Wegner (Wegner, D. (2002). The illusion of conscious will. MIT Press) argues that conscious will is an illusion, citing a wide range of empirical evidence. I shall begin by surveying some of his arguments. Many are unsuccessful. But one—an argument from the ubiquity of self-interpretation—is more promising. Yet is suffers from an obvious lacuna, offered by so-called ‘dual process’ theories of reasoning and decision making (Evans, J., & Over, D. (1996). Rationality and reasoning. Psychology Press; Stanovich, K. (1999). Who is (...) rational? Studies of individual differences in reasoning. Lawrence Erlbaum; Frankish, K. (2004). Mind and supermind. Cambridge University Press). I shall argue that this lacuna can be filled by a plausible a priori claim about the causal role of anything deserving to be called ‘a will.’ The result is that there is no such thing as conscious willing: conscious will is, indeed, an illusion. (shrink)

This paper explores a variety of different versions of the thesis that natural language is involved in human thinking. It distinguishes amongst strong and weak forms of this thesis, dismissing some as implausibly strong and others as uninterestingly weak. Strong forms dismissed include the view that language is conceptually necessary for thought (endorsed by many philosophers) and the view that language is _de facto_ the medium of all human conceptual thinking (endorsed by many philosophers and social scientists). Weak forms include (...) the view that language is necessary for the acquisition of many human concepts, and the view that language can serve to scaffold human thought processes. The paper also discusses the thesis that language may be the medium of _conscious_ propositional thinking, but argues that this cannot be its most fundamental cognitive role. The idea is then proposed that natural language is the medium for non-domain-specific thinking, serving to integrate the outputs of a variety of domain-specific conceptual faculties (or central-cognitive ‘quasi-modules’). Recent experimental evidence in support of this idea is reviewed, and the implications of the idea are discussed, especially for our conception of the architecture of human cognition. Finally, some further kinds of evidence which might serve to corroborate or refute the hypothesis are mentioned. The overall goal of the paper is to review a wide variety of accounts of the cognitive function of natural language, integrating a number of different kinds of evidence and theoretical consideration in order to propose and elaborate the most plausible candidate. (shrink)

Empirical work on motivated reasoning suggests that our judgments are influenced to a surprising extent by our wants, desires and preferences (Kahan 2016; Lord, Ross, and Lepper 1979; Molden and Higgins 2012; Taber and Lodge 2006). How should we evaluate the epistemic status of beliefs formed through motivated reasoning? For example, are such beliefs epistemically justified? Are they candidates for knowledge? In liberal democracies, these questions are increasingly controversial as well as politically timely (Beebe et al. 2018; Lynch forthcoming, 2018; (...) Slothuus and de Vreese 2010). And yet, the epistemological significance of motivated reasoning has been almost entirely ignored by those working in mainstream epistemology. We aim to rectify this oversight. Using politically motivated reasoning as a case study, we show how motivated reasoning gives rise to three distinct kinds of skeptical challenges. We conclude by showing how the skeptical import of motivated reasoning has some important ramifications for how we should think about the demands of intellectual humility. (shrink)

This paper argues that two of my critics (Cowie and Wilson) have become fixated on Fodor’s notion of modularity, both to their own detriment and to the detriment of their understanding of Carruthers, 2006. The paper then focuses on the supposed inadequacies of the latter’s explanations of both content flexibility and human uniqueness, alleged by Machery and Cowie respectively.

