Drafts by Daniel Williams
Neil Levy argues that the importance of acquiring cultural knowledge in our evolutionary past sel... more 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 favourably contrast this explanation with Levy's appeal to epistemic pollution.
When membership of a community depends on commitment to shared beliefs, the community is a belief... more When membership of a community depends on commitment to shared beliefs, the community is a belief-based coalition, and the beliefs are identity-defining beliefs. Belief-based coalitions are pervasive features of human social life and routinely drive motivated cognition and epistemically dysfunctional group dynamics. Despite this, they remain surprisingly undertheorised in social epistemology. This article (i) clarifies the properties of belief-based coalitions and identity-defining beliefs, (ii) explains why they often incentivise and coordinate epistemically dysfunctional forms of communication and cognitive labour, and (iii) argues that they provide a better explanation of many epistemic problems on social media than the concepts of epistemic bubbles, echo chambers, and gamification.
A large and growing body of research in computational psychiatry draws on Bayesian modelling to i... more 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.
An influential body of research in neuroscience and the philosophy of mind asserts that the brain... more An influential body of research in neuroscience and the philosophy of mind asserts that the brain is an organ for prediction error minimization. I clarify how this hypothesis should be understood, and I consider a prominent attempt to justify it, according to which prediction error minimization in the brain is a manifestation of a more fundamental imperative in all self-organizing systems to minimize (variational) free energy. I argue that this justification fails. The sense in which all self-organizing systems can be said to minimize free energy according to the free energy principle is fundamentally different from the alleged sense in which brains minimize prediction error. Thus, even if the free energy principle is true, it provides no support for a theory of the brain as an organ for prediction error minimization - or any other substantive theory of brain function.
I outline and defend the hypothesis that human belief formation is sensitive to social rewards an... more I outline 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: in a species with substantial social scrutiny of beliefs, forming beliefs in a way that is sensitive to their likely effects on other agents leads to practical success. I then show how the hypothesis accommodates and unifies a range of psychological phenomena, including confabulation and rationalisation, positive illusions, and identity protective cognition.
Papers by Daniel Williams
Economics and Philosophy, 2022
Recent work in economics has rediscovered the importance of belief-based utility for understandin... more 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.
Why do well-functioning psychological systems sometimes give rise to absurd beliefs that are radi... more Why do well-functioning psychological systems sometimes give rise to absurd beliefs that are radically misaligned with reality? Drawing on signalling theory, I develop and explore the hypothesis that groups often embrace beliefs that are viewed as absurd by outsiders as a means of signalling ingroup commitment. I clarify the game-theoretic and psychological underpinnings of this hypothesis, I contrast it with similar proposals about the signalling functions of beliefs, and I motivate several psychological and sociological predictions that could be used to distinguish it from alternative explanations of irrational group beliefs.
I clarify and defend the hypothesis that human belief formation is sensitive to social rewards an... more 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: in a species with substantial social scrutiny of beliefs, forming beliefs in a way that is sensitive to their likely effects on other agents leads to practical success. I then show how the hypothesis accommodates and unifies a range of psychological phenomena, including confabulation and rationalisation, positive illusions, and identity protective cognition.
When the costs of acquiring knowledge outweigh the benefits of possessing it, ignorance is ration... more When the costs of acquiring knowledge outweigh the benefits of possessing it, ignorance is rational. In this paper I clarify and explore a related but more neglected phenomenon: cases in which ignorance is motivated by the anticipated costs of possessing knowledge, not acquiring it. The paper has four aims. First, I describe the psychological and social factors underlying this phenomenon of motivated ignorance. Second, I describe those conditions in which it is instrumentally rational. Third, I draw on evidence from the social sciences to argue that this phenomenon of rational motivated ignorance plays an important but often unappreciated role in one of the most socially harmful forms of ignorance today: voter ignorance of societal risks such as climate change. Finally, I consider how to address the high social costs associated with rational motivated ignorance.
