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Evolutionary theory: Quantifiable science or useful analogy?
REVIEW ESSAY
Evolutionary Theory: Quan~~ia~le Science or Useful Analogy? Ian J. Deary and Gavin J. Gibson
Evolution as Entnqy: T& a Unified Theory ofBiology, 2nd ed. by D. R. Brooks & E. 0. Wiley. Chicago: University of Chicago Press, 1988.
The F&
Conceit: The Errors of So&d&m by F. A. Hayek. London: Routledge, 1988. Introduction
Having an interest in evolutionary theory necessitates diverse reading. While the authors of both of the above texts advocate the usefulness of evolutionary ideas, there is an interesting divergence of emphasis. Brooks and Wiley attempt to qu~ti~ the phenomena of evolution using Hierarchical Information Theory (HIT), whereas IIayek attributes to evolutionary phenomena the characteristic of non-quantifiability. Therefore, while Hayek berates “scientistic” intellectuals for their ignorance of biology and economics, because, he reckons, a knowledge of these areas of study would prevent the inappropriate application of a physicalist approach to economic and social phenomena, Brooks and Wiley attempt to capture important aspects of biology in a rna~ernati~~ model. Therefore, a comparative reading of these books reminds us of a central worry conceming evolutionary theory: that is, how far beyond biology may we apply neo-Darwinist models. Many will recall the initial interest which surrounded the publication of Genes, Mind and Cuhre (Lumsden and Wilson, 1981). Of course, this interest soon waned in the face of incomp~hension, and accusations that the authors had been premature in the application of rna~e~tic~ models to complex psychological and cultural phenomena using the framework of neo-Darwinist selectionism. Notwithstanding the accuracy of the criticisms, to what extent the suspicion aroused by such attempts is due to a lack of mathematical understanding
Journal qf Social and Evolutionary Syam.v 15(2):235-240 ISSN: 0161-7361
Copyright 0 1992 by JAI Press, Inc. All ri&htsof lv-pmduction in any form nsewed.
235
on the part of social scientists-especially those interested in interpersonal phenomena, such as social psychologists and social anthropologists- is not clear. Other, less technical, attempts to extend selectionist ideas to the worlds of cognition and culture have varied in the extent to which evolution has been applied formally. Hull (1982) and Dawkins (1976) have been relatively “hard” advocates of the application of evolutions thinking to the world of ideas, and Campbell (19741, the “godfather” of evolutionary epistemology, has argued that many higher order capacities of nervous systems developed along neo-Darwinian lines (i.e., by the generation of random variations followed by natural selection). Others have argued that systems which acquire knowledge of their environment-such as the immune system or animal intelligence-tend to follow selectionist rather than instructionist principles (see Deary, 1988). At a still less formal level, some authors have queried whether the application of selection&m to other than biological evolution is more than analogy (Plotkin, 1987; Ruse, 1986), and some have doubted whether even the analogy is appropriate (Skagestad, 1978; O’Hear, 1987). The arguments of Brooks & Wiley and Hayek wiil not settle these matters. To anticipate what follows, we do not find the mathematical modelling in Evolution as Enrropy sufficiently free from problems to convince us that evolutionary information is quantifiable; and we do not find sufficient justification for Hayek’s claim that cultural evolution is non-neo-Darwinist to encourage us to write off the efforts of the more radical evolutionary epistemologists. Hierarchical I~&orfnation Theory The central aim of Evolution as Entropy is to provide a model for the processes of evolution consistent with the second law of thermodynamics, in the face of the apparent contradiction which exists between the ever-increasing complexity of biological systems and the increasing disorder demanded by the second law (although many would contend that local increases in negentropy within the context of a globally increasing entropy do not threaten the second law). In an attempt to achieve their aim, Brooks and Wiley appeal to the concept of HlT (Brooks, Cumming & Leblond, 19881, which is a method of quantifying the information present in a system by considering this information to be distributed over a number of levels. The following is a brief summary of the main features of HIT. Let X be a random variable which can take any one of a finite set of values x1, . . . ,xk. If these states have relative frequencies Pi, 1 5 i S k, respectively, then in classical information theory, the information of this distribution is defined to be t -
2
i=l
Pi
log* Pi
HIT is an extension of these ideas to higher dimensional systems where the individual elements are themselves assemblies of a number of sub-elements. If we consider the elements to be n-dimensional vectors of the form (e, , . . . ,e,), where each component ej can be in any one of M states, then an i-sized part is defined to be any subvector, (ejt, . . . ,e& j,
Evolutionay Theory -
237
