Daniel Williams

I clarify and defend the hypothesis that human belief formation is sensitive to social rewards and punishments, such that beliefs are sometimes formed based on unconscious expectations of their likely effects on other agents – agents who frequently reward us when we hold ungrounded beliefs and punish us when we hold reasonable ones. After clarifying this phenomenon and distinguishing it from other sources of bias in the psychological literature, I argue that the hypothesis is plausible on theoretical grounds and I show how it illuminates and unifies a range of psychological phenomena, including confabulation and rationalisation, positive illusions, and identity-protective cognition.

A large and growing body of research in computational psychiatry draws on Bayesian modelling to illuminate the dysfunctions and aberrations that underlie psychiatric disorders. After identifying the chief attractions of this research programme, we argue that its typical focus on abstract, domain-general inferential processes is likely to obscure many of the distinctive ways in which the human mind can break down and malfunction. We illustrate this by appeal to psychosis and the social phenomenology of delusions.

Neil Levy argues that the importance of acquiring cultural knowledge in our evolutionary past selected for conformist and deferential social learning, and that contemporary bad beliefs – roughly, popular beliefs at odds with expert consensus – result primarily from the rational deployment of such conformity and deference in epistemically polluted modern environments. I raise several objections to this perspective. First, against the cultural evolutionary theory from which Levy draws, I argue that humans evolved to be highly sophisticated and vigilant social learners. Given this, the ubiquity of bad beliefs in the modern world is puzzling: if humans are so smart and suspicious, why do these characteristics seem so rare in domains such as politics? I argue that the answer rests on the incentives that underlie bad beliefs, and I favorably contrast this explanation with Levy’s appeal to epistemic pollution.

Recent work in economics has rediscovered the importance of belief-based utility for understanding human behaviour. Belief ‘choice’ is subject to an important constraint, however: people can only bring themselves to believe things for which they can find rationalizations. When preferences for similar beliefs are widespread, this constraint generates rationalization markets, social structures in which agents compete to produce rationalizations in exchange for money and social rewards. I explore the nature of such markets, I draw on political media to illustrate their characteristics and behaviour, and I highlight their implications for understanding motivated cognition and misinformation.

ABSTRACT How can imagination generate knowledge when its contents are voluntarily determined? Several philosophers have recently answered this question by pointing to the constraints that underpin imagination when it plays knowledge-generating roles. Nevertheless, little has been said about the nature of these constraints. In this paper, I argue that the constraints that underpin sensory imagination come from the structure of causal probabilistic generative models, a construct that has been highly influential in recent cognitive science and machine learning. I highlight several attractions of this account, and I favourably contrast it with Peter Langland-Hassan’s account of sensory imagination in terms of the forward models exploited in sensorimotor control.