Nick Chater

University of Warwick · Warwick Business School (WBS)

Individuals make biased and variable probability judgements. Recent models such as the Bayesian Sampler and Probability Theory Plus Noise capture these effects by assuming people randomly sample events but are biased towards indifference (i.e., 0.5). However there is a bias they do not capture: systematic violations of binary complementarity, i.e.,...

We have previously argued thatbehavioral scientists have been testing and advocating individualistic (i-frame) solutions to policy problems that have systemic (s-frame) causes and require systemic solutions. Here, we consider the implications of adopting an s-frame approach for research. We argue that an s-frame approach will involve addressing dif...

Societal expectations have been found to determine which social roles people should occupy. However, so far, these beliefs have been mainly explored using implicit measures where expectation-confirming (vs. violating) judgments tend to be more efficient. The present study (N = 44) applied a novel approach – the random generation paradigm – to explo...

Recent advances in artificial intelligence (AI) have produced systems capable of increasingly sophisticated performance on cognitive tasks. However, AI systems still struggle in critical ways: unpredictable and novel environments (robustness), lack of transparency in their reasoning (explainability), challenges in communication and commitment (coop...

Elicitation methods, such as asking people to produce the deciles of a distribution, are standard practices in policy or applied statistics. Similarly, much of cognitive science and psychology focuses on determining people's people's beliefs or latent traits through questionnaires or judgment tasks. However, these approaches often only capture a ro...

It is widely agreed upon that morality guides people with conflicting interests towards agreements of mutual benefit. We therefore might expect numerous proposals for organizing human moral cognition around the logic of bargaining, negotiation, and agreement. Yet, while “contractualist” ideas play an important role in moral philosophy, they are sta...

The categorization of complex real-world stimuli, such as facial expressions, appears to vary greatly between people. This raises a crucial methodological challenge: how is it possible to elicit the mental representation of a complex category for a specific individual? Comprehensive category-elicitation methods such as Markov Chain Monte Carlo with...

Repeated forecasts of changing values are common in many everyday tasks, from predicting the weather to financial markets. A particularly simple and informative instance of such fluctuating values are random walks: Sequences in which each point is a random movement from only its preceding value, unaffected by any previous points. Moreover, random w...

People frequently face decisions that require making inferences about withheld information. The advent of large language models coupled with conversational technology, e.g., Alexa, Siri, Cortana, and the Google Assistant, is changing the mode in which people make these inferences. We demonstrate that conversational modes of information provision, r...

People solve a myriad of coordination problems without explicit communication every day. A recent theoretical account, virtual bargaining, proposes that, to coordinate, we often simulate a negotiation process, and act according to what we would be most likely to agree to do if we were to bargain. But very often several equivalent tacit agreements —...

In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regar...

Our target article distinguishes between policy approaches that seek to address societal problems through intervention at the level of the individual (adopting the "i-frame") and those that seek to change the system within which those individuals live (adopting the "s-frame"). We stress also that a long-standing tactic of corporations opposing syst...

Normative models of decision-making that optimally transform noisy (sensory) information into categorical decisions qualitatively mismatch human behavior. Indeed, leading computational models have only achieved high empirical corroboration by adding task-specific assumptions that deviate from normative principles. In response, we offer a Bayesian a...

What is required to allow an artificial agent to engage in rich, human-like interactions with people? I argue that this will require capturing the process by which humans continually create and renegotiate ‘bargains’ with each other. These hidden negotiations will concern topics including who should do what in a particular interaction, which action...

Sampling approaches to judgment and decision making are distinct from traditional accounts in psychology and neuroscience. While these traditional accounts focus on limitations of the human mind as a major source of bounded rationality, the sampling approach originates in a broader cognitive-ecological perspective. It starts from the fundamental as...

Sampling approaches to judgment and decision making are distinct from traditional accounts in psychology and neuroscience. While these traditional accounts focus on limitations of the human mind as a major source of bounded rationality, the sampling approach originates in a broader cognitive-ecological perspective. It starts from the fundamental as...

Human probability judgments are both variable and subject to systematic biases. Most probability judgment models treat variability and bias separately: a deterministic model explains the origin of bias, to which a noise process is added to generate variability. But these accounts do not explain the characteristic inverse U-shaped signature linking...

The social-contract tradition of Hobbes, Rousseau, Kant, and Rawls has been widely influential in moral philosophy but has until recently received relatively little attention in moral psychology. For contractualist moral theories, ethics is a matter of forming, adhering to, and enforcing (hypothetical) agreements, and morality is fundamentally abou...

In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regar...

We agree with Heintz & Scott-Phillips that pragmatics does not supplement, but is prior to and underpins, language. Indeed, human non-linguistic communication is astonishingly rich, flexible, and subtle, as we illustrate through the game of charades, where people improvise communicative signals when linguistic channels are blocked. The route from n...