organizing systems to be hierarchical systems which satisfy a number of conditions regarding the distribution of information over the various levels in the system, the most significant property being an increasing discrepancy between the observed information and the information capacity with increasing level. According to the authors, the significance of such systems is that, although their information content at all levels increases with time, the total information capacity increases at a faster rate, and this increasing discrepancy is what appears to an observer as an increase in the order, or negentropy, of the system. They then produce evidence in support of the hypothesis that a number of complex biological systems, such as DNA sequences, phylogenetic tree topologies, etc., satisfy the defining conditions of self-organizing systems. In this way they seek to resolve any apparent conflict between Dollo’s law and the second law of thermodynamics. For those readers who take the trouble to examine the modest mathematics involved in the derivation of the “Cumming equation,” little confidence is generated by the multiple misprints in equation 2 on page 67. (In fact, the Cumming equation is a trivial consequence of the expression for the maximal information in a distribution.) Also, on the same page, there is an ambiguity in the definition of distinct i sized parts which is left for the reader to resolve-although these are minor quibbles in comparison to the two more major issues which the authors overlook. The first of these concerns the hierarchical information measure itself, which is defined in the text but not explored in any detail. The authors fail to give any consideration to the properties which the measure might be expected to exhibit, and how these properties would relate to the classical measures of the distributions to which they were applied. For all i, the distributions of the i-sized parts is completely specified by that of the n-sized parts, and this strong interdependence leads us to question how valid, as measures of information, the products of,HIT really are. To use a bit of “formal analogy,” (p. 72), I might have 100 pennies, and hence one pound, in my pocket, but I’d be hard pressed to buy two pounds’ worth of chocolate chip cookies, unless the authors go into the biscuit business. Taking this further, we can straightforwardly verify that an n-dimensional population displaying maximal information in its n-sized parts must exhibit maximal information at all lower levels, but the converse does not hold. In view of this, we would not be unreasonable to propose that the discrepancy between the observed and the maximal information may be a monotonic increasing function of the level in general, implying that at least some of the defining conditions for a self-organizing system are common to all systems. For the concept of the self-organizing system to be of real significance, we require a more detailed analysis of the measure itself to establish the non-triviality of the defining conditions (p. 71). A further need for analysis arises when we consider the subject of sampling. In order to estimate the hierarchical information present in a population, an observer can only consider a finite number of samples. The number of possible i-sized states increases exponentially with i, while the number of samples available to estimate the information in the distribution of those states is proportional to the binomial coefficient “ci which, although rapidly increasing, ultimately decreases to 1 at i=n. Now, this implies that at high levels in a population, even if the information in the underlying distribution is high, only a small part will be observed due to the problem of severe undersampling. The relationship between the expected amount of observed information and the sample size is by no means trivial to analyze, and the authors make no effort to do so. Without such analysis, the question of whether the observation that a system is self-organizing may be anything more than a sampling artifact remains unresolved. This book illustrates a major danger which arises when a mathematical model is applied
238 -
IAN J. DEARY AND GAVIN J. GIBSON
to a situation where the fit between model and reality is difficult to discern, and where the model might be no more than analogy. The behaviour of such a model is deterministic and, therefore, in as much as our understanding of the mathematics allows us, predictable. If a mathematical measure is used to describe quantitatively a physical system, then care must be taken to ensure that the features of the particular phenomena under study are specific to them and not merely features of the measure itself. In short, one may not support any argument by appealing to a mathematical tautology. Whilst we are not claiming that Brooks and Wiley are guilty of this, they fail to demonstrate their innocence. The main failings,of the book are to be found with regard to this problem. The Fatal Conceit Our general understanding (but emphatically not a deterministic understanding) of selforganizing or “self-ordering” systems is the theme of Hayek’s book. This economist/philosopher wrote for over six decades and, although there is little in this book that will surprise those who are familiar with his previous writings, this text, more