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)

Human beings, like other organisms, are the products of evolution. Like other organisms, we exhibit traits that are the product of natural selection. Our psychological capacities are evolved traits as much as are our gait and posture. This much few would dispute. Evolutionary psychology goes further than this, claiming that our psychological traits -- including a wide variety of traits, from mate preference and jealousy to language and reason -- can be understood as specific adaptations to ancestral Pleistocene conditions. In (...) Evolutionary Psychology as Maladapted Psychology, Robert Richardson takes a critical look at evolutionary psychology by subjecting its ambitious and controversial claims to the same sorts of methodological and evidential constraints that are broadly accepted within evolutionary biology. The claims of evolutionary psychology may pass muster as psychology; but what are their evolutionary credentials? Richardson considers three ways adaptive hypotheses can be evaluated, using examples from the biological literature to illustrate what sorts of evidence and methodology would be necessary to establish specific evolutionary and adaptive explanations of human psychological traits. He shows that existing explanations within evolutionary psychology fall woefully short of accepted biological standards. The theories offered by evolutionary psychologists may identify traits that are, or were, beneficial to humans. But gauged by biological standards, there is inadequate evidence: evolutionary psychologists are largely silent on the evolutionary evidence relevant to assessing their claims, including such matters as variation in ancestral populations, heritability, and the advantage offered to our ancestors. As evolutionary claims they are unsubstantiated. Evolutionary psychology, Richardson concludes, may offer a program of research, but it lacks the kind of evidence that is generally expected within evolutionary biology. It is speculation rather than sound science -- and we should treat its claims with skepticism. (shrink)

Human beings, like other organisms, are the products of evolution. Like other organisms, we exhibit traits that are the product of natural selection. Our psychological capacities are evolved traits as much as are our gait and posture. This much few would dispute. Evolutionary psychology goes further than this, claiming that our psychological traits -- including a wide variety of traits, from mate preference and jealousy to language and reason -- can be understood as specific adaptations to ancestral Pleistocene conditions. In (...) Evolutionary Psychology as Maladapted Psychology, Robert Richardson takes a critical look at evolutionary psychology by subjecting its ambitious and controversial claims to the same sorts of methodological and evidential constraints that are broadly accepted within evolutionary biology. The claims of evolutionary psychology may pass muster as psychology; but what are their evolutionary credentials? Richardson considers three ways adaptive hypotheses can be evaluated, using examples from the biological literature to illustrate what sorts of evidence and methodology would be necessary to establish specific evolutionary and adaptive explanations of human psychological traits. He shows that existing explanations within evolutionary psychology fall woefully short of accepted biological standards. The theories offered by evolutionary psychologists may identify traits that are, or were, beneficial to humans. But gauged by biological standards, there is inadequate evidence: evolutionary psychologists are largely silent on the evolutionary evidence relevant to assessing their claims, including such matters as variation in ancestral populations, heritability, and the advantage offered to our ancestors. As evolutionary claims they are unsubstantiated. Evolutionary psychology, Richardson concludes, may offer a program of research, but it lacks the kind of evidence that is generally expected within evolutionary biology. It is speculation rather than sound science -- and we should treat its claims with skepticism. (shrink)

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad's classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components (...) within the system cannot be predicted, even in principle, from the behavior of the system's parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature. (shrink)

It is here argued that functionalist constraints on psychology do not preclude the applicability of classic forms of reduction and, therefore, do not support claims to a principled, or de jure, autonomy of psychology. In Part I, after isolating one minimal restriction any functionalist theory must impose on its categories, it is shown that any functionalism imposing an additional constraint of de facto autonomy must also be committed to a pure functionalist--that is, a computationalist--model for psychology. Using an extended parallel (...) to the reduction of Mendelian to molecular genetics, it is shown in Parts II and III that, contrary to the claims of Hilary Putnam and Jerry Fodor, there is no inconsistency between computational models and classical reductionism: neither plurality of physical realization nor plurality of function are inconsistent with reductionism as defended by Ernest Nagel. Employing the results of Part I, the conclusions of Parts II and III are generalized in Part IV to cover any version of functionalism whatsoever; thus, functionalism and reductionism are shown to be consistent. It is urged in conclusion that although a de facto form of autonomy is defensible, there are sound methodological grounds for unconditionally rejecting any principled version of the autonomy of psychology. (shrink)