Four different accounts of the relationship between third-person mindreading and first-person metacognition are compared and evaluated. While three of them endorse the existence of introspection for propositional attitudes, the fourth (defended here) claims that our knowledge of our own attitudes results from turning our mindreading capacities upon ourselves. Section 1 of this target article introduces the four accounts. Section 2 develops the “mindreading is prior” model in more detail, showing how it predicts introspection for perceptual and quasi-perceptual (e.g., imagistic) mental (...) events while claiming that metacognitive access to our own attitudes always results from swift unconscious self-interpretation. This section also considers the model's relationship to the expression of attitudes in speech. Section 3 argues that the commonsense belief in the existence of introspection should be given no weight. Section 4 argues briefly that data from childhood development are of no help in resolving this debate. Section 5 considers the evolutionary claims to which the different accounts are committed, and argues that the three introspective views make predictions that are not borne out by the data. Section 6 examines the extensive evidence that people often confabulate when self-attributing attitudes. Section 7 considers “two systems” accounts of human thinking and reasoning, arguing that although there are introspectableeventswithin System 2, there are no introspectableattitudes. Section 8 examines alleged evidence of “unsymbolized thinking”. Section 9 considers the claim that schizophrenia exhibits a dissociation between mindreading and metacognition. Finally, section 10 evaluates the claim that autism presents a dissociation in the opposite direction, of metacognition without mindreading. (shrink)

Wolfgang Spohn’s Frege prize lecture, like the work on which it is based, is a tour de force of rich, elegant, coherent argument about how the projected world that we experience is constructed. But we do not live in this projected world nor reason about it. The things Spohn constructs are there from the start—or so my Stanford School pragmatism teaches. This paper explores a deep difference in philosophical approaches—Spohn’s elegant proofs versus the stocky, tangled arguments I advocate—and illustrates how (...) these play out in far more detailed disputes about the nature of causality and causal inference. (shrink)

To explain agent-identification behaviours, universalist theories in the biological and cognitive sciences have posited mental mechanisms thought to be universal to all humans, such as agent detection and face recognition mechanisms. These universalist theories have paid little attention to how particular sociocultural or historical contexts interact with the psychobiological processes of agent-identification. In contrast to universalist theories, contextualist theories appeal to particular historical and sociocultural contexts for explaining agent-identification. Contextualist theories tend to adopt idiographic methods aimed at recording the heterogeneity (...) of human behaviours across history, space, and cultures. Defenders of the universalist approach tend to criticise idiographic methods because such methods can lead to relativism or may lack generality. To overcome explanatory limitations of proposals that adopt either universalist or contextualist approaches in isolation, I propose a philosophical model that integrates contributions from both traditions: the psycho-historical theory of agent-identification. This theory investigates how the tracking processes that humans use for identifying agents interact with the unique socio-historical contexts that support agent-identification practices. In integrating hypotheses about the history of agents with psychological and epistemological principles regarding agent-identification, the theory can generate novel hypotheses regarding the distinction between recognition-based, heuristic-based, and explanation-based agent-identification. (shrink)

Neuromoral theorists are those who claim that a scientific understanding of moral judgment through the methods of psychology, neuroscience and related disciplines can have normative implications and can be used to improve the human ability to make moral judgments. We consider three neuromoral theories: one suggested by Gazzaniga, one put forward by Gigerenzer, and one developed by Greene. By contrasting these theories we reveal some of the fundamental issues that neuromoral theories in general have to address. One important issue concerns (...) whether the normative claims that neuromoral theorists would like to make are to be understood in moral terms or in non-moral terms. We argue that, on either a moral or a non-moral interpretation of these claims, neuromoral theories face serious problems. Therefore, neither the moral nor the non-moral reading of the normative claims makes them philosophically viable. (shrink)

Our programmatic article on Homo heuristicus (Gigerenzer & Brighton, 2009) included a methodological section specifying three minimum criteria for testing heuristics: competitive tests, individual-level tests, and tests of adaptive selection of heuristics. Using Richter and Späth’s (2006) study on the recognition heuristic, we illustrated how violations of these criteria can lead to unsupported conclusions. In their comment, Hilbig and Richter conduct a reanalysis, but again without competitive testing. They neither test nor specify the compensatory model of inference they argue for. (...) Instead, they test whether participants use the recognition heuristic in an unrealistic 100% (or 96%) of cases, report that only some people exhibit this level of consistency, and conclude that most people would follow a compensatory strategy. We know of no model of judgment that predicts 96% correctly. The curious methodological practice of adopting an unrealistic measure of success to argue against a competing model, and to interpret such a finding as a triumph for a preferred but unspecified model, can only hinder progress. Marewski, Gaissmaier, Schooler, Goldstein, and Gigerenzer (2010), in contrast, specified five compensatory models, compared them with the recognition heuristic, and found that the recognition heuristic predicted inferences most accurately. (shrink)