clearly than others he wrote, emphasizes the degree to which his thinking has an evolutionary framework, and the extent to which neo-Darwinist evolution is insufftcient to account for the phenomena of interpersonal exchange, such as the market economy. Hayek’s central thesis-his “big idea,” which drives this book, and many of his other works-is simple, but is also uncomfortable to rationalists, scientists, constructivists and “intellectuals” generally. His notion is that an extended order, such as an advanced society, can never be rendered predictable by science, because no one person could ever collect or make explicit the multitude of variables which interact to sustain that society. At best, he claims, we may attempt a rational reconstruction-a conjectural history or evolutionary account-of moral traditions. And traditions take a place in Hayek’s account of the extended order which is akin to the place of the gene in biological evolution (it being the unit of selection, or “sifting” in Hayek’s parlance). He proposes three possible sources for the emergent rules which individuals adhere to in an advanced society. They might come from: innate moral imperatives; the application of reason; or evolved traditions with which people go along without knowing why. Traditions, he says, lie “between instinct and reason.” Innate morality is not appropriate for an advanced society, because instinctual altruism and solidarity were only adaptive when humans gathered in small groups, the members of which had the same concrete ends. Constuctivists, mainly well-meaning socialists, fail to design a successful society because they possess the fatal conceit that an adequate morality can be designed and constructed afresh using reason (Hayek cites David Hume’s dictum that, “the rules of morality are not the conclusions of our reason,” more than once): . . . one’s initial surprise at finding that intelligentpeople tend to be socialists diminishes when one realizes that, of course, intelligent peopk will tend to overvalue intelligence, and to suppose that we must owe all the advantages and opportunities that our civilization offers to deliberate design rather than to following traditional rules [pp. 53-541.
For Hayek an “evolved morality” of traditions-and tradition lies between instinct and reason, a tertium quid, like several property, savings, equality before the law, honesty, etc.is what created and sustained the extended orders.
Ezmlutiomy Theory
-
239
He is willing to state that our traditions are the product of “selection by evolution,” (p. 69), and that, “the development of variety is an important part of cultural evolution,” (p. 80), but elsewhere in the book he makes clear that he does not consider the evolution of traditions to be neo-Darwinist. Indeed, the evolution of traditions is said to simulate Lamarckism and to operate via group selection. That the differences between Hayek’s own brand of cultural evolution and neo-Darwinism are never spelled out explicitly leaves the reader to speculate how far we are to understand his thesis to be analogy with evolution or to be formally evolutionary, with whatever other non-neo-Darwinist characteristics it might possess. In fact, the main use of the evolutionary analogy here is a negative one. He is keen to demonstrate that constructivists are infected with an understanding of science which is derived from the natural sciences (especially physics), where variables and their interactions are easier to identify and predict, respectively. If only such constructivists were more aware of biology, economics, and evolution, urges Hayek, then they would be more able to appreciate that the extended order cannot be reduced to predictability by the identification of variables. Only broad, abstract principles may be identified, which may foster the continuation of an effective extended order. Therefore, adopting an evolutionary approach to understanding the social order encourages modesty concerning the ability of humans to design their worlds, and prevents the “fatal conceit.” Conclusions
In the end, then, neither volume offers much to the evolutionary epistemologist. Brooks and Wiley’s attempted quantification of the information of self-ordering systems, if it has inherent validity, is difficult to apply to psychological or social phenomena, because units and levels, which are required by HIT, are difficult to divine in these areas. Cultural practices and institutions are not as easy as DNA base pairs to quantify. Hayek’s explicit and muchrepeated aim is to warn us away from “scientism” in our attempts to understand extended orders, and to emphasize that a reductionist account of the extended order is not possible. The best we may attempt is an evolutionary description of the general conditions under which such entities will form and remain effective. Whether Brooks and Wiley’s formulation really extends our knowledge is not clear to us, but Hayek’s essay captures our ignorance rather well. References Brooks, D. R., Cumming, D. D., & LeBlond, P. H. (1988) “Dollo’s Law and the Second Law of Thermodynamics: Analogy or Extension?,” in Weber, B. H., Depew, D. J. & Smith, J. D., eds. Entropy, Information and Evolution: New Perspectives
on Physical and Biological Evolution.
