Evolutionary thinking has expanded in the last decades, spreading from its traditional stronghold – the explanation of speciation and adaptation in biology - to new domains. Fascinating pieces of work, the essays in this collection attest to the illuminating power of evolutionary thinking when applied to the understanding of the human mind. The contributors to_ Cognition, Evolution and Rationality_ use an evolutionary standpoint to approach the nature of the human mind, including both cognitive and behavioural functions. Cognitive (...) class='Hi'>science is by its nature an interdisciplinary subject and the essays in this collection investigate the workings of the mind through a variety of disciplines including the philosophy of science, the philosophy of mind, game theory, robotics and computational neuroanatomy. Topics covered range from general methodological issues to long-standing philosophical problems such as how rational human beings actually are. With contributions from leading experts in the areas involved, this book will be of interest across a number of fields, including philosophy, evolutionary theory and cognitive science. (shrink)

Evolutionary thinking has expanded in the last decades, spreading from its traditional stronghold – the explanation of speciation and adaptation in biology - to new domains. Fascinating pieces of work, the essays in this collection attest to the illuminating power of evolutionary thinking when applied to the understanding of the human mind. The contributors to_ Cognition, Evolution and Rationality_ use an evolutionary standpoint to approach the nature of the human mind, including both cognitive and behavioural functions. Cognitive (...) class='Hi'>science is by its nature an interdisciplinary subject and the essays in this collection investigate the workings of the mind through a variety of disciplines including the philosophy of science, the philosophy of mind, game theory, robotics and computational neuroanatomy. Topics covered range from general methodological issues to long-standing philosophical problems such as how rational human beings actually are. With contributions from leading experts in the areas involved, this book will be of interest across a number of fields, including philosophy, evolutionary theory and cognitive science. (shrink)

Evolutionary thinking has expanded in the last decades, spreading from its traditional stronghold - the explanation of speciation and adaptation in Biology - to new domains including the human sciences. The essays in this collection attest to the illuminating power of evolutionary thinking when applied to the understanding of the human mind. The contributors to Cognition, Evolution and Rationality use an evolutionary standpoint to approach the nature of the human mind, including both cognitive and behavioral functions. Cognitive (...) science is by its nature an interdisciplinary subject and the essays use a variety of disciplines including the Philosophy of Science, the Philosophy of Mind, Game Theory, Robotics and Computational Neuroanatomy to investigate the workings of the mind. The topics covered by the essays range from general methodological issues to long-standing philosophical problems such as how rational human beings actually are. This book will be of interest across a number of fields, including philosophy, evolutionary theory and cognitive science. (shrink)

Without Good Reason offers a clear critical account of the debate in philosophy and cognitive science about whether humans are rational. Various experiments performed over the last several decades have been interpreted as showing that humans are irrational; certain philosophers, on the other hand, have argued that it is a conceptual truth that humans must be rational. Edward Stein concludes that the question of human rationality should be answered not conceptually but empirically: the resources of a fully (...) developed cognitive science need to be used not only to answer this question but generally in investigations of the nature of human knowledge and understanding. (shrink)

Are humans rational? Various experiments performed over the last several decades have been interpreted as showing that humans are irrational we make significant and consistent errors in logical reasoning, probabilistic reasoning, similarity judgements, and risk-assessment, to name a few areas. But can these experiments establish human irrationality, or is it a conceptual truth that humans must be rational, as various philosophers have argued? In this book, Edward Stein offers a clear critical account of this debate about rationality in philosophy (...) and cognitive science. He discusses concepts of rationality - the pictures of rationality that the debate centres on - and assesses the empirical evidence used to argue that humans are irrational. He concludes that the question of human rationality must be answered not conceptually but empirically, using the full resources of an advanced cognitive science. Furthermore, he extends this conclusion to argue that empirical considerations are also relevant to the theory of knowedge - in other words, that epistemology should be naturalized. from the reviews: 'Stein has done a great service in bringing together all of the important arguments in the human rationality debate and providing a measured critical assessment of them.... This will be an important book and is essential reading for epistemologists, philosophers of mind, and cognitive and evolutionary psychologists.' Choice 'very considerable value... for professionals' Times Higher Education Supplement. (shrink)

Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). (...) The discipline is thus at the interface between two very different styles of explanation—as the papers in the current special issue well illustrate, it explores the interplay of rational and mechanistic forces. (shrink)

This volume, derived from the Royal Institute of Philosophy 1992 conference, brings together some of the leading figures in the burgeoning field of cognitive science to explore current and potential advances in the philosophical understanding of mind and cognition. Drawing on work in psychology, computer science and artificial intelligence, linguistics and philosophy, the papers tackle such issues as concept acquisition, blindsight, rationality and related questions as well as contributing to the lively debates about connectionism and neural (...) networks. The collection as a whole reflects the theoretical and methodological dynamism of this interdisciplinary field. (shrink)

The findings of the cognitive sciences enrich our understanding of atheism by providing a more nuanced and empirically grounded concept of ‘belief’ and by problematizing psychological assumptions often employed in theorizing about atheism. Beliefs are diverse not only in content but also level of cognitive processing, and implicit beliefs can and do diverge from explicit beliefs. This is just as true for beliefs about supernatural agents as it is for beliefs about physical objects. Further, findings from the (...) class='Hi'>cognitive sciences call into question the notion that human beings are ‘rational’ and the notion that beliefs can be explained by their ability to provide comfort. The cognitive sciences are replacing such assumptions with an empirically grounded vision of mind and belief. (shrink)

It has always been controversial to make a sharp distinction between the philosophical and the psychological approaches to aesthetics; and the revolution brought about by cognitive science has led many to believe that the philosophy of art no longer controls a sovereign territory of its own. To take one case in point: recent aesthetics has addressed the problem of fiction, asking how it is that real emotions can be felt towards merely imagined events. Several philosophers have tried to (...) solve this problem by leaning on observations in psychology – Jenefer Robinson, for example, exploring the domain of pre-conscious and non-rational responses, and Greg Currie, invoking simulation theory from the realm of cognitive science. I am not yet persuaded that either has succeeded in solving the philosophical question: but the fact that such sophisticated and well-informed philosophers should begin from studies in empirical psychology says much about how the subject of aesthetics has changed since the early days of linguistic analysis. (shrink)

With the title “Philosophy and Cognitive Science: Western and Eastern Studies,” the average reader can expect to find at least three things: a book on the main relationships between cognitive science and philosophy, a text that compares the academic research on cognitive science in Western contexts with Eastern contexts , and finally a significant representation of main Western and Eastern countries, at least those participating in contemporary research. Astonishingly none of these three aspects can (...) be found reading this book. The anthology has a basic and recurring topic, abduction, with a special emphasis on co-editor Magnani’s contributions to the field, although some chapters go beyond this sphere. All the quoted authors and book references belong to the Western bibliographical corpus. Despite being the result of a conference held in Guangzhou, China, the book does not represent the main views of b .. (shrink)

The observation that humans are often irrational has become commonplace. This observation has received empirical support from various experiments performed by cognitive scientists that are supposed to show that humans systematically violate principles of probability, rules of logic, and other norms of reasoning. In response to these experiments, philosophers have made creative and appealing arguments that these experiments must be mistaken or misinterpreted because humans must be rational. I examine these arguments for human rationality and show that they (...) fail; cognitive science does play a role in assessing human rationality. ;In Chapter One, I examine three cognitive science experiments in detail and discuss what is at issue in the debate about human rationality. At issue is whether the mistakes humans make are mere mistakes or indicative of systematic divergences from norms of reasoning. Defenders of human rationality say these mistakes are not characteristic of underlying reasoning abilities but are performance errors. Because humans make performance errors, human reasoning ability cannot be read off of behavior, but rather is to be studied by exploring cognitive competence, the underlying ability to reason. ;In Chapter Two, I develop and discuss the notion of cognitive competence. I then consider and reject two arguments that human cognitive competence must match the norms of reasoning. The first argument appeals to simplicity considerations, the second to the supposed common origin of our cognitive competence and our normative standards. In Chapter Three, I turn to a related argument for a view that humans are rational that says cognitive competence is discovered in the same way norms of reasoning are justified: both projects involve reflective equilibrium using as data people's judgments about what counts as good reasoning. ;In Chapter Four, I consider an argument for human rationality that draws on the principle of charity: when translating utterances of a speaker, one should try to interpret her utterances as rational and true. ;In Chapter Five, I consider an argument for human rationality that appeals to evolution. This argument claims that natural selection will select for cognitive mechanisms that produce true beliefs, and that such "truth-tropic" mechanisms are sufficient for being rational. ;My overall conclusion is that while cognitive science does not determine what the normative principles of reasoning are, it is relevant to whether or not human cognitive competence matches these principles; whether or not humans are irrational is, thus, an empirical question. (shrink)