Bayesian reasoning, defined here as the updating of a posterior probability following new information, has historically been problematic for humans. Classic psychology experiments have tested human Bayesian reasoning through the use of word problems and have evaluated each participant’s performance against the normatively correct answer provided by Bayes’ theorem. The standard finding is of generally poor performance. Over the past two decades, though, progress has been made on how to improve Bayesian reasoning. Most notably, research has demonstrated that the use (...) of frequencies in a natural sampling framework —as opposed to single-event probabilities—can improve participants’ Bayesian estimates. Furthermore, pictorial aids and certain individual difference factors also can play significant roles in Bayesian reasoning success. The mechanics of how to build tasks which show these improvements is not under much debate. The explanations for why naturally-sampled frequencies and pictures help Bayesian reasoning remain hotly contested, however, with many researchers falling into ingrained “camps” organized around two dominant theoretical perspectives. The present paper evaluates the merits of these theoretical perspectives, including the weight of empirical evidence, theoretical coherence, and predictive power. By these criteria, the ecological rationality approach is clearly better than the heuristics and biases view. Progress in the study of Bayesian reasoning will depend on continued research that honestly, vigorously, and consistently engages across these different theoretical accounts rather than staying “siloed” within one particular perspective. The process of science requires an understanding of competing points of view, with the ultimate goal being integration. (shrink)

The domain of “folk-economics” consists in explicit beliefs about the economy held by laypeople, untrained in economics, about such topics as, for example, the causes of the wealth of nations, the benefits or drawbacks of markets and international trade, the effects of regulation, the origins of inequality, the connection between work and wages, the economic consequences of immigration, or the possible causes of unemployment. These beliefs are crucial in forming people's political beliefs and in shaping their reception of different policies. (...) Yet, they often conflict with elementary principles of economic theory and are often described as the consequences of ignorance, irrationality, or specific biases. As we will argue, these past perspectives fail to predict the particular contents of popular folk-economic beliefs and, as a result, there is no systematic study of the cognitive factors involved in their emergence and cultural success. Here we propose that the cultural success of particular beliefs about the economy is predictable if we consider the influence of specialized, largely automatic inference systems that evolved as adaptations to ancestral human small-scale sociality. These systems, for which there is independent evidence, include free-rider detection, fairness-based partner choice, ownership intuitions, coalitional psychology, and more. Information about modern mass-market conditions activates these specific inference systems, resulting in particular intuitions, for example, that impersonal transactions are dangerous or that international trade is a zero-sum game. These intuitions in turn make specific policy proposals more likely than others to become intuitively compelling, and, as a consequence, exert a crucial influence on political choices. (shrink)

What makes beliefs thrive? In this paper, we model the dissemination of bona fide science versus pseudoscience, making use of Dan Sperber's epidemiological model of representations. Drawing on cognitive research on the roots of irrational beliefs and the institutional arrangement of science, we explain the dissemination of beliefs in terms of their salience to human cognition and their ability to adapt to specific cultural ecologies. By contrasting the cultural development of science and pseudoscience along a number of dimensions, we gain (...) a better understanding of their underlying epistemic differences. Pseudoscience can achieve widespread acceptance by tapping into evolved cognitive mechanisms, thus sacrificing intellectual integrity for intuitive appeal. Science, by contrast, defies those deeply held intuitions precisely because it is institutionally arranged to track objective patterns in the world, and the world does not care much about our intuitions. In light of these differences, we discuss the degree of openness or resilience to conceptual change (evidence and reason), and the divergent ways in which science and pseudoscience can achieve cultural “success”. (shrink)

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, the (...) analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an opportunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would suggest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to implement novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engineering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engineering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms. (shrink)