Cambridge, MA: MIT Press. Campbell, D. T. (1974) “Evolutionary Epistemology,” in Schlipp, P. A., ed. The Philosophy of Karl Popper. La Salle, IL: Open Court, pp. 413-463. Deary, I. J. (1988) “Applying Evolutionary Epistemoloy: Prom Immunity to Intelligence.” Journal of Social and Biological Structures, I I, 399408.
Dawkins, R. (1976) The Selfish Gene. London: Oxford University Press, Hull, D. (1982) “The Naked Meme,” in Plotkin, H. C., ed. Learning, Development and Culture. Chichester: Wiley, pp. 273-327.
240
-
IAN J. DEARY AND GAVIN J. GIBSON
Lumsden, C. J. & Wilson, E. 0. (1981) Genes, Mind and Culture: The Coevolutionary Process. London: Harvard University Press. O’Hear, A. (1987) “Has the Theory of Evolution any Relevance to Philsophy?” Ratio, XXZX, 16-35. Plotkin, H. C. (1987) “Evolutionary Epistemology as Science.” Biology and Philosophy, 2, 295-313. Ruse, M. (1986) Taking Darwin Seriously: A Naturalistic Approach to Philosophy. Oxford: Blackwell. Skagestad, P. (1978) “TakingEvolution Seriously.”The Monist, 61, 611-621.
Postscript We have found reflection on the advantages and disadvantages of using analogies in an attempt to increase our understanding of cultural phenomena interesting. The points of similarity between biological and cultural evolution are probably numerous enough to warrant Hayek’s use of the term “cultural evolution.” However, one finds points of similarity in unexpected places. One amusing coincidence is the identity of names for the agents of change in biological and cultural evolution. Some of the mutations occurring in DNA are caused by a species of chemical called free radicals (and animals have biochemical processes directed toward limiting their damaging effects). Likewise, human free radicals provide the pressure for change in a liberal democratic society (and conservatives offer the buffer to counter their redesigning zeal). We leave the readers to consider whether this curiosity has any significance.
Evolutionary Theory: Quan~~ia~le Science or Useful Analogy? Ian J. Deary and Gavin J. Gibson
Evolution as Entnqy: T& a Unified Theory ofBiology, 2nd ed. by D. R. Brooks & E. 0. Wiley. Chicago: University of Chicago Press, 1988.
The F&
Conceit: The Errors of So&d&m by F. A. Hayek. London: Routledge, 1988. Introduction
Having an interest in evolutionary theory necessitates diverse reading. While the authors of both of the above texts advocate the usefulness of evolutionary ideas, there is an interesting divergence of emphasis. Brooks and Wiley attempt to qu~ti~ the phenomena of evolution using Hierarchical Information Theory (HIT), whereas IIayek attributes to evolutionary phenomena the characteristic of non-quantifiability. Therefore, while Hayek berates “scientistic” intellectuals for their ignorance of biology and economics, because, he reckons, a knowledge of these areas of study would prevent the inappropriate application of a physicalist approach to economic and social phenomena, Brooks and Wiley attempt to capture important aspects of biology in a rna~ernati~~ model. Therefore, a comparative reading of these books reminds us of a central worry conceming evolutionary theory: that is, how far beyond biology may we apply neo-Darwinist models. Many will recall the initial interest which surrounded the publication of Genes, Mind and Cuhre (Lumsden and Wilson, 1981). Of course, this interest soon waned in the face of incomp~hension, and accusations that the authors had been premature in the application of rna~e~tic~ models to complex psychological and cultural phenomena using the framework of neo-Darwinist selectionism. Notwithstanding the accuracy of the criticisms, to what extent the suspicion aroused by such attempts is due to a lack of mathematical understanding
Journal qf Social and Evolutionary Syam.v 15(2):235-240 ISSN: 0161-7361
Copyright 0 1992 by JAI Press, Inc. All ri&htsof lv-pmduction in any form nsewed.