Abstract Studies of irrationality in cognitive psychology have usually looked at areas where humans might be expected to be rational, yet appear not to be. In this paper the other extreme of human irrationality is examined: the delusion as it occurs in psychiatric illness. A parallel is suggested between the delusion as an aberration of cognition and some illusions which result from aberrations within optics. It is argued that, because delusions are found predominantly within certain limited areas of (...) class='Hi'>cognitive functioning, they may represent a form of mental aberration which may tell us something about the abstract properties of mind. Possible implications of this model for several areas of cognitive science are discussed. (shrink)

I offer a novel interpretation of Aristotle's psychology and notion of rationality, which draws the line between animal and specifically human cognition. Aristotle distinguishes belief (doxa), a form of rational cognition, from imagining (phantasia), which is shared with non-rational animals. We are, he says, “immediately affected” by beliefs, but respond to imagining “as if we were looking at a picture.” Aristotle's argument has been misunderstood; my interpretation explains and motivates it. Rationality includes a filter that interrupts the pathways (...) between cognition and behavior. This prevents the subject from responding to certain representations. Stress and damage compromise the filter, making the subject respond indiscriminately, as non-rational animals do. Beliefs are representations that have made it past the filter, which is why they can “affect [us] immediately.” Aristotle's claims express ceteris paribus generalizations, subject to exceptions. No list of provisos could turn them into non-vacuous universal claims, but this does not rob them of their explanatory power. Aristotle's cognitive science resolves a tension we grapple with today: it accounts for the specialness of human action and thinking within a strictly naturalistic framework. The theory is striking in its insight and explanatory power, instructive in its methodological shortcomings. (shrink)

: This paper continues my application of theories of concepts developed in cognitive psychology to clarify issues in Kuhn's mature account of scientific change. I argue that incommensurability is typically neither global nor total, and that the corresponding form of scientific change occurs incrementally. Incommensurability can now be seen as a local phenomenon restricted to particular points in a conceptual framework represented by a set of nodes. The unaffected parts in the framework constitute the basis for continued communication between (...) the communities supporting alternative structures. The importance of a node is a measure of the severity of incommensurability introduced by replacing it. Such replacements occur incrementally so that changes like that from the conceptual structure of Aristotelian celestial physics to the conceptual structure of Newtonian celestial physics occur in small stages over time, and for each change it is in principle possible to identify the arguments and evidence that led historical actors to make the revisions. Thus the process of scientific change is a rational one, even when its beginning and end points are incommensurable conceptual structures. It is also apparent, from a detailed examination of the conceptual structure of astronomy at the time of Copernicus, thatthe kind of conceptual difficulty identified as incommensurability may occur within a single scientific tradition as well as between two rival traditions. (shrink)

In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states can (...) at any given time be adequately described by a single subjective probability function. We show that monistic Bayesians cannot provide an adequate solution to the new Tweety puzzle, because this requires one to refer to a frequency-based probability function. We conclude that monistic Bayesianism cannot be a fully adequate theory of epistemic states. In the second part we describe an empirical study, which provides support for the thesis that monistic Bayesianism is also inadequate as a descriptive theory of cognitive states. In the final part of the paper we criticize Bayesian approaches in cognitive science, insofar as their monistic tendency cannot adequately address the new Tweety puzzle. We, further, argue against monistic Bayesianism in cognitive science by means of a case study. In this case study we show that Oaksford and Chater’s (2007, 2008) model of conditional inference—contrary to the authors’ theoretical position—has to refer also to a frequency-based probability function. (shrink)

