Robert Richardson

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

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

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.

  Evolutionary psychology purports to explain human capacities as adaptations to an ancestral environment. A complete explanation of human language or human reasoning as adaptations depends on assessing an historical claim, that these capacities evolved under the pressure of natural selection and are prevalent because they provided systematic advantages to our ancestors. An outline of the character of the information needed in order to offer complete adaptation explanations is drawn from Robert Brandon (1990), and explanations offered for the evolution of language and reasoning within evolutionary psychology are evaluated. Pinker and Bloom's (1992) defense of human language as an adaptation for verbal communication, Robert Nozick's (1993) account of the evolutionary origin of rationality, and Cosmides and Tooby's (1992) explanation of human reasoning as an adaptation for social exchange, are discussed in light of what is known, and what is not known, about the history of human evolution. In each case, though a plausible case is made that these capacities are adaptations, there is not enough known to offer even a semblance of an explanation of the origin of these capacities. These explanations of the origin of human thought and language are simply speculations lacking the kind of detailed historical information required for an evolutionary explanation of an adaptation

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

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].

William Uttal's The new phrenology is a broad attack on localization in cognitive neuroscience. He argues that even though the brain is a highly differentiated organ, "high level cognitive functions" should not be localized in specific brain regions. First, he argues that psychological processes are not well-defined. Second, he criticizes the methods used to localize psychological processes, including imaging technology: he argues that variation among individuals compromises localization, and that the statistical methods used to construct activation maps are flawed. Neither criticism is compelling. First, as we illustrate, there are behavioral measures which offer at least weak constraints on psychological attribution. Second, though imaging does face methodological difficulties associated with variation among individuals, these are broadly acknowledged; moreover, his specific criticisms of the imaging work, and in particular of fMRI, misrepresent the methodology. In concluding, we suggest a way of framing the issues that might allow us to resolve differences between localizationist models and more distributed models empirically

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.

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.

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”.

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.

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

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

  Pickering and Chater (P&C) maintain that folk psychology and cognitive science should neither compete nor cooperate. Each is an independent enterprise, with a distinct subject matter and characteristic modes of explanation. P&C''s case depends upon their characterizations of cognitive science and folk psychology. We question the basis for their characterizations, challenge both the coherence and the individual adequacy of their contrasts between the two, and show that they waver in their views about the scope of each. We conclude that P&C do not so muchdiscover ascreate the gap they find between folk psychology and cognitive science. It is an artifact of their implausible and unmotivated attempt to demarcate the two areas, and of the excessively narrow accounts they give of each

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.

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.".

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

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.

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