From the beginning of chaos research until today, the unpredictability of chaos has been a central theme. It is widely believed and claimed by philosophers, mathematicians and physicists alike that chaos has a new implication for unpredictability, meaning that chaotic systems are unpredictable in a way that other deterministic systems are not. Hence, one might expect that the question ‘What are the new implications of chaos for unpredictability?’ has already been answered in a satisfactory way. However, this is not the (...) case. I will critically evaluate the existing answers and argue that they do not fit the bill. Then I will approach this question by showing that chaos can be defined via mixing, which has never before been explicitly argued for. Based on this insight, I will propose that the sought-after new implication of chaos for unpredictability is the following: for predicting any event, all sufficiently past events are approximately probabilistically irrelevant. (shrink)

We distinguish dynamical and statistical interpretations of evolutionary theory. We argue that only the statistical interpretation preserves the presumed relation between natural selection and drift. On these grounds we claim that the dynamical conception of evolutionary theory as a theory of forces is mistaken. Selection and drift are not forces. Nor do selection and drift explanations appeal to the (sub-population-level) causes of population level change. Instead they explain by appeal to the statistical structure of populations. We briefly discuss the implications (...) of the statistical interpretation of selection for various debates within the philosophy of biologythe `explananda of selection' debate and the `units of selection' debate. (shrink)

There are two competing interpretations of the modern synthesis theory of evolution: the dynamical (also know as ‘traditional’) and the statistical. The dynamical interpretation maintains that explanations offered under the auspices of the modern synthesis theory articulate the causes of evolution. It interprets selection and drift as causes of population change. The statistical interpretation holds that modern synthesis explanations merely cite the statistical structure of populations. This paper offers a defense of statisticalism. It argues that a change in trait frequencies (...) in a population can be attributed only to selection or drift against the background of a particular statistical description of the population. The traditionalist supposition that selection and drift are description‐independent causes of population change leads the dynamical interpretation into a dilemma: it must face a contradiction or accept the loss of explanatory power. (shrink)

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: [email protected]. (shrink)

Recently, several philosophers have challenged the view that evolutionary theory is usefully understood by way of an analogy with Newtonian mechanics. Instead, they argue that evolutionary theory is merely a statistical theory. According to this alternate approach, natural selection and random genetic drift are not even causes, much less forces. I argue that, properly understood, the Newtonian analogy is unproblematic and illuminating. I defend the view that selection and drift are causes in part by attending to a pair of important (...) distinctions—that between process and product and that between natural selection and fitness. (shrink)

In "The Indeterministic Character of Evolutionary Theory: No 'Hidden Variables Proof' But No Room for Determinism Either," Brandon and Carson (1996) argue that evolutionary theory is statistical because the processes it describes are fundamentally statistical. In "Is Indeterminism the Source of the Statistical Character of Evolutionary Theory?" Graves, Horan, and Rosenberg (1999) argue in reply that the processes of evolutionary biology are fundamentally deterministic and that the statistical character of evolutionary theory is explained by epistemological rather than ontological considerations. In (...) this paper I focus on the topic of mutation. By focusing on some of the theory and research on this topic from early to late, I show how quantum indeterminism hooks up to point mutations (via tautomeric shifts, proton tunneling, and aqueous thermal motion). I conclude with a few thoughts on some of the wider implications of this topic. (shrink)

Recently, a number of philosophers of biology have endorsed views about random drift that, we will argue, rest on an implicit assumption that the meaning of concepts such as drift can be understood through an examination of the mathematical models in which drift appears. They also seem to implicitly assume that ontological questions about the causality of terms appearing in the models can be gleaned from the models alone. We will question these general assumptions by showing how the same equation (...) — the simple 2 = p2 + 2pq + q2 — can be given radically different interpretations, one of which is a physical, causal process and one of which is not. This shows that mathematical models on their own yield neither interpretations nor ontological conclusions. Instead, we argue that these issues can only be resolved by considering the phenomena that the models were originally designed to represent and the phenomena to which the models are currently applied. When one does take those factors into account, starting with the motivation for Sewall Wright’s and R.A. Fisher’s early drift models and ending with contemporary applications, a very different picture of the concept of drift emerges. On this view, drift is a term for a set of physical processes, namely, indiscriminate sampling processes. (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)