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad’s classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components (...) within the system cannot be predicted, even in principle, from the behavior of the system’s parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature. (shrink)

Multiple realization was once taken to be a challenge to reductionist visions, especially within cognitive science, and a foundation of the “antireductionist consensus.” More recently, multiple realization has come to be challenged on naturalistic grounds, as well as on more “metaphysical” grounds. Within cognitive science, one focal issue concerns the role of neural plasticity for addressing these issues. If reorganization maintains the same cognitive functions, that supports claims for multiple realization. I take up the reorganization involved in language dysfunctions to (...) deal with questions concerned with multiple realization and neural plasticity. Beginning with Broca’s case for localization and the nineteenth century discussion of “reorganization,” and returning to more recent evidence for neural plasticity, I argue that, in the end, there is substantial support for multiple realization in cognitive systems; I further argue that this is wholly consistent with a recognition of methodological pluralism in cognitive science. (shrink)

Multiple realization historically mandated the autonomy of psychology, and its principled irreducibility to neuroscience. Recently, multiple realization and its implications for the reducibility of psychology to neuroscience have been challenged. One challenge concerns the proper understanding of reduction. Another concerns whether multiple realization is as pervasive as is alleged. I focus on the latter question. I illustrate multiple realization with actual, rather than hypothetical, cases of multiple realization from within the biological sciences. Though they do support a degree of autonomy (...) for higher levels of explanation and organization, they do not have the dire consequences critics of multiple realization fear. †To contact the author, please write to: Department of Philosophy, University of Cincinnati, P.O. Box 210374, Cincinnati, OH 45221‐0374; e‐mail: [email protected]. (shrink)

There is often substantial disparity between philosophical ideals and scientific practice. Philosophical reductionism is motivated by a drive for ontological austerity. The vehicle is conceptual parsimony: the fewer our conceptual primitives, the less are our ontological commitments. A general moral to be drawn from my “Functionalism and Reductionism” is that scientific reduction does not, and should not be expected to, facilitate conceptual economy; yet reduction it still is, and in the classical mold. Those who press for the irreducibility of a (...) functional psychology have been seduced by an inadequate account of scientific reduction. Patricia Kitcher is unhappy with my argument because it fails to live up to her philosophical ideals. “The claim that psychology is irreducible to neurophysiology,” she suggests, “rests to a large extent on the fact that, even in principle, neurophysiology is not capable of carrying out the explanatory work of a functional psychology”. (shrink)

We offer a systematic examination of propensity interpretations of fitness, which emphasizes the role that fitness plays in evolutionary theory and takes seriously the probabilistic character of evolutionary change. We distinguish questions of the probabilistic character of fitness from the particular interpretations of probability which could be incorporated. The roles of selection and drift in evolutionary models support the view that fitness must be understood within a probabilistic framework, and the specific character of organism/environment interactions supports the conclusion that fitness (...) must be understood as a propensity rather than as a limiting frequency. (shrink)

Sober (1992) has recently evaluated Brandon's (1982, 1990; see also 1985, 1988) use of Salmon's (1971) concept of screening-off in the philosophy of biology. He critiques three particular issues, each of which will be considered in this discussion.