Does conscious reflection lead to good decision-making? Whereas engaging in reflection is traditionally thought to be the best way to make wise choices, recent psychological evidence undermines the role of reflection in lay and expert judgement. The literature suggests that thinking about reasons does not improve the choices people make, and that experts do not engage in reflection, but base their judgements on intuition, often shaped by extensive previous experience. Can we square the traditional accounts of wisdom with the results (...) of these empirical studies? Should we even attempt to? I shall defend the view that philosophy and cognitive sciences genuinely interact in tackling questions such as whether reflection leads to making wise choices. (shrink)

In binary choice between discrete outcome lotteries, an individual may prefer lottery L1 to lottery L2 when the probability that L1 delivers a better outcome than L2 is higher than the probability that L2 delivers a better outcome than L1. Such a preference can be rationalized by three standard axioms (solvability, convexity and symmetry) and one less standard axiom (a fanning-in). A preference for the most probable winner can be represented by a skew-symmetric bilinear utility function. Such a utility function (...) has the structure of a regret theory when lottery outcomes are perceived as ordinal and the assumption of regret aversion is replaced with a preference for a win. The empirical evidence supporting the proposed system of axioms is discussed. (shrink)

A heuristic is a rule of thumb. In psychology, heuristics are relatively simple rules for making judgments. A fast heuristic is easy to use and allows one to make judgments quickly. A frugal heuristic relies on a small fraction of the available evidence in making judgments. Typically, fast and frugal heuristics (FFHs) have, or are claimed to have, a further property: They are very reliable, yielding judgments that are about as accurate in the long run as ideal non-fast, non-frugal rules. (...) This paper introduces some well-known examples of FFHs, raises some objections to the FFH program, and looks at the implications of those parts of the FFH program about which we can have some reasonable degree of confidence. (shrink)

Empirical adequacy matters directly - as it does for antirealists - if we aim to get all or most of the observable facts right, or indirectly - as it does for realists - as a symptom that the claims we make about the theoretical facts are right. But why should getting the facts - either theoretical or empirical - right be required of an acceptable theory? Here we endorse two other jobs that good theories are expected to do: helping us (...) with a) understanding and b) managing the world. Both are of equal, often greater, importance than getting a swathe of facts right, and empirical adequacy fares badly in both. It is not needed for doing these jobs and in many cases it gets in the way of doing them efficiently. (shrink)

Rationality in decision making is commonly assessed by comparing choice performance against normative standards. We argue that such a performance-centered approach blurs the distinction between rational choice and adaptive behavior. Instead, rational choice should be assessed with regard to the way individuals make analytic decisions. We suggest that analytic decisions can be made in two different modes in which control processes are directed at different levels. In a RUN mode, thought is directed at controlling the operation of a decision strategy. (...) In the JUMP mode, the individual analyses the interpretation of the decision situation as well as the appropriateness of alternative strategies. We suggest that a decision should be considered “rational” when an individual is able to switch between these modes and balance their interaction. (shrink)

This paper focuses on tacit versus explicit uses of plural performance metrics as a primary methodological characteristic. This characteristic usefully distinguishes two schools of normative analysis and their approaches to normative interpretations of bounded rationality. Both schools of thought make normative claims about bounded rationality by comparing the performance of decision procedures using more than one performance metric. The consistency school makes tacit reference to performance metrics outside its primary axiomatic framework, but lexicographically promotes internal axiomatic consistency as the primary, (...) and in most cases sufficient, normative outcome with which to undertake welfare comparisons. The consistency school's axiomatization program, in both neoclassical and behavioral forms, pre-commits to welfare interpretations that follow a hierarchy of rationalities based on the stringency of restrictions that different axiomatizations impose on choice data. In contrast, the ecological rational.. (shrink)

We investigate 1 factor that influences the success of ideas or cultural representations by proposing that they have a habitat, that is, a set of environmental cues that encourages people to recall and transmit them. We test 2 hypotheses: (a) fluctuation: the success of an idea will vary over time with fluctuations in its habitat, and (b) competition: ideas with more prevalent habitats will be more successful. Four studies use subject ratings and data from newspapers to provide correlational support for (...) our 2 hypotheses, with a negative factoid, positive rumor, catchphrases, and variants of a proverb. Three additional experimental studies manipulate the topic of actual conversations and find empirical support for our theory, with catchphrases, proverbs, and slang. The discussion examines how habitat prevalence applies to a more extensive class of ideas and suggests how habitats may influence the process by which ideas evolve. (shrink)