There are three related criteria that a concept of fitness should be able to meet: it should render the principle of natural selection non-tautologous and it should be explanatory and predictive. I argue that for fitness to be able to fulfill these criteria, it cannot be a property that changes over the course of an individual's life. Rather, I introduce a fitness concept--Block Fitness--and argue that an individual's genes and environment fix its fitness in such a way that each individual's (...) fitness has a fixed value over its lifetime. (shrink)

In this paper, it is argued that selection and drift might be distinct. This contradicts recent arguments by Brandon (forthcoming) and Matthen and Ariew (2002) that such a distinction “violates sound probabilistic thinking” (Matthen and Ariew 2002, 62). While their arguments might be valid under certain assumptions, they overlook a possible way to make sense of the distinction. Whether this distinction makes sense, I argue, depends on the source of probabilities in natural selection. In particular, if the probabilities used in (...) defining fitness values are at least partly a result of abstracting from or ignoring certain features of the environment, then selection and drift might in fact be causally distinct. (shrink)

We critically examine Denis Walsh’s latest attack on the causalist view of fitness. Relying on Judea Pearl’s Sure-Thing Principle and geneticist John Gillespie’s model for fitness, Walsh has argued that the causal interpretation of fitness results in a reductio. We show that his conclusion only follows from misuse of the models, that is, (1) the disregard of the real biological bearing of the population-size parameter in Gillespie’s model and (2) the confusion of the distinction between ordinary probability and Pearl’s causal (...) probability. Properly understood, the models used by Walsh do not threaten the causalist view of fitness. (shrink)

The concept of "fitness" is a notion of central importance to evolutionary theory. Yet the interpretation of this concept and its role in explanations of evolutionary phenomena have remained obscure. We provide a propensity interpretation of fitness, which we argue captures the intended reference of this term as it is used by evolutionary theorists. Using the propensity interpretation of fitness, we provide a Hempelian reconstruction of explanations of evolutionary phenomena, and we show why charges of circularity which have been levelled (...) against explanations in evolutionary theory are mistaken. Finally, we provide a definition of natural selection which follows from the propensity interpretation of fitness, and which handles all the types of selection discussed by biologists, thus improving on extant definitions. (shrink)

Biologists and philosophers have been extremely pessimistic about the possibility of demonstrating random drift in nature, particularly when it comes to distinguishing random drift from natural selection. However, examination of a historical case-Maxime Lamotte's study of natural populations of the land snail, Cepaea nemoralis in the 1950s - shows that while some pessimism is warranted, it has been overstated. Indeed, by describing a unique signature for drift and showing that this signature obtained in the populations under study, Lamotte was able (...) to make a good case for a significant role for drift. It may be difficult to disentangle the causes of drift and selection acting in a population, but it is not impossible. (shrink)

The latter half of the twentieth century has been marked by debates in evolutionary biology over the relative significance of natural selection and random drift: the so-called “neutralist/selectionist” debates. Yet John Beatty has argued that it is difficult, if not impossible, to distinguish the concept of random drift from the concept of natural selection, a claim that has been accepted by many philosophers of biology. If this claim is correct, then the neutralist/selectionist debates seem at best futile, and at worst, (...) meaningless. I reexamine the issues that Beatty raises, and argue that random drift and natural selection, conceived as processes, can be distinguished from one another. (shrink)

In my contribution to the Symposium ("On the Vagaries of Determinism and Indeterminism"), I will identify several issues that arise in trying to decide whether Newtonian particle mechanics qualifies as a deterministic theory. I'll also give a mini-tutorial on the geometry and dynamical properties of Norton's dome surface. The goal is to better understand how his example works, and better appreciate just how wonderfully strange it is.