The mutual influence of science and values in biology is exhibited in several cases from the biological literature. It is argued in a number of cases, from R. A. Fisher's argument for the optimality of a 50:50 sex ratio to A. Jensen's defense of a genetic basis for intelligence, and including work on the evolution of sexual dimorphism and muted aggression, that the credence accorded the views is disproportionate with their theoretical and empirical warrant. It is, furthermore, suggested that the (...) proper explanation for the attraction and persistence of such views lies in their conformity with ideological norms. There is thus an important, if circumscribed, role for ideological critique in the evaluation of scientific theories; in particular, it lies in the explanation of the acceptance and persistence of scientific views, given independent grounds for questioning their justifiability. (shrink)

Evolutionary models can explain the dynamics of populations, how genetic, genotypic, or phenotypic frequencies change with time. Models incorporating chance, or drift, predict specific patterns of change. These are illustrated using classic work on blood types by Cavalli-Sforza and his collaborators in the Parma Valley of Italy, in which the theoretically predicted patterns are exhibited in human populations. These data and the models display properties of ensembles of populations. The explanatory problem needs to be understood in terms of how likely (...) an observed change, in either a population or an ensemble, would be under drift alone; this is fundamentally a matter of chance. Understood in this way, issues of drift and chance undercut most recent philosophical, but not biological, discussions of the role of "genetic drift.". (shrink)

The formal framework of Kauffman (1991) depicts the constraints of self-organization on the evolution of complex systems and the relation of self-organization to selection. We discuss his treatment of 'generic constraints' as sources of order (section 2) and the relation between adaptation and organization (section 3). We then raise a number of issues, including the role of adaptation in explaining order (section 4) and the limitations of formal approaches in explaining the distinctively biological (section 5). The principal question we pose (...) is the relation of generic constraints on evolution to more specific local constraints, imposed, for example, by the characteristic materials out of which organisms are constructed, the accidental features characteristic of the Bauplan of a lineage, and the local vicissitudes of adaptation. We offer no answer to this large question. (shrink)

Bounded rationality is a fundamental feature of cognition. We make choices between alternatives in light of our goals, relying on incomplete information and limited resources. As a consequence, PROBLEM SOLVING cannot be exhaustive: we cannot explore all the possibilities which confront us, and search must be constrained in ways that facilitate search efficiency even at the expense of search effectiveness. If we think of problem solving as a search through the space of possibilities as it was conceptualized by Allen Newell (...) and Herbert A. Simon, limitations on search entail that for all but the simplest problems we can investigate at most a small proportion of the possibilities. Moreover, our evaluation of these possibilities will be uncertain and incomplete. We must rely on heuristic methods for pruning the tree of possibilities and for evaluating the possibilities we consider. In medical diagnosis, for example, the problem is one of inferring what disease is present from a given set of symptoms, when no one symptom is invariably present with a given disease, and the same symptom can have various causes. Moreover, patients can be suffering from more than one disease, a fact which compounds the difficulties of accurate diagnosis. Given that symptoms cannot generally be assumed to be independent and are noisy indicators of the underlying disease, the size of the search space turns out to be large, and inference concerning underlying diseases is inevitably uncertain. One solution is to limit the range of the search, eliminating some candidates as implausible; that is, we may adopt assumptions limiting the range of diseases considered to a narrow range of those antecedently likely. Good diagnosticians evidently narrow the range to no more than a handful of candidates. Search must be limited in order to be efficient. (shrink)

Recent work on self organization promises an explanation of complex order which is independent of adaptation. Self-organizing systems are complex systems of simple units, projecting order as a consequence of localized and generally nonlinear interactions between these units. Stuart Kauffman offers one variation on the theme of self-organization, offering what he calls a ``statistical mechanics'' for complex systems. This paper explores the explanatory strategies deployed in this ``statistical mechanics,'' initially focusing on the autonomy of statistical explanation as it applies in (...) evolutionary settings and then turning to Kauffman's analysis. Two primary morals emerge as a consequence of this examination: first, the view that adaptation and self-organization should be seen as competing theories or models is misleading and simplistic; and second, while we need a synthesis treating self-organization and adaptation as geared toward different problems, at different levels of organization, and deploying different methods, we do not yet have such a synthesis. (shrink)