Effectively updating one’s beliefs requires sufficient empirical evidence (i.e., data) and the computational capacity to process it. Yet both data and computational resources are limited for human minds. Here, we study the problem of belief updating under limited data and limited computation. Using information theory to characterize constraints on...

Noise in behavior is often viewed as a nuisance: while the mind aims to take the best possible action, it is let down by unreliability in the sensory and motor systems. How researchers study cognition reflects this viewpoint - averaging over trials and participants in order to discover the deterministic relationships between experimental manipulati...

How do individual human minds create languages, legal systems, scientific theories, and technologies? From a cognitive science viewpoint, such collective phenomena may be considered a type of distributed computation in which human minds together solve computational problems beyond any individual. This viewpoint may also shift our perspective on ind...

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many...

Human cognition is fundamentally noisy. While routinely regarded as a nuisance in experimental investigation, the few studies investigating properties of cognitive noise have found surprising structure. A first line of research has shown that inter-response-time distributions are heavy-tailed. That is, response times between subsequent trials usual...

People can instantaneously create novel conventions that link individual communicative signals to meanings, both in experiments and everyday communication. Yet a basic principle of natural communication is that the meaning of a signal typically contrasts with the meanings of alternative signals that were available but not chosen. That is, communica...

One of the most robust effects in cognitive psychology is anchoring, in which judgments show a bias toward previously viewed values. However, in what is essentially the same task as used in anchoring research, a perceptual illusion demonstrates the opposite effect of repulsion. Here, we united these two literatures, testing in two experiments with...

Repeated forecasts of changing targets are a key aspect of many everyday tasks, from predicting the weather to financial markets. Random walks provide a particularly simple and informative case study, as new values represent random deviations from the preceding value only, with further previous points being irrelevant. Moreover, random walks often...

People often make, and are held to account for, purely tacit commitments in interactions with other people: commitments that have never been explicitly articulated or agreed. Moreover, unspoken, tacit commitments are often perceived as binding: people often stick to, and are expected to stick to, these commitments, even where it might seem against...

Social interaction is both ubiquitous and central to understanding human behavior. Such interactions depend, we argue, on shared intentionality: the parties must form a common understanding of an ambiguous interaction (e.g., one person giving a present to another requires that both parties appreciate that a voluntary transfer of ownership is intend...

Many proponents of behavioural public policy work within a broadly consequentialist framework. From this perspective, the ultimate aim of public policy is to maximise utility, happiness, welfare, the satisfaction of preferences, or similar; and the behavioural aspect of public policy aims to harness a knowledge of human psychology to make this maxi...

The key to explaining the many mysteries of language is to think of it as a game, say cognitive scientists Morten H. Christiansen and Nick Chater

Bayesian approaches presuppose that following the coherence conditions of probability theory makes probabi-listic judgments more accurate. But other influential theories claim accurate judgments (with high "ecological rationality") do not need to be coherent. Empirical results support these latter theories, threatening Bayesian models of intelligen...

Human beings perform well in uncertain environments, matching the performance of complex probabilistic models in complex tasks such as language or physical system prediction. Yet people’s judgments about probabilities also display well-known biases. How can this be? Recently cognitive scientists have explored the possibility that the same sampling...

Much categorization behavior can be explained by family resemblance: New items are classified by comparison with previously learned exemplars. However, categorization behavior also shows a variety of dimensional biases, where the underlying space has so-called "separable" dimensions: Ease of learning categories depends on how the stimuli align with...

Human beings perform well in uncertain environments, matching the performance of complex probabilistic models in complex tasks such as language or physical system prediction. Yet people’s judgments about probabilities also display well-known biases. How can this be? Recently cognitive scientists have explored the possibility that the same sampling...

Human-like computing will require machines to communicate interactively with people, to take in human knowledge and preferences, to explain the machine’s actions, and to generally coordinate human and machine behaviour. But even the simplest communicative interactions raise deep theoretical challenges. Human and machine spontaneously have to “agree...

Human probability judgments are variable and subject to systematic biases. Sampling-based accounts of probability judgment have successfully explained such idiosyncrasies by assuming that people remember or simulate instances of events and base their judgments on sampled frequencies. Biases have been explained either by noise corrupting sample accu...

Human cognition is fundamentally noisy. While routinely regarded as a nuisance in experimental investigation, the few studies investigating properties of cognitive noise have found surprising structure. A first line of research has shown that inter-response-time distributions are heavy-tailed. That is, response times between subsequent trials usual...

Price series in speculative markets show a common set of statistical properties, termed ‘stylised facts’. While some facts support simple efficient markets composed of homogenous rational agents (e.g., the absence of autocorrelation in price increments), others do not (e.g., heavy-tailed distributions of price changes and volatility clustering) (Ca...

