Daniel Andler

Cognitive science, which appears as an articulated group of research programs whose aim is to constitute a science of the mind, raises a number of issues from the point of view of philosophy of science. This chapter will sample the field by dealing with two main topics. The first one is the hypothesis of a modular architecture of the mind, which has occupied cognitive science since more than 30 years. The second part of the chapter is devoted to the foundations and limits of cognitive science, dealing notably with the functionalist framework (in particular, the computational theory of the mind) and the so-called _language of thought_ hypothesis. We conclude by saying a few words about the division of labor among philosophers who are interested in cognition.

situation in the sciences of man and show it to be fallacious. On the view to be 6 rejected, the sciences of man are undergoing the first serious attempt in history to 7 thoroughly naturalize their subject matter and thus to put an end to their separate sta- 8 tus. Progress has (on this view) been quite considerable in the disciplines in charge 9 of the individual, while in the social sciences the outcome of the process is moot: 10 the naturalistic social sciences are still in their infancy, and whether they will even- 11 tually engulf or at least profoundly transform the field of social science is unclear. 12 The dichotomous conception pits two camps against one another. On the one hand, 13..

Recent years have seen a notable increase in the production of scientific expertise by large multidisciplinary groups. The issue we address is how reports may be written by such groups in spite of their size and of formidable obstacles: complexity of subject matter, uncertainty, and scientific disagreement. Our focus is on the International Panel on Climate Change, unquestionably the best-known case of such collective scientific expertise. What we show is that the organization of work within the IPCC aims to make it possible to produce documents that are indeed expert reports. To do so, we first put forward the epistemic norms that apply to expert reports in general, that is, the properties that reports should have in order to be useful and to help decision-making. Section 2 claims that these properties are: intelligibility, relevance and accuracy. Based on this analysis, section 3 points to the difficulties of having IPCC reports indeed satisfying these norms. We then show how the organization of work within the IPCC aims at and to a large extent secures intelligibility, relevance and accuracy, with the result that IPCC reports can be relied on for decision-making. Section 4 focuses on the fundamentals of IPCC’s work organization--that is, division of labour within the IPCC--while section 5 investigates three frameworks that were introduced over the course of the functioning of the IPCC: the reviewing procedure of IPCC reports, the language that IPCC authors use to express uncertainty and the Coupled Model Intercomparison Project. Concluding remarks are offered in section 6.

Our approach to emotion emphasized three key ingredients. We do not yet have a mature science of emotion, or even a consensus view—in this respect we are more hesitant than Sander, Grandjean, and Scherer or Luiz Pessoa. Relatedly, a science of emotion needs to be highly interdisciplinary, including ecology, psychology, neuroscience, and philosophy. We recommend a functionalist view that brackets conscious experiences and that essentially treats emotions as latent variables inferred from a number of measures. But our version of functionalism is not definitional or ontological. It is resolutely methodological, in good part because it is too early to attempt definitions.

We defend a functionalist approach to emotion that begins by focusing on emotions as central states with causal connections to behavior and to other cognitive states. The approach brackets the conscious experience of emotion, lists plausible features that emotions exhibit, and argues that alternative schemes are unpromising candidates. We conclude with the benefits of our approach: one can study emotions in animals; one can look in the brain for the implementation of specific features; and one ends up with an architecture of the mind in which emotions are fully accommodated through their relations to the rest of cognition. Our article focuses on arguing for this general approach; as such, it is an essay in the philosophy of emotion rather than in the psychology or neuroscience of emotion.

Biological and Cultural Bases of Human Inference addresses the interface between social science and cognitive science. In this volume, Viale and colleagues explore which human social cognitive powers evolve naturally and which are influenced by culture. Updating the debate between innatism and culturalism regarding human cognitive abilities, this book represents a much-needed articulation of these diverse bases of cognition. Chapters throughout the book provide social science and philosophical reflections, in addition to the perspective of evolutionary theory and the central assumptions of cognitive science. The overall approach of the text is based on three complementary levels: adult performance, cognitive development, and cultural history and prehistory. Scholars from several disciplines contribute to this volume, including researchers in cognitive, developmental, social and evolutionary psychology, neuropsychology, cognitive anthropology, epistemology, and philosophy of mind. This contemporary, important collection appeals to researchers in the fields of cognitive, social, developmental, and evolutionary psychology and will prove valuable to researchers in the decision sciences.

This paper attempts to show that context is normative. Perceiving and acting, speaking and understanding, reasoning and evaluating, judging and deciding, doing and not doing, as accomplished by humans, invariably occur within a context. The context dictates, or at least constrains, the proper accomplishment of the act. One may construe this undisputed fact in a naturalistic way: one can think of the context as a positive given, and of the constraints it creates as constituting a natural fact. Whether the act is carried out in conformity with these constraints is then a mere matter of correct functioning of the cognitive system. However, I argue, this is not the only, nor the more plausible way of considering the matter. The context is not a determinate function of situation and task, nor is the outcome of a task a determinate function of a given context: context choice and contextual constraints are irreducibly normative. The norm they obey is sui generis, and goes under the (disreputable) name of intelligence.