Given free information and unlimited processing power, should decision algorithms use as much information as possible? A formal model of the decision-making environment is developed to address this question and provide conditions under which informationally frugal algorithms, without any information or processing costs whatsoever, are optimal. One cause of compression that allows optimal algorithms to rationally ignore information is inverse movement of payoffs and probabilities (e.g., high payoffs occur with low probably and low payoffs occur with high probability). If inversely (...) related payoffs and probabilities cancel out, then predictors that correlate with payoffs and consequently condition the probabilities associated with different payoffs will drop out of the expected-payoff objective function, severing the link between information and optimal action rules. Stochastic payoff processes in which rational ignoring occurs are referred to as compressed environments, because optimal action depends on a reduced-dimension subset of the environmental parameters. This paper considers benefits and limitations of economic models versus other methods for studying links between environmental structure and the real-world success of simple decision procedures. Different methods converge on the normative proposition of ecological rationality, as opposed to axiomatic rationality based on informational efficiency and internal consistency axioms, as a superior framework for comparing the effectiveness of decision strategies and prescribing decision algorithms in application. (shrink)

The existence of superstition and religious beliefs in most, if not all, human societies is puzzling for behavioral ecology. These phenomena bring about various fitness costs ranging from burial objects to celibacy, and these costs are not outweighed by any obvious benefits. In an attempt to resolve this problem, we present a verbal model describing how humans and other organisms learn from the observation of coincidence (associative learning). As in statistical analysis, learning organisms need rules to distinguish between real patterns (...) and randomness. These rules, which we argue are equivalent to setting the level of α for rejection of the null hypothesis in statistics, are governed by risk management as well as by comparison to previous experiences. Risk management means that the cost of a possible type I error (superstition) has to be traded off against the cost of a possible type II error (ignorance). This trade-off implies that the occurrence of superstitious beliefs is an inevitable consequence of an organism’s ability to learn from observation of coincidence. Comparison with previous experiences (as in Bayesian statistics) improves the chances of making the right decision. While this Bayesian approach is found in most learning organisms, humans have evolved a unique ability to judge from experiences whether a candidate subject has the power to mechanistically cause the observed effect. Such “strong” causal thinking evolved because it allowed humans to understand and manipulate their environment. Strong causal thinking, however, involves the generation of hypotheses about underlying mechanisms (i.e., beliefs). Assuming that natural selection has favored individuals that learn quicker and more successfully than others owing to (1) active search to detect patterns and (2) the desire to explain these patterns mechanistically, we suggest that superstition has evolved as a by-product of the first, and that belief has evolved as a by-product of the second. (shrink)

People’s beliefs about normality play an important role in many aspects of cognition and life (e.g., causal cognition, linguistic semantics, cooperative behavior). But how do people determine what sorts of things are normal in the first place? Past research has studied both people’s representations of statistical norms (e.g., the average) and their representations of prescriptive norms (e.g., the ideal). Four studies suggest that people’s notion of normality incorporates both of these types of norms. In particular, people’s representations of what is (...) normal were found to be influenced both by what they believed to be descriptively average and by what they believed to be prescriptively ideal. This is shown across three domains: people’s use of the word ‘‘normal” (Study 1), their use of gradable adjectives (Study 2), and their judgments of concept prototypicality (Study 3). A final study investigated the learning of normality for a novel category, showing that people actively combine statistical and prescriptive information they have learned into an undifferentiated notion of what is normal (Study 4). Taken together, these findings may help to explain how moral norms impact the acquisition of normality and, conversely, how normality impacts the acquisition of moral norms. (shrink)

