This volume consists of the first of the John Dewey Lectures delivered under the auspices of Columbia University's Philosophy Department as well as other essays by the author. Intended to clarify the meaning of the philosophical doctrines propounded by Professor Quine in 'Word and Objects', the essays included herein both support and expand those doctrines.

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

Tested the 2-process theory of detection, search, and attention presented by the current authors in a series of experiments. The studies demonstrate the qualitative difference between 2 modes of information processing: automatic detection and controlled search; trace the course of the learning of automatic detection, of categories, and of automatic-attention responses; and show the dependence of automatic detection on attending responses and demonstrate how such responses interrupt controlled processing and interfere with the focusing of attention. The learning of categories is (...) shown to improve controlled search performance. A general framework for human information processing is proposed. The framework emphasizes the roles of automatic and controlled processing. The theory is compared to and contrasted with extant models of search and attention. (shrink)

Dual-process and dual-system theories in both cognitive and social psychology have been subjected to a number of recently published criticisms. However, they have been attacked as a category, incorrectly assuming there is a generic version that applies to all. We identify and respond to 5 main lines of argument made by such critics. We agree that some of these arguments have force against some of the theories in the literature but believe them to be overstated. We argue that the dual-processing (...) distinction is supported by much recent evidence in cognitive science. Our preferred theoretical approach is one in which rapid autonomous processes are assumed to yield default responses unless intervened on by distinctive higher order reasoning processes. What defines the difference is that Type 2 processing supports hypothetical thinking and load heavily on working memory. (shrink)

Arguments that ordinary inanimate objects such as tables and chairs, sticks and stones, simply do not exist have become increasingly common and increasingly prominent. Some are based on demands for parsimony or for a non-arbitrary answer to the special composition question; others arise from prohibitions against causal redundancy, ontological vagueness, or co-location; and others still come from worries that a common sense ontology would be a rival to a scientific one. Until now, little has been done to address these arguments (...) in a unified and systematic way. Ordinary Objects is designed to fill this gap, demonstrating that the mistakes behind all of these superficially diverse eliminativist arguments may be traced to a common source. It aims to develop an ontology of ordinary objects subject to no such problems, providing perhaps the first sustained defense of a common sense ontology in two generations. The work done along the way addresses a number of major issues in philosophy of language and metaphysics, contributing to debates about analyticity, identity conditions, co-location and the grounding problem, vagueness, overdetermination, parsimony, and ontological commitment. In the end, the most important result of addressing these eliminativist arguments is not merely avoiding their conclusions; examining their failings also gives us reason to suspect that many apparent disputes in ontology are pseudo-debates. For it brings into question widely-held assumptions about which uses of metaphysical principles are appropriate, which metaphysical demands are answerable, and how we should go about addressing such fundamental questions as "What exists?". As a result, the work of Ordinary Objects promises to provide not only the route to a reflective understanding of our unreflective common-sense view, but also a better understanding of the proper methods and limits of metaphysics. (shrink)

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based" because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve (...) complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. (shrink)

William Uttal is concerned that in an effort to prove itself a hard science, psychology may have thrown away one of its most important methodological tools—a critical analysis of the fundamental assumptions that underlie day-to-day empirical research. In this book Uttal addresses the question of localization: whether psychological processes can be defined and isolated in a way that permits them to be associated with particular brain regions. New, noninvasive imaging technologies allow us to observe the brain while it is actively (...) engaged in mental activities. Uttal cautions, however, that the excitement of these new research tools can lead to a neuroreductionist wild goose chase. With more and more cognitive neuroscientific data forthcoming, it becomes critical to question their limitations as well as their potential. Uttal reviews the history of localization theory, presents the difficulties of defining cognitive processes, and examines the conceptual and technical difficulties that should make us cautious about falling victim to what may be a "neo-phrenological" fad. (shrink)

Prospect Theory: For Risk and Ambiguity, provides a comprehensive and accessible textbook treatment of the way decisions are made both when we have the statistical probabilities associated with uncertain future events and when we lack them. The book presents models, primarily prospect theory, that are both tractable and psychologically realistic. A method of presentation is chosen that makes the empirical meaning of each theoretical model completely transparent. Prospect theory has many applications in a wide variety of disciplines. The material in (...) the book has been carefully organized to allow readers to select pathways through the book relevant to their own interests. With numerous exercises and worked examples, the book is ideally suited to the needs of students taking courses in decision theory in economics, mathematics, finance, psychology, management science, health, computer science, Bayesian statistics, and engineering. (shrink)