It is widely thought that the cognitive science of religion may have a bearing on the epistemic status of religious beliefs and on other topics in philosophy of religion. Epistemologists have used theories from CSR to argue both for and against the rationality of religious beliefs, or they have claimed that CSR is neutral vis-à-vis the epistemic status of religious belief. However, since CSR is a rapidly evolving discipline, a great deal of earlier research on the topic (...) has become dated. Furthermore, most of the debate on the epistemic consequences of CSR has not taken into account insights from the philosophy of science, such as explanatory pluralism and explanatory levels. This volume overcomes these deficiencies. This volume brings together new philosophical reflection on CSR. It examines the influence of CSR theories on the epistemic status of religious beliefs; it discusses its impact on philosophy of religion; and it offers new insights for CSR. The book addresses the question of whether or not the plurality of theories in CSR makes epistemic conclusions about religious belief unwarranted. It also explores the impact of CSR on other topics in philosophy of religion like the cognitive consequences of sin and naturalism. Finally, the book investigates what the main theories in CSR aim to explain, and addresses the strengths and weaknesses of CSR. (shrink)

This book illustrates the program of Logical-Informational Dynamics. Rational agents exploit the information available in the world in delicate ways, adopt a wide range of epistemic attitudes, and in that process, constantly change the world itself. Logical-Informational Dynamics is about logical systems putting such activities at center stage, focusing on the events by which we acquire information and change attitudes. Its contributions show many current logics of information and change at work, often in multi-agent settings where social behavior is essential, (...) and often stressing Johan van Benthem's pioneering work in establishing this program. However, this is not a Festschrift, but a rich tapestry for a field with a wealth of strands of its own. The reader will see the state of the art in such topics as information update, belief change, preference, learning over time, and strategic interaction in games. Moreover, no tight boundary has been enforced, and some chapters add more general mathematical or philosophical foundations or links to current trends in computer science. (shrink)

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, (...) and the upper millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:The Philosophic Foundations of Mimetic Theory and Cognitive Science(Including Artificial Intelligence)Jean-Pierre Dupuy (bio)In the mid 1970s I discovered at the same time cognitive science and mimetic theory. Being a philosopher with a scientific background, I immediately brought them together and tried to reconceptualize the latter in terms of the former. In a sense, I haven't stopped doing that in the last 45 years. That is (...) why I feel fully at home with the goals pursued by the organizers of this conference.I do not believe it is feasible or even desirable to operate the rapprochement between the two disciplines at a global level. The history of cognitive science is exceedingly involved, and the part played by artificial intelligence in it compared to the part played by the neurosciences has varied greatly over time.1 Only a piecemeal approach makes sense. I present here four short case studies that cover the whole period, from the beginnings in cybernetics to today's artificial intelligence (AI).In order to better situate these studies within a broader frame, I propose the diagram in Figure 1. To comment on it would require more time than available for my whole presentation. Let me just say the following. [End Page 1]It is essential to distinguish between two kinds of AI. The first to bear this name was launched by economist Herbert Simon and computer scientist Allan Newell at a Dartmouth conference in 1956. It was based on the premise that thinking is computing, with this computation bearing on sentences of a "language of thought" implementable in a digital computer. It turns out that this AI(1) was progressively substituted from the 1980s onward by an AI(2), which, to some extent, was a return to a fundamental result obtained by cybernetics in 1943. Neurophysiologist Warren McCulloch and mathematician Walter Pitts had constructed a mathematical model of a network of elementary calculators called "neurons" and explored its properties. The capacity to "think" was one of these. It was not situated at the elementary level, as was the case in AI(1), but it emerged at the collective level from the interactions between the neurons.This model was heavily criticized by the supporters of AI(1),2 and its first implementations, in the notorious "Perceptron" in particular (1957), were pitiful failures. However, the emergence of "second-order cybernetics" under the guidance of cybernetician Heinz von Foerster and the theory of complex, self-organizing systems that it helped develop, in cooperation and rivalry with similar efforts in the physical sciences, enabled the neural network model to come to a second life under different names: formal neurons, deep learning, big data, and the like. Together, they constitute AI(2).The following network of influences wouldn't have been possible without its stem, that is, the boxes containing the names of Kurt Gödel and Alan Turing. The former revolutionized logic by showing that reasoning about arithmetic and arithmetic are one and the same, insofar as it is possible to code in a 1-to-1 fashion propositions about integers (for instance, "7 is a prime number") by means of integers. The latter demonstrated that some mechanisms can self-transcend inasmuch as they generate an ensemble of outputs that cannot be defined mechanistically. Later, John von Neumann, who is credited along with Alan Turing with having invented the digital computer, would use this logical possibility to define complexity: A mechanism is complex if it is capable of generating one more complex than itself. The gate was open for the theories of complex, self-organizing systems to thrive and, by way of consequence, for AI(2) to emerge.fascination with modelsHerbert Simon (1916–2001), winner of the Nobel Prize in economics for his work on what he called "bounded rationality," is generally considered to be one [End Page 2] Click for larger view View full resolutionFigure 1.of the founders of artificial intelligence. Some cognitive scientists still rely on the computer program that he devised with Alan Newell to simulate the creative processes of human thought—a program aptly named "General Problem Solver." The title of one of his principal works, The Sciences of the... (shrink)