Developmental biology has resurfaced in recent years, often without a clearly central role for the organism. The organism is pulled in divergent directions: on the one hand, there is an important body of work that emphasizes the role of the gene in development, as executing and controlling embryological change; on the other hand, there are more theoretical approaches under which the organism disappears as little more than an instance for testing biological generalizations. I press here for the ineliminability of the (...) organism in developmental biology on explanatory grounds. I examine classical work concerned with growth and development, particularly in Drosophila and C. elegans. Some of this work is suggestive of modular development, and accordingly suggests a level below that of the organism as being explanatory. These are not the only type of case. There are other equally well-established results, which indicate greater integration in the developing organism. Though with a modular organization the organism can be thought of as made up of its constituent traits, and though the explanations of these traits may lie in terms of cells or genes, even with modular development the explanations of "genetic" differences require an appeal to the organism. With non-modular organization the organism has an even more central role. This does not mean that these genetic or cellular contributions are unreal in any way, or that development requires some sort of vitalistic contribution; but the genetic contributions make sense only as constituents of the organism, embedded in a larger organic context. (shrink)

Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation and development of mechanistic (...) models, identifying five constraints which guide the articulation of models in molecular systems biology. These constraints are not independent of one another, with the result that modeling becomes an iterative process. We illustrate the use of these constraints in the modeling of the mechanism for bistability in the lac operon. (shrink)

Genetic regulatory networks are complex, involving tens or hundreds of genes and scores of proteins with varying dependencies and organizations. This invites the application of artificial techniques in coming to understand natural complexity. I describe two attempts to deploy artificial models in understanding natural complexity. The first abstracts from empirically established patterns, favoring random architectures and very general constraints, in an attempt to model developmental phenomena. The second incorporates detailed information concerning the genetic structure, organization, and dependencies in actual systems (...) in an attempt to explain developmental differences. The results offered by these models, pitched at these different levels of abstraction, are different. The more detailed models are more continuous with classical developmental approaches. (shrink)

The classic charge against Freudian theory is that the therapeutic success of psychoanalysis can be explained without appeal to the mechanisms of repression and insight. Whatever therapeutic success psychoanalysis might enjoy would then provide no support for the diagnostic claim that psychological disorders are due to repressed desires or for the therapeutic claim that the gains in psychoanalysis are due to insight into repressed causes. Adolf Grünbaum has repeated the charge in The Foundations of Psychoanalysis (1984), arguing that Freud's response (...) to it in what he calls the "Tally Argument" is woefully inadequate. Grünbaum claims that Freud's defense depends on the view that only psychoanalytic techniques can yield therapeutic effects, and therefore that the transience of some psychoanalytic "cures", the existence of alternative treatment modalities, and the frequency of spontaneous remission undermine Freud's defense of psychoanalysis. I argue that, whatever the merits of psychoanalysis, Freud is not logically committed to any view as extreme as that attributed to him by Grünbaum; and, furthermore, Grünbaum's rendering of Freud is historically inaccurate. (shrink)

(1983). Consciousness and complexity: Evolutionary perspectives on the mind-body problem. Australasian Journal of Philosophy: Vol. 61, No. 4, pp. 378-395.

Selection operates at many levels. Some of the most obvious cases are organismic, such as changes in coloration under the influence of predation (cf. Kettlewell 1973; also Endler 1986). It also operates at other levels. Meiotic drive involves selection for a gene, independently of its effect on the organism. At a higher level, there may also be selection for patterns of colony growth in social insects, again under the influence of predation (cf. Wilson 1971). The appropriate level of selection is (...) a matter of the causal patterns exhibited, or the target of selection. It can also be understood as a question of the appropriate level at which to seek explanatory laws.Robert Brandon (1982, 1990) first clearly distinguished the question of the level of selection from debates over the units of selection. In doing so, he argued that the phenotype is commonly the target of selection, whatever the unit of selection might be. (shrink)