The concept of fitness, central to population genetics and to the synthetic theory of evolution, is discussed. After a historical introduction on the origin of this concept, the current meaning of it in population genetics is examined: a cause of the selective process and its quantification. Several difficulties arise for its exact definition. Three adequacy criteria for such a definition are formulated. It is shown that it is impossible to formulate an adequate definition of fitness respecting these criteria. The propensity (...) definition of fitness is presented and rejected. Finally it is argued that fitness is a conceptual device, a useful tool, only for descriptive purposes of selective processes, changing from case to case, and thus devoid of any substantial physical counterpart. Any attempt to its reification is an apport to the metaphysical load evolutionary theory has inherited from Natural Theology. (shrink)

We argue that Brandon and Carson's (1996) "The Indeterministic Character of Evolutionary Theory" fails to identify any indeterminism that would require evolutionary theory to be a statistical or probabilistic theory. Specifically, we argue that (1) their demonstration of a mechanism by which quantum indeterminism might "percolate up" to the biological level is irrelevant; (2) their argument that natural selection is indeterministic because it is inextricably connected with drift fails to join the issue with determinism; and (3) their view that experimental (...) methodology in botany assumes indeterminism is both false and incompatible with the commitment to discoverable causal mechanisms underlying biological processes. We remain convinced that the probabilism of the theory of evolution is epistemically, not ontologically, motivated. (shrink)

I argue that results from foraging theory give us good reason to think some evolutionary phenomena are indeterministic and hence that evolutionary theory must be probabilistic. Foraging theory implies that random search is sometimes selectively advantageous, and experimental work suggests that it is employed by a variety of organisms. There are reasons to think such search will sometimes be genuinely indeterministic. If it is, then individual reproductive success will also be indeterministic, and so too will frequency change in populations of (...) organisms employing such search. (shrink)

One central tenet of the Modern Evolutionary Synthesis , and the consensus view among biologists until now, is that all genetic mutations occur by “chance” or at “random” with respect to adaptation. However, the discovery of some molecular mechanisms enhancing mutation rate in response to environmental conditions has given rise to discussions among biologists, historians and philosophers of biology about the “chance” vs “directed” character of mutations . In fact, some argue that mutations due to a particular kind of mutator (...) mechanisms challenge the Modern Synthesis because they are produced when and where needed by the organisms concerned. This paper provides a defense of the Modern Synthesis’ consensus view about the chance nature of all genetic mutations by reacting to Jablonka and Lamb’s analysis of genetic mutations and the explicit Lamarckian flavor of their arguments. I argue that biologists can continue to talk about chance mutations according to what I call and define as the notion of “evolutionary chance,” which I claim is the Modern Synthesis’ consensus view and a reformulation of Darwin’s most influential idea of “chance” variation. Advances in molecular genetics are therefore significant but not revolutionary with respect to the Modern Synthesis’ paradigm. (shrink)

This article offers three contrasting cases of the use of neutrality and drift in molecular evolution. In the first, neutrality is assumed as a simplest case for modeling. In the second and third, concepts of drift and neutrality are developed within the context of population genetics testing and the development and application of the molecular clock.