The phenomenon of base-rate neglect has elicited much debate. One arena of debate concerns how people make judgments under conditions of uncertainty. Another more controversial arena concerns human rationality. In this target article, we attempt to unpack the perspectives in the literature on both kinds of issues and evaluate their ability to explain existing data and their conceptual coherence. From this evaluation we conclude that the best account of the data should be framed in terms of a dual-process model of (...) judgment, which attributes base-rate neglect to associative judgment strategies that fail to adequately represent the set structure of the problem. Base-rate neglect is reduced when problems are presented in a format that affords accurate representation in terms of nested sets of individuals. (shrink)

. Evolutionary psychology and behavioural genomics are both approaches to explain human behaviour from a genetic point of view. Nonetheless, thus far the development of these disciplines is anything but interdependent. This paper examines the question whether evolutionary psychology can contribute to behavioural genomics. Firstly, a possible inconsistency between the two approaches is reviewed, viz. that evolutionary psychology focuses on the universal human nature and disregards the genetic variation studied by behavioural genomics. Secondly, we will discuss the structure of biological (...) explanations. Some philosophers rightly acknowledge that explanations do not involve laws which are exceptionless and universal. Instead, generalisations that are invariant suffice for successful explanation as long as two other stipulations are recognised: the domain within which the generalisation has no exceptions as well as the distribution of the mechanism described by the generalisation should both be specified. It is argued that evolutionary psychology can contribute to behavioural genomic explanations by accounting for these two specifications. (shrink)

Orthodox decision theory gives no advice to agents who hold two goods to be incommensurate in value because such agents will have incomplete preferences. According to standard treatments, rationality requires complete preferences, so such agents are irrational. Experience shows, however, that incomplete preferences are ubiquitous in ordinary life. In this paper, we aim to do two things: (1) show that there is a good case for revising decision theory so as to allow it to apply non-vacuously to agents with incomplete (...) preferences, and (2) to identify one substantive criterion that any such non-standard decision theory must obey. Our criterion, Competitiveness, is a weaker version of a dominance principle. Despite its modesty, Competitiveness is incompatible with prospectism, a recently developed decision theory for agents with incomplete preferences. We spend the final part of the paper showing why Competitiveness should be retained, and prospectism rejected. (shrink)

In response to Stephen Neale (2016), I argue that aphonic expressions, such as PRO, are intentionally uttered by normal speakers of natural language, either by acts of omitting to say something explicitly, or by acts of giving phonetic realization to aphonics. I argue, also, that Gricean intention-based semantics should seek divorce from Cartesian assumptions of transparent access to propositional attitudes and, consequently, that Stephen Schiffer's so-called meaning-intention problem is not powerful enough to banish alleged cases of over-intellectualization in contemporary philosophy (...) of language and mind. (shrink)

Many philosophers and cognitive scientists claim that our everyday or "folk" understanding of mental states constitutes a theory of mind. That theory is widely called "folk psychology" (sometimes "commonsense" psychology). The terms in which folk psychology is couched are the familiar ones of "belief" and "desire", "hunger", "pain" and so forth. According to many theorists, folk psychology plays a central role in our capacity to predict and explain the behavior of ourselves and others. However, the nature and status of folk (...) psychology remains controversial. (shrink)

A long tradition of psychological research has explored the distinction between characteristics that are part of the self and those that lie outside of it. Recently, a surge of research has begun examining a further distinction. Even among characteristics that are internal to the self, people pick out a subset as belonging to the true self. These factors are judged as making people who they really are, deep down. In this paper, we introduce the concept of the true self and (...) identify features that distinguish people’s understanding of the true self from their understanding of the self more generally. In particular, we consider recent findings that the true self is perceived as positive and moral, and that this tendency is actor-observer invariant and cross-culturally stable. We then explore possible explanations for these findings and discuss their implications for a variety of issues in psychology. (shrink)