It is widely acknowledged that the new emerging discipline cognitive science of religion has a bearing on how to think about the epistemic status of religious beliefs. Both defenders and opponents of the rationality of religious belief have used cognitive theories of religion to argue for their point. This paper will look at the defender-side of the debate. I will discuss an often used argument in favor of the trustworthiness of religious beliefs, stating that cognitive (...) science of religion shows that religious beliefs are natural and natural beliefs ought to be trusted in the absence of counterevidence. This argument received its most influential defense from Justin Barrett in a number of papers, some in collaboration with Kelly James Clark. I will discuss their version of the argument and argue that it fails because the natural beliefs discovered by cognitive scientists of religion are not the religious beliefs of the major world religions. A survey of the evidence from cognitive science of religion will show that cognitive science does show that other beliefs come natural and that these can thus be deemed trustworthy in the absence of counterevidence. These beliefs are teleological beliefs, afterlife beliefs and animistic theistic beliefs. (shrink)

Cognitive Science of Religion is still a rather young discipline. Depending on what one deems to be the first paper or book in the field, the discipline is now almost forty or almost thirty years old. Philosophical and theological discussion on CSR started in the late 2000s. From its onset, the main focus has been the epistemic consequences of CSR, and this focus is dominant even today. Some of those involved in the debate discussed the relevance of CSR (...) for further issues in philosophy of religion, and other have examined how CSR weighs in on various theological questions. Finally, a small number of philosophers offered criticisms or support for various CSR-theories. In this chapter, we give an overview of the debates so far and provide an outline of the book. (shrink)

This collection focuses on questions that arise when morality is considered from the perspective of recent work on rational choice and evolution. Linking questions like "Is it rational to be moral?" to the evolution of cooperation in "The Prisoners Dilemma," the book brings together new work using models from game theory, evolutionary biology, and cognitive science, as well as from philosophical analysis. Among the contributors are leading figures in these fields, including David Gauthier, Paul M. Churchland, Brian Skyrms, (...) Ronald de Sousa, and Elliot Sober. (shrink)

The main task of Cognitive Science is to construct concepts and models that would be superordinate to knowledge in the various particular cognitive sciences. In particular, one major objective is to formulate a hypergeneral description of representations that could encompass all descriptions given in subordinate domains.A first basic distinction is between natural and rational representations, i.e. given mental entities and representations that are governed by prescriptive rules coming from logical or scientific thought. In addition, representations must be (...) described in respect to several sources of variability, which are tentatively listed here.Description of natural representations is based on a distinction between taken representations, which are mental events, and type representations, which are lasting structures registered in memory. The connection between them can be modelled through the concept of activation.One advantage of activation models is their large compatibilty, not only with experimental evidence in cognitive psychology, but also with facts and hypotheses in neurosciences, and programming modes or requirements in artificial intelligence. Comprehension of natural language is a highly representative domain in this respect, which exemplifies the power of these concepts. (shrink)