235
on the part of social scientists-especially those interested in interpersonal phenomena, such as social psychologists and social anthropologists- is not clear. Other, less technical, attempts to extend selectionist ideas to the worlds of cognition and culture have varied in the extent to which evolution has been applied formally. Hull (1982) and Dawkins (1976) have been relatively “hard” advocates of the application of evolutions thinking to the world of ideas, and Campbell (19741, the “godfather” of evolutionary epistemology, has argued that many higher order capacities of nervous systems developed along neo-Darwinian lines (i.e., by the generation of random variations followed by natural selection). Others have argued that systems which acquire knowledge of their environment-such as the immune system or animal intelligence-tend to follow selectionist rather than instructionist principles (see Deary, 1988). At a still less formal level, some authors have queried whether the application of selection&m to other than biological evolution is more than analogy (Plotkin, 1987; Ruse, 1986), and some have doubted whether even the analogy is appropriate (Skagestad, 1978; O’Hear, 1987). The arguments of Brooks & Wiley and Hayek wiil not settle these matters. To anticipate what follows, we do not find the mathematical modelling in Evolution as Enrropy sufficiently free from problems to convince us that evolutionary information is quantifiable; and we do not find sufficient justification for Hayek’s claim that cultural evolution is non-neo-Darwinist to encourage us to write off the efforts of the more radical evolutionary epistemologists. Hierarchical I~&orfnation Theory The central aim of Evolution as Entropy is to provide a model for the processes of evolution consistent with the second law of thermodynamics, in the face of the apparent contradiction which exists between the ever-increasing complexity of biological systems and the increasing disorder demanded by the second law (although many would contend that local increases in negentropy within the context of a globally increasing entropy do not threaten the second law). In an attempt to achieve their aim, Brooks and Wiley appeal to the concept of HlT (Brooks, Cumming & Leblond, 19881, which is a method of quantifying the information present in a system by considering this information to be distributed over a number of levels. The following is a brief summary of the main features of HIT. Let X be a random variable which can take any one of a finite set of values x1, . . . ,xk. If these states have relative frequencies Pi, 1 5 i S k, respectively, then in classical information theory, the information of this distribution is defined to be t -
2
i=l
Pi
log* Pi
HIT is an extension of these ideas to higher dimensional systems where the individual elements are themselves assemblies of a number of sub-elements. If we consider the elements to be n-dimensional vectors of the form (e, , . . . ,e,), where each component ej can be in any one of M states, then an i-sized part is defined to be any subvector, (ejt, . . . ,e& j,
Evolutionay Theory -
237
organizing systems to be hierarchical systems which satisfy a number of conditions regarding the distribution of information over the various levels in the system, the most significant property being an increasing discrepancy between the observed information and the information capacity with increasing level. According to the authors, the significance of such systems is that, although their information content at all levels increases with time, the total information capacity increases at a faster rate, and this increasing discrepancy is what appears to an observer as an increase in the order, or negentropy, of the system. They then produce evidence in support of the hypothesis that a number of complex biological systems, such as DNA sequences, phylogenetic tree topologies, etc., satisfy the defining conditions of self-organizing systems. In this way they seek to resolve any apparent conflict between Dollo’s law and the second law of thermodynamics. For those readers who take the trouble to examine the modest mathematics involved in the derivation of the “Cumming equation,” little confidence is generated by the multiple misprints in equation 2 on page 67. (In fact, the Cumming equation is a trivial consequence of the expression for the maximal information in a distribution.) Also, on the same page, there is an ambiguity in the definition of distinct i sized parts which is left for the reader to resolve-although these are minor quibbles in comparison to the two more major issues which the authors overlook. The first of these concerns the hierarchical information measure itself, which is defined in the text but not explored in any detail. The authors fail to give any consideration to the properties which the measure might be expected to exhibit, and how these properties would relate to the classical measures of the distributions to which they were applied. For all i, the distributions of the i-sized parts is completely specified by that of the n-sized parts, and this strong interdependence leads us to question how valid, as measures of information, the products of,HIT really are. To use a bit of “formal analogy,” (p. 72), I might have 100 pennies, and hence one pound, in my pocket, but I’d be hard pressed to buy two pounds’ worth of chocolate chip cookies, unless the authors go into the biscuit