Understanding the folk notion of free will and moral responsibility is important for a host of applied and theoretical issues in psychology, philosophy, and ethics. The bulk of experimental research has focused on folk intuitions concerning determinism's relation to free will and moral responsibility. However, determinism is a difficult term for many folk to understand. Accordingly researchers often use comprehension questions to identify and exclude large proportions of participants who seem to struggle with relevant concepts. Here, we document some of (...) the cognitive mechanisms involved in folk judgments related to comprehension of determinism, and its relations to free will and moral responsibility. Results provide prescriptions for experimental designs that can increase comprehension, potentially decreasing sampling biases. Theoretical and methodological implications are discussed. (shrink)

This thesis aims to develop a psychologically plausible account of concepts by integrating key insights from philosophy (on the metaphysical basis for concept possession) and psychology (on the mechanisms underlying concept acquisition). I adopt an approach known as informational atomism, developed by Jerry Fodor. Informational atomism is the conjunction of two theses: (i) informational semantics, according to which conceptual content is constituted exhaustively by nomological mind–world relations; and (ii) conceptual atomism, according to which (lexical) concepts have no internal structure. I (...) argue that informational semantics needs to be supplemented by allowing content-constitutive rules of inference (“meaning postulates”). This is because the content of one important class of concepts, the logical terms, is not plausibly informational. And since, it is argued, no principled distinction can be drawn between logical concepts and the rest, the problem that this raises is a general one. An immediate difficulty is that Quine’s classic arguments against the analytic/synthetic distinction suggest that there can be no principled basis for distinguishing content-constitutive rules from the rest. I show that this concern can be overcome by taking a psychological approach: there is a fact of the matter as to whether or not a particular inference is governed by a mentally-represented inference rule, albeit one that analytic philosophy does not have the resources to determine. I then consider the implications of this approach for concept acquisition. One mechanism underlying concept acquisition is the development of perceptual detectors for the objects that we encounter. I investigate how this might work, by drawing on recent ideas in ethology on ‘learning instincts’, and recent insights into the neurological basis for perceptual learning. What emerges is a view of concept acquisition as involving a complex interplay between innate constraints and environmental input. This supports Fodor’s recent move away from radical concept nativism: concept acquisition requires innate mechanisms, but does not require that concepts themselves be innate. (shrink)

This paper outlines a new type of skepticism that is both compatible with fallibilism and supported by work in psychology. In particular, I will argue that we often cannot properly trust our ability to rationally evaluate reasons, arguments, and evidence (a fundamental knowledge-seeking faculty). We humans are just too cognitively impaired to achieve even fallible knowledge, at least for many beliefs.

Starting from the sixties of the past century theory change has become a main concern of philosophy of science. Two of the best known formal accounts of theory change are the post-Popperian theories of verisimilitude (PPV for short) and the AGM theory of belief change (AGM for short). In this paper, we will investigate the conceptual relations between PPV and AGM and, in particular, we will ask whether the AGM rules for theory change are effective means for approaching the truth, (...) i.e., for achieving the cognitive aim of science pointed out by PPV. First, the key ideas of PPV and AGM and their application to a particular kind of propositional theories - the so called "conjunctive propositions" - will be illustrated. Afterwards, we will prove that, as far as conjunctive propositions are concerned, AGM belief change is an effective tool for approaching the truth. (shrink)

In this paper I will present an analysis of the impact that the notion of “bounded rationality”, introduced by Herbert Simon in his book “Administrative Behavior”, produced in the field of Artificial Intelligence (AI). In particular, by focusing on the field of Automated Decision Making (ADM), I will show how the introduction of the cognitive dimension into the study of choice of a rational (natural) agent, indirectly determined - in the AI field - the development of a line of research (...) aiming at the realisation of artificial systems whose decisions are based on the adoption of powerful shortcut strategies (known as heuristics) based on “satisficing” - i.e. non optimal - solutions to problem solving. I will show how the “heuristic approach” to problem solving allowed, in AI, to face problems of combinatorial complexity in real-life situations and still represents an important strategy for the design and implementation of intelligent systems. (shrink)