Stuart Kauffman’s forthcoming book, The Origins of Order: Self Organization and Selection in Evolution (1991), is a large and ambitious attempt to bring about a major reorientation in theoretical biology and to provide a fundamental reinterpretation of the place of selection in evolutionary theory. Kauffman offers a formal framework which allows one to pose precise and well-defined questions about the constraints that self-organization imposes on the evolution of complex systems, and the relation of self-organization and selection. He says at the (...) outset that he wants to “delineate the spontaneous sources of order, the self organized properties of simple and complex systems” and to understand how they “permit, enable and limit the efficacy of natural selection” (Introduction, p. 2).2 As he says somewhat later, the central theme running through his book is that “the order in organisms may largely reflect spontaneous order in complex systems” (ch. 6, p. 224). (shrink)

Selection operates at many levels. Robert Brandon has distinguished the question of the level of selection from the unit of selection, arguing that the phenotype is commonly the target of selection, whatever the unit of selection might be. He uses "screening off" as a criterion for distinguishing the level of selection. Cave animals show a common morphological pattern which includes hypertrophy of some structures and reduction or loss of others. In a study of a cave dwelling crustacean, Gammarus minus, we (...) find evidence for selection for both increased antennal size and reduction of eyes. The genetic structure of the population does not support the view that the phenotype screens off the genotype in explaining the differences in fitness. Nonetheless, the results do indicate that the level of selection is at least at the level of the phenotype in both cases. (shrink)

John Bickle's Psychoneural reduction: the new wave (Cambridge, MA: MIT Press, 1998) aims to resurrect reductionism within philosophy of mind. He develops a new model of scientific reduction, geared to enhancing our understanding of how theories in neuroscience and cognitive science are interrelated. I put this discussion in context, and assess the prospects for new wave reductionism, both as a general model of scientific reduction and as an attempt to defend reductionism in the philosophy of mind.

We have no schema for comprehending how a radical revision of our conceptual scheme such as that embraced by "eliminative materialism" could possibly be rationally justified. This general point is illustrated and pressed through an examination of richard rorty's classic defense of the "disappearance form of the identity theory." it is argued that 1) though more standard critiques of rorty fail, 2) rorty fails to make out the case for the view that incorrigibility" is the "mark of the mental" to (...) the exclusion of intentionality, And 3) the paradigmatic elimination of demons a explanatory entities cannot be extended to yield a justification for the elimination of the mental. (shrink)

Among recent materialists, it has become increasingly common to waive questions of the reducibility or even the consistency of psychological and physiological domains of discourse and to argue for the eliminability of mentalistic conceptions in favor of descriptions of the physical workings of organisms.A more paradigmatic reductionist account has the advantage of giving a clear standard by which we might judge the acceptability of physicalist views: materialism is correct if physical theory is capable of capturing psychological theory. Arguments over this, (...) the identity theory, unfortunately enmeshed theorists in apparently endless disputes over the viability of topic neutral translations; hence, if it is possible for materialists to argue for their position without maintaining a general reduction, such a maneuver would have much to recommend it. (shrink)

Reverse engineering is a matter of inferring adaptive function from structure. The utility of reverse engineering for evolutionary biology has been a matter of controversy. I offer a simple taxonomy of the uses of engineering design in assessing adaptation, with a variety of illustrations. The plausibility of applications of engineering design reflects the specific way the models are elaborated and derived.

Much recent work in sociobiology can be understood as designed to demonstrate the sufficiency of selection operating at lower levels of organization by the development of models at the level of the gene or the individual. Higher level units are accordingly viewed as artifacts of selection operating at lower levels. The adequacy of this latter form of argument is dependent upon issues of the complexity of the systems under consideration. A taxonomy is proposed elaborating a series of types, or grades, (...) of hierarchically organized systems. These range from aggregative systems, in which there is no organization relevant to systemic properties, through several graded variations reflecting various degrees of functional interdependence of components, to integrated systems, which manifest component specialization and diversification as well as a subordination of component function to systemic function. It is suggested that the most complex form of organization is plausibly treated as indicative of higher level units of selection. (shrink)