The chapter places Kant's discussions of empirical and rational psychology in the context of previous discussions in Germany. It also considers the status of what might be called his "transcendental psychology" as an instance of a special kind of knowledge: transcendental philosophy. It is divided into sections that consider four topics: the refutation of traditional rational psychology in the Paralogisms; the contrast between traditional empirical psychology and the transcendental philosophy of the Deduction; Kant's appeal to an implicit psychology in his (...) taxonomy and theory of cognitive faculties throughout the Critique of Pure Reason; and his new definitions of and support for empirical and rational psychology in the Doctrine of Method. (shrink)

Philosophers and cognitive scientists have been debating about the nature of practical knowledge in skilled action. A big challenge is that of establishing whether and how practical knowledge (knowledge-how) is influenced by, or related to propositional knowledge (knowledge-that). This becomes even more challenging when trying to understand how propositional and motor representations may cooperate in making action performance flexible, while also remaining rational. In this paper, we offer an account that explains how practical knowledge leads to the execution of (...) our actions in a way that accounts for its relation to propositional knowledge, and with respect to the possibility of granting flexibility and rationality. (shrink)

Religious belief and behavior raises the following two questions: (Q1) Does God, or any other being or state that is integral to various religious traditions, exist? (Q2) Why do humans have religious beliefs and engage in religious behavior? How one answers (Q2) can affect how reasonable individuals can be in accepting a particular answer to (Q1). My aim in this chapter is to carefully distinguish the various ways in which an answer to Q2 might affect the rationality of believing (...) in God. A literature has sprouted around this exact issue, but it has heretofore focused almost exclusively on one way in which a genealogy for p can affect the rationality of believing p – namely, by the genealogy functioning within a debunking argument. However, there are other ways a genealogy can affect the rationality of a belief. I suggest that we should be interested in whether genealogies more broadly cast doubt on religious beliefs. My main goal is: (i) to argue that CSR does not cast doubt on theistic belief in a few of the primary ways that propositions can cast doubt on other propositions, including via a debunking argument; and (ii) to suggest that one plausible way in which CSR might cast doubt on theistic belief is by undermining various traditional theistic reasons, and to illustrate how this might work with one example of a traditional theistic reason – religious experience. (shrink)

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character (...) and are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms ‘optimal’ and ‘rational’ have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success. (shrink)

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, (...) and the upper millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

This volume, derived from the Royal Institute of Philosophy 1992 conference, brings together some of the leading figures in the burgeoning field of cognitive science to explore current and potential advances in the philosophical understanding of mind and cognition. Drawing on work in psychology, computer science and artificial intelligence, linguistics and philosophy, the papers tackle such issues as concept acquisition, blindsight, rationality and related questions as well as contributing to the lively debates about connectionism and neural (...) networks. The collection as a whole reflects the theoretical and methodological dynamism of this interdisciplinary field. (shrink)

This paper contains an overview of the essays contained in the Mind and morals anthology plus a critical discussion of certain themes raised in many of these essays concerning the bearing of recent work in cognitive science on the traditional project of moral theory. Specifically, I argue for the following claims: (1) authors like Virginia Held, who appear to be antagonistic toward the methodological naturalism of Owen Flanagan, Andy Clark, Paul Churchland, and others, are really in fundamental agreement (...) with the naturalists (at least once the naturalist view is suitably clarified); (2) the prototype theory of moral concepts that is inspired by recent work in cognitive science does not necessarily jeopardize the aim of systematization characteristic of traditional moral theory; (3) nor does it threaten certain widely accepted views about moral rationality that is part of traditional moral theorizing. Moreover, I speculate that (4) recent work in cognitive science can be expected to play a corroborative role in the justification of theories in ethics, but we should probably not expect this work to yield new insights and directions in ethics. Finally, (5) Fodor's recent critique of cognitive science makes clear the perils of methodological ethical naturalism. (shrink)