Naturalistic thinking and knowing, the tacit, experiential, and intuitive reasoning of everyday interaction, have long been regarded as inferior to formal reason and labeled primitive, fallible, subjective, superstitious, and in some cases ineffable. But, naturalistic thinking is more rational and definable than it appears. It is also relevant to design. Inquiry into the mechanisms of naturalistic thinking and knowledge can bring its resources into focus and enable designers to create better, human-centered designs for use in real-world settings. This article makes (...) a case for the explicit, formal study of implicit, naturalistic thinking within the fields of design. It develops a framework for defining and studying naturalistic thinking and knowledge, for integrating them into design research and practice, and for developing a more integrated, consistent theory of knowledge in design. It will (a) outline historical definitions of knowledge, attitudes toward formal and naturalistic thinking, and the difficulties presented by the co-presence of formal and naturalistic thinking in design, (b) define and contrast formal and naturalistic thinking as two distinct human cognitive systems, (c) demonstrate the importance of naturalistic cognition in formal thinking and real-world judgment, (d) demonstrate methods for researching naturalistic thinking that can be of use in design, and (e) briefly discuss the impact on design theory of admitting naturalistic thinking as valid, systematic, and knowable. (shrink)

This paper presents a practical case study showing how, despite the nowadays limited collaboration between AI and Cognitive Science (CogSci), cognitive research can still have an important role in the development of novel AI technologies. After a brief historical introduction about the reasons of the divorce between AI and CogSci research agendas (happened in the mid’80s of the last century), we try to provide evidence of a renewed collaboration by showing a recent case study on a commonsense reasoning system, built (...) by using insights from cognitive semantics. (shrink)

We overview the main historical and technological elements characterising the rise, the fall and the recent renaissance of the cognitive approaches to Artificial Intelligence and provide some insights and suggestions about the future directions and challenges that, in our opinion, this discipline needs to face in the next years.

Spontaneous actions are preceded by brain signals that may sometimes be detected hundreds of milliseconds in advance of a subject's conscious intention to act. These signals have been claimed to reflect prior unconscious decisions, raising doubts about the causal role of conscious will. Murakami et al. (2014. Nat Neurosci 17: 1574–1582) have recently argued for a different interpretation. During a task in which rats spontaneously decided when to abort waiting, the authors recorded neurons in the secondary motor cortex. The neural (...) activity and relationship to action timing was parsimoniously explained using an integration-to-bound model, similar to those widely used to account for evidence-based decisions. In this model, the brain accumulates spontaneously occurring inputs voting for or against an action, but only commits to act once a certain threshold is crossed. The model explains how spontaneous decisions can be forecast (partially predicted) by neurons that reflect either the input or output of the integrator. It therefore presents an explicit hypothesis capable of rejecting the claim that such predictive signals imply unconscious decisions. We suggest that these results can inform the current debate on free will but must be considered with caution. (shrink)

This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is an important (...) aspect of human intelligence. For this task, in fact, humans adopt a wide range of heuristics (Gigerenzer & Todd) due to their “bounded rationality” (Simon, 1957). In this perspective, one of the requirements that should be considered for the design, the realization and the evaluation of intelligent cognitively-inspired systems should be rep- resented by their ability of heuristically identify and retrieve, from the general knowledge stored in their artificial Long Term Memory (LTM), that one which is synthetically and contextually relevant. This requirement, however, is often neglected. Currently, artificial cognitive systems and architectures are not able, de facto, to deal with complex knowledge structures that can be even slightly comparable to the knowledge heuris- tically managed by humans. In this paper I will argue that this is not only a technological problem but also an epistemological one and I will briefly sketch a proposal for a possible solution. (shrink)

A theory of rationality is a theory that evaluates instances of reasoning as rational, irrational, or (ir)rational to some degree. Theories can be categorized as rule-based or consequentialist. Rule-based theories say that rational reasoning accords with certain rules (e.g., of logic or probability). Consequentialist theories say that rational reasoning tends to produce good consequences. For instance, the reliabilist takes rationality to be reasoning that tends to produce mostly true beliefs. The pragmatist takes it to be reasoning that tends to produce (...) mostly useful beliefs. This article reviews some of the features and the challenges of rule-based, reliabilist, and pragmatist theories of rationality. (shrink)