Estimation, choice, confidence, and response times are the primary behavioural measures in perceptual and cognitive tasks. These measures have attracted extensive modeling efforts in the cognitive sciences, but there is the lack of a unified approach to explain all measures simultaneously within one framework. We propose an Autocorrelated Bayesian...

Contrary to common belief, our preferences do not only shape our decisions but are also shaped by what decisions we make. This effect, known as choice-induced preference change, has been extensively studied in individuals. Here we document choice-induced preference change in groups. We do so by using the choice-blindness paradigm, a method by which...

In Bayesian cognitive science, the mind is seen as a spectacular probabilistic-inference machine. But judgment and decision-making (JDM) researchers have spent half a century uncovering how dramatically and systematically people depart from rational norms. In this article, we outline recent research that opens up the possibility of an unexpected re...

The present crisis demands an all-out response if it is to be mastered with minimal damage. This means we, as the behavioural science community, need to think about how we can adapt to best support evidence-based policy in a rapidly changing, high-stakes environment. This piece is an attempt to initiate this process. The ‘recommendations’ made are...

Human probability judgments are systematically biased, in apparent tension with Bayesian models of cognition. But perhaps the brain does not represent probabilities explicitly, but approximates probabilistic calculations through a process of sampling, as used in computational probabilistic models in statistics. Naïve probability estimates can be ob...

Resource rationality is useful for choosing between models with the same cognitive constraints but cannot settle fundamental disagreements about what those constraints are. We argue that sampling is an especially compelling constraint, as optimizing accumulation of evidence or hypotheses minimizes the cost of time, and there are well-established mo...

The psychology of verbal reasoning initially compared performance with classical logic. In the last 25 years, a new paradigm has arisen, which focuses on knowledge-rich reasoning for communication and persuasion and is typically modeled using Bayesian probability theory rather than logic. This paradigm provides a new perspective on argumentation, e...

Previous research examining trust of autonomous vehicles has largely focused on holistic trust, with little work on evaluation of specific behaviours and interactions with human-controlled vehicles. Six experiments examined the influence of pull-in distance, vehicle perspective (overtaking/being overtaken), following distance and immersion on self-...

Human choice behavior shows a range of puzzling anomalies. Even simple binary choices are modified by accept/reject framing and by the presence of decoy options, and they can exhibit circular (i.e., intransitive) patterns of preferences. Each of these phenomena is incompatible with many standard models of choice but may provide crucial clues concer...

May provides a compelling case that reasoning is central to moral psychology. In practice, many morally significant decisions involve several moral agents whose actions are interdependent – and agents embedded in society. We suggest that social life and the rich patterns of reasoning that underpin it are ethical through and through.

People often make, and are held to account for, purely tacit commitments in interactions with other people: commitments which have never been explicitly articulated or agreed. Moreover, unspoken, tacit commitments are often perceived as binding: people often stick to, and are expected to stick to, these commitments, even where it might seem against...

People’s probability estimates have been used to argue that people are irrational: effects such as conservatism and the conjunction fallacy show that these estimates are inconsistent with one another, and are thus incoherent. However, recent work has shown that probability estimates are surprisingly consistent with the laws of probability theory as...

People often psychologically commit to a course of action in strategic interactions, even where it might seem irrational to do so. For example, such psychological commitments may lead people to punish counterparts who violate an unenforceable agreement (at a cost to themselves), or to cooperate in the Centipede game and the finitely repeated Prison...

Mercier and Sperber illuminate many aspects of reasoning and rationality, providing refreshing and thoughtful analysis and elegant and well‐researched illustrations. They make a good case that reasoning should be viewed as a type of intuition, rather than a separate cognitive process or system. Yet questions remain. In what sense, if any, is reason...

Language acquisition researchers have often viewed children as ‘mini-linguists,’ attempting to infer abstract knowledge of language from exposure to their native language. From this perspective, the challenge of acquisition can seem so formidable that meeting it would appear to require that much of this knowledge must be built-in, as a language ins...

Languages with many speakers tend to be structurally simple while small communities sometimes develop languages with great structural complexity. Paradoxically, the opposite pattern appears to be observed for non-structural properties of language such as vocabulary size. These apparently opposite patterns pose a challenge for theories of language c...

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called ‘trend-dam...

To drive safely among human drivers, cyclists and pedestrians, autonomous vehicles will need to mimic, or ideally improve upon, humanlike driving. Yet, driving presents us with difficult problems of joint action: 'negotiating' with other users over shared road space. We argue that autonomous driving provides a test case for computational theories o...

How do firms manage to collude without communicating? Why do we find more collusion in price competition than in quantity competition? Why is collusion so hard to detect? We examine strategic behavior in competitive interactions by developing and applying the concept of virtual bargaining. When decision makers virtually bargain, they mentally simul...