Although the presence of cognitive values in science has been accepted for half a century, until recently it was claimed that the presence of non-cognitive values threatened the rationality and objectivity of science and it was a sign of a scientist’s weakness. This view appeared to be correct when cognitive and non-cognitive values were treated dichotomously, and science was seen as a set of theories and procedures. The analysis of science as (...) a social practice shows however that this dichotomy cannot be maintained and that the scientist, when planning and conducting research, makes assumptions which include value judgments encompassing certain non-cognitive values. Ignoring the presence of non-cognitive values does not secure objectivity and rationality of science. On the contrary, since they are constitutive elements of scientific research, pretending that they do not work in research exposes science to ideologization. Rational subordination of science to them becomes a vehicle and a warrant of not only rationality but also objectivity and social responsibility of science. This in turn allows us to restore the proper place of science in culture. (shrink)

The last 15 years or so has seen the development of a fascinating new area of cognitive science: the cognitive science of religion (CSR). Scientists in this field aim to explain religious beliefs and various other religious human activities by appeal to basic cognitive structures that all humans possess. The CSR scientific theories raise an interesting philosophical question: do they somehow show that religious belief, more specifically belief in a god of some kind, is irrational? (...) In this paper I investigate this question and argue that CSR does not show that belief in god is irrational. (shrink)

In his book Representation Reconsidered, William Ramsey argues against the view that the concept of mental representation employed by cognitive scientists should be based on the folk-psychological concept of mental representation as propositional attitudes. The author of the present article will attempt to show that, contrary to what Ramsey himself claims, the fact that the folk concept of mental representation will most likely not be a part of the conceptual repository of cognitive science does not imply that (...) beliefs, desires or the rationality of human cognition should be eliminated from the naturalistic outlook on the nature of mind and cognitive processes. The key to see that this is the case lies in understanding cognitive systems as multi-level, hierarchically organized mechanisms. (shrink)

In Rationality and Logic, Robert Hanna argues that logic is intrinsically psychological and that human psychology is intrinsically logical. He claims that logic is cognitively constructed by rational animals and that rational animals are essentially logical animals. In order to do so, he defends the broadly Kantian thesis that all rational animals possess an innate cognitive "logic faculty." Hanna 's claims challenge the conventional philosophical wisdom that sees logic as a fully formal or "topic-neutral" science irreconcilably separate (...) from the species- or individual-specific focus of empirical psychology.Logic and psychology went their separate ways after attacks by Frege and Husserl on logical psychologism--the explanatory reduction of logic to empirical psychology. Hanna argues, however, that--despite the fact that logical psychologism is false--there is an essential link between logic and psychology. Rational human animals constitute the basic class of cognizers or thinkers studied by cognitive psychology; given the connection between rationality and logic that Hanna claims, it follows that the nature of logic is significantly revealed to us by cognitive psychology. Hanna 's proposed "logical cognitivism" has two important consequences: the recognition by logically oriented philosophers that psychologists are their colleagues in the metadiscipline of cognitive science; and radical changes in cognitive science itself. Cognitive science, Hanna argues, is not at bottom a natural science; it is both an objective or truth-oriented science and a normative human science, as is logic itself. (shrink)

[from the publisher's website] Questions about the existence and attributes of God form the subject matter of natural theology, which seeks to gain knowledge of the divine by relying on reason and experience of the world. Arguments in natural theology rely largely on intuitions and inferences that seem natural to us, occurring spontaneously—at the sight of a beautiful landscape, perhaps, or in wonderment at the complexity of the cosmos—even to a nonphilosopher. In this book, Helen De Cruz and Johan De (...) Smedt examine the cognitive origins of arguments in natural theology. They find that although natural theological arguments can be very sophisticated, they are rooted in everyday intuitions about purpose, causation, agency, and morality. Using evidence and theories from disciplines including the cognitive science of religion, evolutionary ethics, evolutionary aesthetics, and the cognitive science of testimony, they show that these intuitions emerge early in development and are a stable part of human cognition. -/- De Cruz and De Smedt analyze the cognitive underpinnings of five well-known arguments for the existence of God: the argument from design, the cosmological argument, the moral argument, the argument from beauty, and the argument from miracles. Finally, they consider whether the cognitive origins of these natural theological arguments should affect their rationality. (shrink)