British Journal for the Philosophy of Science , 2019
A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to... more A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to model information processing within the brain. Many theorists have noted that this research seems to be in tension with a large body of experimental results purportedly documenting systematic deviations from Bayesian updating in human belief formation. In response, proponents of the Bayesian brain hypothesis contend that Bayesian models can accommodate such results by making suitable assumptions about model parameters (for example, priors, likelihoods, and utility functions). To make progress in this debate, I argue that it is fruitful to focus not on specific experimental results but rather on what I call the 'sources of epistemic irrationality' in human cognition. I identify four such sources and I explore whether and, if so, how Bayesian models can be reconciled with them: (1) processing costs; (2) evolutionary suboptimality; (3) motivated cognition; and (4) error management.
Recent research in cognitive and computational neuroscience portrays the neocortex as a hierarchi... more Recent research in cognitive and computational neuroscience portrays the neocortex as a hierarchically structured prediction machine. Several theorists have drawn on this research to challenge the traditional distinction between perception and cognition—specifically, to challenge the very idea that perception and cognition constitute useful kinds from the perspective of cognitive neuroscience. In place of this traditional taxonomy, such theorists advocate a unified inferential hierarchy subject to substantial bi-directional message passing. I outline the nature of this challenge and then raise two objections to the cognitive architecture it proposes as a replacement: first, standard ways of characterising this inferential hierarchy are in tension with the representational reach of conceptual thought; second, there is compelling evidence that commonsense reasoning is structured around highly domain-specific intuitive theories that are difficult to situate within a single hierarchy.
We argue that one important aspect of the "cognitive neuroscience revolution" identified by Boone... more We argue that one important aspect of the "cognitive neuroscience revolution" identified by Boone and Piccinini (2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both "from below" and "from above" — that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves ("from below"), and from a greater appreciation of the problems solved by bio-cognitive systems, chiefly regulation and prediction ("from above"). We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of (predictive) dynamical models as a central postulate in neurocognitive research.
Researchers in the field of computational psychiatry have recently sought to model the formation ... more Researchers in the field of computational psychiatry have recently sought to model the formation and retention of
delusions in terms of dysfunctions in a process of hierarchical Bayesian inference. I present a systematic review of
such models and raise two challenges that have not received sufficient attention in the literature. First, the
characteristic that is supposed to most sharply distinguish hierarchical Bayesian models from their competitors is their
abandonment of the distinction between perception and cognition in favour of a unified inferential hierarchy. Standard
ways of characterising this hierarchy, however, are inconsistent with the range of phenomena that delusions can
represent. Second, there is little evidence that belief fixation in the healthy population is Bayesian, and an abundance of evidence that it is not. Given this, attempts to model delusions in terms of dysfunctions in a process of
Bayesian inference are of dubious theoretical value.
Predictive processing has recently been advanced as a global cognitive architecture for the brain... more Predictive processing has recently been advanced as a global cognitive architecture for the brain. I argue that its commitments concerning the nature and format of cognitive representation are unable to account for two basic characteristics of conceptual thought: first, its generality--the fact that we can think and flexibly reason about phenomena at any level of spatiotemporal scale and abstraction; second, its rich compositionality--the specific way in which concepts productively combine to yield our thoughts. I consider two strategies for avoiding these objections and I argue that both confront formidable challenges.
I identify three lessons from Kenneth Craik's landmark book "The Nature of Explanation" for conte... more I identify three lessons from Kenneth Craik's landmark book "The Nature of Explanation" for contemporary debates surrounding the existence, importance, and nature of mental representation: first, an account of mental representations as neural structures that function analogously to public models; second, an appreciation of prediction as the central component of intelligence in demand of such models; and third, a metaphor for understanding the brain as an engineer, not a scientist. I then relate these insights to discussions surrounding the representational status of predictive processing—which, I argue, provides a contemporary vindication of Craik's extremely prescient "hypothesis on the nature of thought."
Clark has recently suggested that predictive processing advances a theory of neural function with... more Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the ''representation wars'' of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing's account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based representational architecture with organism-relative contents that functions in the service of pragmatic success, not veridical representation. Finally , I argue that internal representation so understood is either impervious to the three anti-representationalist challenges I outline or can actively embrace them.