business. Taking this further, we can straightforwardly verify that an n-dimensional population displaying maximal information in its n-sized parts must exhibit maximal information at all lower levels, but the converse does not hold. In view of this, we would not be unreasonable to propose that the discrepancy between the observed and the maximal information may be a monotonic increasing function of the level in general, implying that at least some of the defining conditions for a self-organizing system are common to all systems. For the concept of the self-organizing system to be of real significance, we require a more detailed analysis of the measure itself to establish the non-triviality of the defining conditions (p. 71). A further need for analysis arises when we consider the subject of sampling. In order to estimate the hierarchical information present in a population, an observer can only consider a finite number of samples. The number of possible i-sized states increases exponentially with i, while the number of samples available to estimate the information in the distribution of those states is proportional to the binomial coefficient “ci which, although rapidly increasing, ultimately decreases to 1 at i=n. Now, this implies that at high levels in a population, even if the information in the underlying distribution is high, only a small part will be observed due to the problem of severe undersampling. The relationship between the expected amount of observed information and the sample size is by no means trivial to analyze, and the authors make no effort to do so. Without such analysis, the question of whether the observation that a system is self-organizing may be anything more than a sampling artifact remains unresolved. This book illustrates a major danger which arises when a mathematical model is applied
238 -
IAN J. DEARY AND GAVIN J. GIBSON
to a situation where the fit between model and reality is difficult to discern, and where the model might be no more than analogy. The behaviour of such a model is deterministic and, therefore, in as much as our understanding of the mathematics allows us, predictable. If a mathematical measure is used to describe quantitatively a physical system, then care must be taken to ensure that the features of the particular phenomena under study are specific to them and not merely features of the measure itself. In short, one may not support any argument by appealing to a mathematical tautology. Whilst we are not claiming that Brooks and Wiley are guilty of this, they fail to demonstrate their innocence. The main failings,of the book are to be found with regard to this problem. The Fatal Conceit Our general understanding (but emphatically not a deterministic understanding) of selforganizing or “self-ordering” systems is the theme of Hayek’s book. This economist/philosopher wrote for over six decades and, although there is little in this book that will surprise those who are familiar with his previous writings, this text, more clearly than others he wrote, emphasizes the degree to which his thinking has an evolutionary framework, and the extent to which neo-Darwinist evolution is insufftcient to account for the phenomena of interpersonal exchange, such as the market economy. Hayek’s central thesis-his “big idea,” which drives this book, and many of his other works-is simple, but is also uncomfortable to rationalists, scientists, constructivists and “intellectuals” generally. His notion is that an extended order, such as an advanced society, can never be rendered predictable by science, because no one person could ever collect or make explicit the multitude of variables which interact to sustain that society. At best, he claims, we may attempt a rational reconstruction-a conjectural history or evolutionary account-of moral traditions. And traditions take a place in Hayek’s account of the extended order which is akin to the place of the gene in biological evolution (it being the unit of selection, or “sifting” in Hayek’s parlance). He proposes three possible sources for the emergent rules which individuals adhere to in an advanced society. They might come from: innate moral imperatives; the application of reason; or evolved traditions with which people go along without knowing why. Traditions, he says, lie “between instinct and reason.” Innate morality is not appropriate for an advanced society, because instinctual altruism and solidarity were only adaptive when humans gathered in small groups, the members of which had the same concrete ends. Constuctivists, mainly well-meaning socialists, fail to design a successful society because they possess the fatal conceit that an adequate morality can be designed and constructed afresh using reason (Hayek cites David Hume’s dictum that, “the rules of morality are not the conclusions of our reason,” more than once): . . . one’s initial surprise at finding that intelligentpeople tend to be socialists diminishes when one realizes that, of course, intelligent peopk will tend to overvalue intelligence, and to suppose that we must owe all the advantages and opportunities that our civilization offers to deliberate design rather than to following traditional rules [pp. 53-541.
For Hayek an “evolved morality” of traditions-and tradition lies between instinct and reason, a tertium quid, like several property, savings, equality before the law, honesty, etc.is what created and sustained the extended orders.