This paper addresses the apparent mismatch between the normative and descriptive literatures in the cognitive science of conditional reasoning. Descriptive psychological theories still regard material implication as the normative theory of the conditional. However, over the last 20 years in the philosophy of language and logic the idea that material implication can account for everyday indicative conditionals has been subject to severe criticism. The majority view is now apparently in favour of a subjective conditional probability interpretation. A comparative (...) model fitting exercise is presented that shows that a conditional probability model can explain as much of the data on abstract indicative conditional reasoning tasks as psychological theories that supplement material implication with various rationally unjustified processing assumptions. Consequently, when people are asked to solve laboratory reasoning tasks, they can be seen as simply generalising their everyday probabilistic reasoning strategies to this novel context. (shrink)

Are the cognitive sciences relevant for law? How do they influence legal theory and practice? Should lawyers become part-time cognitive scientists? The recent advances in the cognitive sciences have reshaped our conceptions of human decision-making and behavior. Many claim, for instance, that we can no longer view ourselves as purely rational agents equipped with free will. This change is vitally important for lawyers, who are forced to rethink the foundations of their theories and the framework of legal (...) practice. Featuring multidisciplinary scholars from around the world, this book offers a comprehensive overview of the emerging field of law and the cognitive sciences. It develops new theories and provides often provocative insights into the relationship between the cognitive sciences and various dimensions of the law including legal philosophy and methodology, doctrinal issues, and evidence. (shrink)

This paper explores the relation between evolutionary explanations of religious belief and a core idea in both classical Christian theology and Reformed Epistemology, namely that humans have fallen into sin. In particular, it challenges the claim made by De Cruz and De Smedt that ‘ in the light of current evolutionary and cognitive theories, the Reformed epistemological view of NES [the noetic effects of sin] is in need of revision.’ Three possible solutions to this conundrum are examined, two of (...) which are shown to be plausible. (shrink)

Bayesian approaches to human cognition have been extensively advocated in the last decades, but sharp objections have been raised too within cognitive science. In this paper, we outline a diagnosis of what has gone wrong with the prevalent strand of Bayesian cognitive science (here labelled pure Bayesian cognitive science), relying on selected illustrations from the psychology of reasoning and tools from the philosophy of science. Bayesians’ reliance on so-called method of rational analysis is (...) a key point of our discussion. We tentatively conclude on a constructive note, though: an appropriately modified variant of Bayesian cognitive science can still be coherently pursued, as some scholars have noted. (shrink)

Computational physical systems may exhibit indeterminacy of computation (IC). Their identified physical dynamics may not suffice to select a unique computational profile. We consider this phenomenon from the point of view of cognitive science and examine how computational profiles of cognitive systems are identified and justified in practice, in the light of IC. To that end, we look at the literature on the underdetermination of theory by evidence and argue that the same devices that can be successfully (...) employed to confirm physical hypotheses can also be used to rationally single out computational profiles, notwithstanding IC. (shrink)

In this article I consider the relevance of Tomasello’s work on social cognition to the theory of communicative action. I argue that some revisions are needed to cope with Tomasello’s results, but they do not affect the core of the theory. Moreover, they arguably reinforce both its explanatory power and the plausibility of its normative claims. I proceed in three steps. First, I compare and contrast Tomasello’s views on the ontogeny of human social cognition with the main tenets of Habermas’ (...) theory of communicative action. Second, I suggest how to reframe the role of language in the theory of communicative rationality in order to integrate the two theories. Third, I show how this affects social ontology, supporting the view that the construction of social reality is normatively constrained by the bounds of reason. (shrink)