We seem to suffer from a case of cognitive dissonance. On the one hand, we seem to have almost unanimously rejected as hopeless or incoherent the aim of a unified science. On the other, we passionately debate about the prospects of research programs which, if successful, would considerably enhance the prospects of unification: from particle physics to cognitive neuroscience, from evolutionary theory to logical modeling or dynamic systems, a common motivation seems to be the quest for unity1. The purpose of this paper is to relieve the dissonance. I will defend a moderate form of unity, one which is compatible with the diversity and open-endedness of science, for which I can think of no better name than federalism, as it combines plurality and the construction of a common epistemic area. This view is not original: Otto Neurath himself espoused it, albeit in a context which is in certain respects quite unlike ours2.

In Hubert Dreyfus’s critique of artificial intelligence1, considerable importance is given to the matter of context –used here as a blanket term covering an immense and possibly heterogeneous phenomenon, which includes situation, background, circumstances, occasion and possibly more. Perhaps the best way to point to context in this most general sense is to proceed dialectically, and take as a first approximation context to be whatever is revealed as an obstacle whenever one attempts to account for mental dynamics on the formal model of a combinatorial game over families of interchangeable, fixed, self-standing – context-free as it were– elements. Dreyfus has argued persuasively that the human mind always ‘operates’, if that is the right word, within a setting which permeates whatever it is it operates on. Dreyfus’s thought on these matters was shaped during the years when artificial intelligence (AI) was at the height of early hopes and initial successes. This was also a period during which what was to become known as ‘cognitive science’ was little more than a ray of light falling on psychology..

Fifty years before the present volume appeared, artificial intelligence (AI) and cognitive science (Cogsci) emerged from a couple of small-scale academic encounters on the East Coast of the United States. Wedded together like Siamese twins, these nascent research programs appeared to rest on some general assumptions regarding the human mind, and closely connected methodological principles, which set them at such a distance from phenomenology that no contact between the two approaches seemed conceivable. Soon however contact was made, in the form of a head-on critique of the AI/Cogsci project mostly inspired by arguments from phenomenology. For a while, it seemed like nothing would come of it: AI/Cogsci bloomed while the small troop of critical phenomenologists kept objecting. Then AI and Cogsci went their separate ways. AI underwent a deep transformation and all but surrendered to the phenomenological critique. Cogsci meanwhile pursued the initial program with a far richer collection of problems, concepts and methods, and was for a long time quite unconcerned by suggestions and objections from phenomenology. The last decade and half has seen a remarkable reversal: on the one hand, a few cognitive scientists have been actively pursuing the goal of reconciliating Cogsci, whether empirically or foundationally, with some of the insights procured by phenomenology; on the other, many cognitive scientists and philosophers of mind who think of themselves as, respectively, mainstream and analytic, and have no or little acquaintance with, and often little sympathy for, phenomenology, have been actively pursuing research programs geared toward some of the key issues identified by phenomenological critics of early AI/Cogsci. It might seem then as if those critics were now vindicated. But while these new directions are undoubtedly promising, it is not yet clear that phenomenology and Cogsci can be truly reconciled. Some suspect that Cogsci must distort beyond recognition those phenomenological themes it means to weave into its fabric, while phenomenology may be losing touch with its roots by tuning onto the logic of Cogsci which is, after all, an empirical science. To the present writer, it is far too early for anything like a verdict, as the task of clarifying the issues and gaining a much deeper understanding of the issues on both sides has barely begun. But whatever emerges from this exploration will probably have deep consequences for both Cogsci and philosophy..

Scholars from various philosophical schools of thought, including cultural relativism, hermeneutics, and postmodernism, have recently critiqued rationalism in light of new developments in the cognitive sciences. Each of these new developments set into motion new inquiries in each school philosophical school of thought. Now, in Facets of Rationality, a distinguished team of scholars examines these new inquiries and bring rationality back into the mainstream of the social sciences. The unique feature of this book lies in its multidisciplinary exploration of rational concerns and in discovering the integral meaning of rationality as viewed by the perspectives of different disciplines. As such, it will of considerable interest to those involved with the study and teaching of philosophy, theoretical psychology, cognitive science, political theory, and linguistics.

Conventional wisdom holds two seemingly opposed beliefs. One is that communities are often much better than individuals at dealing with certain situations or solving certain problems. The other is that crowds are usually, and some say always, at best as intelligent as their least intelligent members and at worst even less. Consistency would seem to be easily re-established by distinguishing between advanced, sophisticated social organizations which afford the supporting communities a high level of collective performance, and primitive, mob-like structures which pull the group towards the lower end of the achievement scale. But this reconciliation meets with some objections. The most familiar ones concern the mixed record of elaborate social systems, which are said to occasionally or even, according to some accounts, systematically produce wrong decisions, poor assessments, disastrous plans, counterproductive measures, etc. A more recent set of objections rests on cases where ‘crowds’, i,e, groups not organized in a sophisticated way, produce good results, in fact, results which better those of most, or even all, members of the group. Such cases are collected in James Surowiecki’s book The Wisdom of Crowds, which argues more generally in favor of an ‘order out of chaos’ view of collective thinking: whether sophisticated or simple, social organizations for the production of knowledge or problem-solving can benefit from the absence of certain individualistc constraints which are traditionally thought to foster excellence in cognitive tasks. This flavor of paradox is enhanced by Surowiecki’s choice of phrase: at the surface level, ‘wisdom of crowds’ conflicts with the well-entrenched cliché of the folly1 of crowds; but at a deeper level, Surowiecki seems to appeal to one frequent connotation of ‘wisdom’ which is precisely its paradoxical character. Whether Surowiecki actually intended to exploit this..