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the (...) authors held a competition between the satisficing "Take The Best" algorithm and various "rational" inference procedures. The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference. (shrink)

In recent analytic metaphysics, the view that ‘ordinary inanimate objects such as sticks and stones, tables and chairs, simply do not exist’ has been defended by some noteworthy writers. Thomasson opposes such revisionary ontology in favour of an ontology that is conservative with respect to common sense. The book is written in a straightforward, methodical and down-to-earth style. It is also relatively non-specialized, enabling the author and her readers to approach problems that are often dealt with in isolation in a (...) more unified way.Thomasson's arguments are mainly counter-attacks on six ‘eliminativist’ arguments against ordinary objects. A causal redundancy argument espoused by Trenton Merricks holds that to suppose that there are ordinary objects is to suppose that these objects have distinctive causal powers. However, the casual efficacy of a baseball, for example, is exhausted by that of some suitably arranged …. (shrink)

Modularity has been the subject of intense debate in the cognitive sciences for more than 2 decades. In some cases, misunderstandings have impeded conceptual progress. Here the authors identify arguments about modularity that either have been abandoned or were never held by proponents of modular views of the mind. The authors review arguments that purport to undermine modularity, with particular attention on cognitive architecture, development, genetics, and evolution. The authors propose that modularity, cleanly defined, provides a useful framework for directing (...) research and resolving debates about individual cognitive systems and the nature of human evolved cognition. Modularity is a fundamental property of living things at every level of organization; it might prove indispensable for understanding the structure of the mind as well. (shrink)

Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these models (...) are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

The first section introduces a distinction between 2 families of cognitive operations, called System 1 and System 2. The second section presents an attribute-substitution model of heuristic judgment, which elaborates and extends earlier treatments of the topic. The third section introduces a research design for studying attribute substitution. The fourth section discusses the controversy over the representativeness heuristic. The last section situates representativeness within a broad family of prototype heuristics, in which properties of a prototypical exemplar dominate global judgments concerning (...) an entire set. (shrink)

This book is an examination of the nature of economic explanation. The opening chapters introduce current thinking in the philosophy of science and review the literature on methodology. Professor Blaug then turns to the troublesome question of the logical status of welfare economics, giving the reader an understanding of the outstanding issues in the methodology of economics. This is followed by a series of case studies of leading economic controversies, which shows how controversies in economics may be illuminated by paying (...) attention to questions of methodology. A final chapter draws the strands together and gives the author's view of what is wrong with modern economics. This book is a revised and updated edition of a classic work on the methodology of economics, in which Professor Blaug develops his discussion of the latest developments in macroeconomics, general equilibrium theory and international trade theory. A new section on the rationality postulate is also added. (shrink)

In recent years evolutionary psychologists have developed and defended the Massive Modularity Hypothesis, which maintains that our cognitive architecture—including the part that subserves ‘central processing’ —is largely or perhaps even entirely composed of innate, domain-specific computational mechanisms or ‘modules’. In this paper I argue for two claims. First, I show that the two main arguments that evolutionary psychologists have offered for this general architectural thesis fail to provide us with any reason to prefer it to a competing picture of the (...) mind which I call the Library Model of Cognition. Second, I argue that this alternative model is compatible with the central theoretical and methodological commitments of evolutionary psychology. Thus I argue that, at present, the endorsement of the Massive Modularity Hypothesis by evolutionary psychologists is both unwarranted and unmotivated. (shrink)

Brain images are used both as scientific evidence and to illustrate the results of neuroimaging experiments. These images are apt to be viewed as photographs of brain activity, and in so viewing them people are prone to assume that they share the evidential characteristics of photographs. Photographs are epistemically compelling, and have a number of characteristics that underlie what I call their inferential proximity. Here I explore the aptness of the photography analogy, and argue that although neuroimaging does bear important (...) similarities to photography, the details of the generation and analysis of neuroimages significantly complicate the relation of the image to the data. Neuroimages are not inferentially proximate, but their seeming so increases the potential for misinterpretation. This suggests caution in appealing to such images in the public domain. (shrink)

Understanding more about how the brain functionsshouldhelp us understand economic behaviour. But some would have us believe that it has done this already, and that insights from neuroscience have already provided insights in economics that we would not otherwise have. Much of this is just academic marketing hype, and to get down to substantive issues we need to identify that fluff for what it is. After we clear away the distractions, what is left? The answer is that a lot is (...) left, but it is still all potential. That is not a bad thing, or a reason to stop the effort, but it does point to the need for a serious reconsideration of what neuroeconomics is and what passes for explanation in this literature. I argue that neuroeconomics can be a valuable field, but not the way it is being developed and “sold” now. The same is true more generally of behavioural economics, which shares many of the methodological flaws of neuroeconomics. (shrink)