Ezmlutiomy Theory
-
239
He is willing to state that our traditions are the product of “selection by evolution,” (p. 69), and that, “the development of variety is an important part of cultural evolution,” (p. 80), but elsewhere in the book he makes clear that he does not consider the evolution of traditions to be neo-Darwinist. Indeed, the evolution of traditions is said to simulate Lamarckism and to operate via group selection. That the differences between Hayek’s own brand of cultural evolution and neo-Darwinism are never spelled out explicitly leaves the reader to speculate how far we are to understand his thesis to be analogy with evolution or to be formally evolutionary, with whatever other non-neo-Darwinist characteristics it might possess. In fact, the main use of the evolutionary analogy here is a negative one. He is keen to demonstrate that constructivists are infected with an understanding of science which is derived from the natural sciences (especially physics), where variables and their interactions are easier to identify and predict, respectively. If only such constructivists were more aware of biology, economics, and evolution, urges Hayek, then they would be more able to appreciate that the extended order cannot be reduced to predictability by the identification of variables. Only broad, abstract principles may be identified, which may foster the continuation of an effective extended order. Therefore, adopting an evolutionary approach to understanding the social order encourages modesty concerning the ability of humans to design their worlds, and prevents the “fatal conceit.” Conclusions
In the end, then, neither volume offers much to the evolutionary epistemologist. Brooks and Wiley’s attempted quantification of the information of self-ordering systems, if it has inherent validity, is difficult to apply to psychological or social phenomena, because units and levels, which are required by HIT, are difficult to divine in these areas. Cultural practices and institutions are not as easy as DNA base pairs to quantify. Hayek’s explicit and muchrepeated aim is to warn us away from “scientism” in our attempts to understand extended orders, and to emphasize that a reductionist account of the extended order is not possible. The best we may attempt is an evolutionary description of the general conditions under which such entities will form and remain effective. Whether Brooks and Wiley’s formulation really extends our knowledge is not clear to us, but Hayek’s essay captures our ignorance rather well. References Brooks, D. R., Cumming, D. D., & LeBlond, P. H. (1988) “Dollo’s Law and the Second Law of Thermodynamics: Analogy or Extension?,” in Weber, B. H., Depew, D. J. & Smith, J. D., eds. Entropy, Information and Evolution: New Perspectives
on Physical and Biological Evolution.
Cambridge, MA: MIT Press. Campbell, D. T. (1974) “Evolutionary Epistemology,” in Schlipp, P. A., ed. The Philosophy of Karl Popper. La Salle, IL: Open Court, pp. 413-463. Deary, I. J. (1988) “Applying Evolutionary Epistemoloy: Prom Immunity to Intelligence.” Journal of Social and Biological Structures, I I, 399408.
Dawkins, R. (1976) The Selfish Gene. London: Oxford University Press, Hull, D. (1982) “The Naked Meme,” in Plotkin, H. C., ed. Learning, Development and Culture. Chichester: Wiley, pp. 273-327.
240
-
IAN J. DEARY AND GAVIN J. GIBSON
Lumsden, C. J. & Wilson, E. 0. (1981) Genes, Mind and Culture: The Coevolutionary Process. London: Harvard University Press. O’Hear, A. (1987) “Has the Theory of Evolution any Relevance to Philsophy?” Ratio, XXZX, 16-35. Plotkin, H. C. (1987) “Evolutionary Epistemology as Science.” Biology and Philosophy, 2, 295-313. Ruse, M. (1986) Taking Darwin Seriously: A Naturalistic Approach to Philosophy. Oxford: Blackwell. Skagestad, P. (1978) “TakingEvolution Seriously.”The Monist, 61, 611-621.
Postscript We have found reflection on the advantages and disadvantages of using analogies in an attempt to increase our understanding of cultural phenomena interesting. The points of similarity between biological and cultural evolution are probably numerous enough to warrant Hayek’s use of the term “cultural evolution.” However, one finds points of similarity in unexpected places. One amusing coincidence is the identity of names for the agents of change in biological and cultural evolution. Some of the mutations occurring in DNA are caused by a species of chemical called free radicals (and animals have biochemical processes directed toward limiting their damaging effects). Likewise, human free radicals provide the pressure for change in a liberal democratic society (and conservatives offer the buffer to counter their redesigning zeal). We leave the readers to consider whether this curiosity has any significance.