Predictive processing and its apparent commitment to explaining cognition in terms of Bayesian in... more Predictive processing and its apparent commitment to explaining cognition in terms of Bayesian inference over hierarchical generative models seems to flatly contradict the pragmatist conception of mind and experience. Against this, I argue that this appearance results from philosophical overlays at odd with the science itself, and that the two frameworks are in fact well-poised for mutually beneficial theoretical exchange. Specifically, I argue: first, that predictive processing illuminates pragmatism's commitment to both the primacy of pragmatic coping in accounts of the mind and the profound organism-relativity of experience; second, that this pragmatic, narcissistic character of prediction error minimization undermines its ability to explain the distinctive normativity of intentionality; and third, that predictive processing therefore mandates an extra-neural account of intentional content of exactly the sort that pragmatism's communitarian vision of human thought can provide.
Book Reviews by Daniel Williams
Philosophical Psychology
Much of contemporary philosophy assumes a close connection between thought and language. It is wi... more Much of contemporary philosophy assumes a close connection between thought and language. It is widely assumed, for example, that the structural units, semantic properties, and forms of reasoning associated with language-like systems of representation are adequate tools with which to characterise the nature of cognition. Sometimes this assumption is made explicit, as with the popular idea that thought literally occurs in a lingua mentis, an in-the-head symbol system with a combinatorial syntax and semantics . But it is also implicit in the kinds of investigations that characterise core areas of semantics, epistemology, and the philosophy of mind. As Steven Horst (2016) notes in his excellent new book, "Cognitive Pluralism", these investigations typically assume that thought plays out among units of only three "sizes": word-sized concepts, sentence-sized intentional states, and argument-sized inferences -"a three-tiered picture of the elements of our cognitive architecture whose predominant features are conspicuously modelled on those of a language" (5). 1
Thesis by Daniel Williams
I outline and defend a theory of mental representation based on three ideas that I extract from t... more I outline and defend a theory of mental representation based on three ideas that I extract from the work of the mid-twentieth century philosopher, psychologist, and cybernetician Kenneth Craik: first, an account of mental representation in terms of idealised models that capitalize on structural similarity to their targets; second, an appreciation of prediction as the core function of such models; and third, a regulatory understanding of brain function. I clarify and elaborate on each of these ideas, relate them to contemporary advances in neuroscience and machine learning, and favourably contrast a predictive model-based theory of mental representation with other prominent accounts of the nature, importance, and functions of mental representations in cognitive science and philosophy.
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Drafts by Daniel Williams
Papers by Daniel Williams
delusions in terms of dysfunctions in a process of hierarchical Bayesian inference. I present a systematic review of
such models and raise two challenges that have not received sufficient attention in the literature. First, the
characteristic that is supposed to most sharply distinguish hierarchical Bayesian models from their competitors is their
abandonment of the distinction between perception and cognition in favour of a unified inferential hierarchy. Standard
ways of characterising this hierarchy, however, are inconsistent with the range of phenomena that delusions can
represent. Second, there is little evidence that belief fixation in the healthy population is Bayesian, and an abundance of evidence that it is not. Given this, attempts to model delusions in terms of dysfunctions in a process of
Bayesian inference are of dubious theoretical value.
Book Reviews by Daniel Williams
Thesis by Daniel Williams
delusions in terms of dysfunctions in a process of hierarchical Bayesian inference. I present a systematic review of
such models and raise two challenges that have not received sufficient attention in the literature. First, the
characteristic that is supposed to most sharply distinguish hierarchical Bayesian models from their competitors is their
abandonment of the distinction between perception and cognition in favour of a unified inferential hierarchy. Standard
ways of characterising this hierarchy, however, are inconsistent with the range of phenomena that delusions can
represent. Second, there is little evidence that belief fixation in the healthy population is Bayesian, and an abundance of evidence that it is not. Given this, attempts to model delusions in terms of dysfunctions in a process of
Bayesian inference are of dubious theoretical value.