I distinguish between two styles of research that are both called . Neurocellular economics (NE) uses the modelling techniques and mathematics of economics to model relatively encapsulated functional parts of brains. This approach rests upon the fact that brains are, like markets, massively distributed information-processing networks over which executive systems can exert only limited and imperfect governance. Harrison's (2008) deepest criticisms of neuroeconomics do not apply to NE. However, the more famous style of neuroeconomics is behavioural economics in the scanner. (...) This is often motivated by complaints about conventional economics frequently heard from behavioural economists. It attempts to use neuroimaging data to justify arguments for replacing standard aspects of microeconomic theory by facts and conjectures about human psychology. Harrison's grounds for unease about neuroeconomics apply to most BES, or at least to its explicit methodology. This methodology is naively reductionist and illegitimately assumes that economics should not do what all successful science does, namely, model abstract aspects of its target phenomena instead of would-be complete and fully ecologically situated facsimiles of them. (shrink)

In traditional decision theory, utility is regarded as a mathematical representation of preferences to be inferred from agents hedonic experiences. Some go as far as to contend that utility is literally computed by specific neural areas and urge economists to complement or substitute their notion of utility with some neuro-psychological construct. In this paper, I distinguish three notions of utility that are frequently mentioned in debates about decision theory and examine some critical issues regarding their definition and measurability. Moreover, I (...) provide various empirical and conceptual reasons to doubt that economists should base decision theoretic analyses on some neuro-psychological notion of utility. (shrink)

Brain damage may doubly dissociate cognitive modules, but the practice of revealing dissociations is predicated on modularity being true (T. Shallice, 1988). This article questions the utility of assuming modularity, as it examines a paradigmatic double dissociation of reading modules. Reading modules illustrate two general problems. First, modularity fails to converge on a fixed set of exclusionary criteria that define pure cases. As a consequence, competing modular theories force perennial quests for purer cases, which simply perpetuates growth in the list (...) of exclusionary criteria. The first problem leads, in part, to the second problem. Modularity fails to converge on a fixed set of pure cases. The second failure perpetuates unending fractionation into more modules. (shrink)

Ontic structural realism (OSR) is crucially motivated by empirical discoveries of fundamental physics. To this extent its potential to furnish a general metaphysics for science may appear limited. However, OSR also provides a good account of the progress that has been achieved over the decades in a formalized special science, economics. Furthermore, this has a basis in the ontology presupposed by economic theory, and is not just an artifact of formalization. †To contact the author, please write to: 4th Floor, Humanities (...) Building, University of Alabama at Birmingham, 900 13th Street South, Birmingham, AL 35294‐1260; School of Economics, Leslie Social Science Building, University of Cape Town, Private Bag, Rondebosch 7701, Cape Town, South Africa; e‐mail: [email protected]. (shrink)

This essay attempts to distinguish the pressing issues for economists and economic methodologists concerning realism in economics from those issues that are of comparatively slight importance. In particular I shall argue that issues concerning the goals of science are of considerable interest in economics, unlike issues concerning the evidence for claims about unobservables, which have comparatively little relevance. In making this argument, this essay raises doubts about the two programs in contemporary economic methodology that raise the banner of realism. In (...) particular I argue that the banner makes it more difficult to relate the concerns of those who wave it to those of other methodologists. Although this essay argues that many of the debates in this century between scientific realists and their opponents are not relevant to economics, it does not attack scientific realism, and it does not urge economists or economic methodologists to reject it. (shrink)

The need to align multiple experimental procedures and produce converging results so as to demonstrate that the phenomenon under investigation is real and not an artifact is a commonplace both in scientific practice and discussions of scientific methodology (Campbell and Stanley 1963; Wimsatt 1981). Although sometimes this is the purpose of aligning techniques, often there is a different purpose—multiple techniques are sought to supply different perspectives on the phenomena under investigation that need to be integrated to answer the questions scientists (...) are asking. After introducing this function, I will illustrate it by considering three of the major techniques in cognitive neuroscience for linking cognitive function with neural structure. (shrink)

