years since I took my first psychology course, much has changed. Wars have begun and ended, the US population has nearly doubled, and fifty new countries appear on redrawn world maps. Nor has social psychology stood still. The Society of Experimental Social Psychology was founded in 1965; the European Association of Experimental Social Psychology followed suit the next year (later dropping Experimental from its name). In 1974, the Society of Personality and Social Psychology (SPSP) was formed, building on the history of Division 8 of the American Psychological Association. The Association for Psychological Science (originally the American Psychological Society) came into being in 1988, and hosted the initial meetings of SPSP that evolved into an independent convention. These six decades establish the context for my development as a social psychologist on a path shaped by both chance and choice.