Lake et al. argue persuasively that modelling human-like intelligence requires flexible, compositional representations in order to embody world knowledge. But human knowledge is too sparse and self-contradictory to be embedded in “intuitive theories.” We argue, instead, that knowledge is grounded in exemplar-based learning and generalization, combi...

Both resources in the natural environment and concepts in a semantic space are distributed "patchily", with large gaps in between the patches. To describe people's internal and external foraging behavior, various random walk models have been proposed. In particular, internal foraging has been modeled as sampling: in order to gather relevant informa...

The evaluation of magnitudes serves as a foundation not only for numerical and mathematical cognition, but also for decision making. Recent theoretical developments and empirical studies have linked numerical magnitude evaluation to a wide variety of core phenomena in decision making and challenge the idea that preferences are driven by an innate,...

This article features an interdisciplinary debate and dialogue about the nature of mind, perception, and rationality. Scholars from a range of disciplines — cognitive science, applied and experimental psychology, behavioral economics, and biology — offer critiques and commentaries of a target article by Felin, Koenderink, and Krueger (2017): “Ratio...

People often have to make decisions based on many pieces of information. Previous work has found that people are able to integrate values presented in a rapid serial visual presentation (RSVP) stream to make informed judgements on the overall stream value (Tsetsos et al. Proceedings of the National Academy of Sciences of the United States of Americ...

Book synopsis: Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Although causal reasoning is a component of most of our...

This article introduces strategists to the Mindspace framework and explores its applications in strategic contexts. This framework consists of nine effective behavioral interventions that are grounded in public policy applications, and it focuses on how changing the context can be more effective than attempts to de-bias decision makers. Behavioral...

Conventional economic policy focuses on ‘economic’ solutions (e.g. taxes, incentives, regulation) to problems caused by market-level factors such as externalities, misaligned incentives and information asymmetries. By contrast, ‘nudges’ provide behavioural solutions to problems that have generally been assumed to originate from limitations in human...

Recent research comparing mental models theory and causal Bayes nets for their ability to account for discounting and augmentation inferences in causal conditional reasoning had some limitations. One of the experiments used an ordinal scale and multiple items and analysed the data by subjects and items. This procedure can create a variety of proble...

Humans can communicate even with few existing conventions in common (e.g., when they lack a shared language). We explored what makes this phenomenon possible with a nonlinguistic experimental task requiring participants to coordinate toward a common goal. We observed participants creating new communicative conventions using the most minimal possibl...

Bayesian explanations have swept through cognitive science over the past two decades, from intuitive physics and causal learning, to perception, motor control and language. Yet people flounder with even the simplest probability questions. What explains this apparent paradox? How can a supposedly Bayesian brain reason so poorly with probabilities? I...

Humans deviate from rational choice theory if their estimates of the attribute values for one alternative change as a function of the attribute values of competing alternatives (1). In our paper (2), we report such “context-dependent” (CD) deviations from rationality in the form of a frequent winner (FW) effect and the corresponding weak stochastic...

Book synopsis: In recent years the psychology of reasoning has undergone radical change, which can only be seen as a Kuhn-style scientific revolution. This shift has been dubbed ?New Paradigm?. For years, psychologists of reasoning focused on binary truth values and regarded the influence of belief as a bias. In contrast to this, the new paradigm p...

If human language must be squeezed through a narrow cognitive bottleneck, what are the implications for language processing, acquisition, change, and structure? In our target article, we suggested that the implications are far-reaching and form the basis of an integrated account of many apparently unconnected aspects of language and language proces...

When making a decision, humans consider two types of information: information they have acquired through their prior experience of the world, and further information they gather to support the decision in question. Here, we present evidence that data from search engines such as Google can help us model both sources of information. We show that stat...

Chapter 5 proposes that language has evolved to rely on a multitude of probabilistic information sources for its acquisition, allowing language to be as expressive as possible while still being learnable by domain- general learning mechanisms. The structure of the vocabulary is used a case study, revealing a complex relationship between systematici...

The apparently unified picture of language and language processing from classical cognitive science does not provide a compelling picture: the relationship between processing and acquisition is tenuous; language evolution seems miraculous. The standard defense of the classical picture against concerns of this kind is that it is “the only game in to...

The third chapter explores the implications of the cultural evolution of language for understanding the problem of language acquisition, which is cast in a new and much more tractable form. In essence, the child faces a problem of induction, where the objective is to coordinate with others (C-induction), rather than to model the structure of the na...

The experience-based approach to language processing suggests that our ability to generate complex syntactic structures may emerge gradually, construction by construction. This contrasts with most current approaches to linguistic structure, which suggest that our generative linguistic capacity derives from recursion as a built-in fundamental proper...