Brain damage may doubly dissociate cognitive modules, but the practice of revealing dissociations is predicated on modularity being true (T. Shallice, 1988). This article questions the utility of assuming modularity, as it examines a paradigmatic double dissociation of reading modules. Reading modules illustrate two general problems. First, modularity fails to converge on a fixed set of exclusionary criteria that define pure cases. As a consequence, competing modular theories force perennial quests for purer cases, which simply perpetuates growth in the list (...) of exclusionary criteria. The first problem leads, in part, to the second problem. Modularity fails to converge on a fixed set of pure cases. The second failure perpetuates unending fractionation into more modules. (shrink)

Over the last decade, neuroeconomic research has attracted increasing attention by economic modellers and methodologists. In this paper, I examine five issues about neuroeconomic modelling and methodology that have recently been subject to considerable controversy. For each issue, I explicate and appraise prominent neuroeconomists' findings, focusing on those that are claimed to directly inform economic theorizing. Moreover, I assess often-made assertions concerning how neuroeconomic research putatively advances the economic modelling of choice. In doing so, I combine review and critical arguments (...) to provide a methodological evaluation of neuroeconomists' contributions. (shrink)

In the recent literature at the interface between economics, biology and neuroscience, several authors argue that by adopting an interdisciplinary approach to the analysis of decision making, economists will be able to construct predictively and explanatorily superior models. However, most economists remain quite reluctant to import biological or neural insights into their account of choice behaviour. In this paper, I reconstruct and critique one of the main arguments by means of which economists attempt to vindicate their conservative position. Furthermore, I (...) develop an alternative defense of the thesis that economists justifiably rely on a methodologically distinctive approach to the modelling of choice behaviour. (shrink)

A few aspects of the issue of realism are addressed in the context of a social science. The paper looks for adjustments needed in our conceptions of scientiflc realism to accommodate some peculiarities of economics. Ontologically speaking, economics appears to be closely linked to commonsense conceptions of the world, thus the problem of theoretical concepts does not emerge in the same form it is often taken to exist in physics. Theory formation is largely a matter of idealization and isolation among (...) observables rather than postulation of unobservables. Given that isolative theories violate the truth in many ways, truth is more of a problem than existence in a realism pertaining to economics. The idea of significant truth -which is able to tolerare varieties of untruths in theories- is suggested to be based on the notion of the way the world works; this is a matter of the causal structure and functioning of the world. None of this is undermined by the acknowledgement that economist’s attittudes and decisions are shapped by rhetorical persuasion. (shrink)

There are many interesting empirical and theoretical issues concerning the evolution of cognition. Despite this, recent books on the topic concentrate on two problems. One is mental modularity. The other is what distinguishes human from non-human minds. While it is easy to understand why people are interested in human uniqueness, it is not clear why modularity is the centre of attention. Fodor (2000) has a nice argument for why people _should_ be interested in modularity.

A few aspects of the issue of realism are addressed in the context of a social science. The paper looks for adjustments needed in our conceptions of scientiflc realism to accommodate some peculiarities of economics. Ontologically speaking, economics appears to be closely linked to commonsense conceptions of the world, thus the problem of theoretical concepts does not emerge in the same form it is often taken to exist in physics. Theory formation is largely a matter of idealization and isolation among (...) observables rather than postulation of unobservables. Given that isolative theories violate the truth in many ways, truth is more of a problem than existence in a realism pertaining to economics. The idea of significant truth -which is able to tolerare varieties of untruths in theories- is suggested to be based on the notion of the way the world works; this is a matter of the causal structure and functioning of the world. None of this is undermined by the acknowledgement that economist’s attittudes and decisions are shapped by rhetorical persuasion. (shrink)

Proponents of neuroeconomics often argue that better knowledge of the human neural architecture enables economists to improve standard models of choice. In their view, these improvements provide compelling reasons to use neural findings in constructing and evaluating economic models. In a recent article, I criticized this view by pointing to the trade-offs between the modeling desiderata valued by neuroeconomists and other economists, respectively. The present article complements my earlier critique by focusing on three modeling desiderata that figure prominently in economic (...) and neuroeconomic modeling. For each desideratum, I examine findings that neuroeconomists deem to be especially relevant for economists and argue that neuroeconomists have failed to substantiate their calls to use these findings in constructing and evaluating economic models. In doing so, I identify methodological and evidential constraints that will continue to hinder neuroeconomists’ attempts to improve such models. Moreover, I draw on the literature on scientific modeling to advance the ongoing philosophical discussion regarding the prospects of interdisciplinary models of choice. (shrink)

Neuroeconomics is the newest of the economic sciences with a focus on how the embodied human brain interacts with its institutional and social environment to make economic decisions. This paper presents an overview of neuroeconomics methods and reviews a number of results in this emerging field of study.