Biologists in the last 50 years have increasingly emphasized the role of historical contingency in explaining the distribution and dynamics of biological systems. However, recent work in philosophy of biology has shown that historical contingency carries various interpretations and that we are still lacking a general understanding of historicity, i.e., a framework from which to interpret why and to what extent history matters in biological processes. Building from examples and analyses of the long-term experimental evolution (LTEE) project, this paper argues (...) that historicity possess three essential conditions: (1) multiple possible pasts, (2) multiple possible outcomes at a given instant, and (3) a relationship of causal dependence between these two sets. These criteria can be further specified in two general forms of historicity: dependence on initial conditions and path dependence. More attention is devoted to developing a rigorous account of the latter, which captures the type of historicity displayed by stochastic processes. This paper also highlights that it is often more productive to adopt an instant-relative approach and think in terms of degree of historicity instead of trying to maintain a rigid and absolute dichotomy between historical and ahistorical (completely convergent) processes. (shrink)

In this paper we first briefly review Bell's (1964, 1966) Theorem to see how it invalidates any deterministic "hidden variable" account of the apparent indeterminacy of quantum mechanics (QM). Then we show that quantum uncertainty, at the level of DNA mutations, can "percolate" up to have major populational effects. Interesting as this point may be it does not show any autonomous indeterminism of the evolutionary process. In the next two sections we investigate drift and natural selection as the locus of (...) autonomous biological indeterminacy. Here we conclude that the population-level indeterminacy of natural selection and drift are ultimately based on the assumption of a fundamental indeterminacy at the level of the lives and deaths of individual organisms. The following section examines this assumption and defends it from the determinists' attack. Then we show that, even if one rejects the assumption, there is still an important reason why one might think evolutionary theory (ET) is autonomously indeterministic. In the concluding section we contrast the arguments we have mounted against a deterministic hidden variable account of ET with the proof of the impossibility of such an account of QM. (shrink)

Among the liveliest disputes in evolutionary biology today are disputes concerning the role of chance in evolution--more specifically, disputes concerning the relative evolutionary importance of natural selection vs. so-called "random drift". The following discussion is an attempt to sort out some of the broad issues involved in those disputes. In the first half of this paper, I try to explain the differences between evolution by natural selection and evolution by random drift. On some common construals of "natural selection", those two (...) modes of evolution are completely indistinguishable. Even on a proper construal of "natural selection", it is difficult to distinguish between the "improbable results of natural selection" and evolution by random drift. In the second half of this paper, I discuss the variety of positions taken by evolutionists with respect to the evolutionary importance of random drift vs. natural selection. I will then consider the variety of issues in question in terms of a conceptual distinction often used to describe the rise of probabilistic thinking in the sciences. I will argue, in particular, that what is going on here is not, as might appear at first sight, just another dispute about the desirability of "stochastic" vs. "deterministic" theories. Modern evolutionists do not argue so much about whether evolution is stochastic, but about how stochastic it is. (shrink)

Recently advocates of the propensity interpretation of fitness have turned critics. To accommodate examples from the population genetics literature they conclude that fitness is better defined broadly as a family of propensities rather than the propensity to contribute descendants to some future generation. We argue that the propensity theorists have misunderstood the deeper ramifications of the examples they cite. These examples demonstrate why there are factors outside of propensities that determine fitness. We go on to argue for the more general (...) thesis that no account of fitness can satisfy the desiderata that have motivated the propensity account. (shrink)

The central point of this essay is to demonstrate the incommensurability of ‘Darwinian fitness’ with the numeric values associated with reproductive rates used in population genetics. While sometimes both are called ‘fitness’, they are distinct concepts coming from distinct explanatory schemes. Further, we try to outline a possible answer to the following question: from the natural properties of organisms and a knowledge of their environment, can we construct an algorithm for a particular kind of organismic life-history pattern that itself will (...) allow us to predict whether a type in the population will increase or decrease relative to other types? Introduction Darwinian fitness Reproductive fitness and genetical models of evolution The models of reproductive fitness 4.1 The Standard Viability Model 4.2 Frequency-dependent selection 4.3 Fertility models 4.4 Overlapping generations Fitness as outcome 5.1 Fitness as actual increase in type 5.2 Fitness as expected increase in type 5.2.1 Expected increase within a generation 5.2.2 Expected increase between generations 5.2.3 Postponed reproductive fitness effects The book-keeping problem Conclusion. (shrink)

The central point of this essay is to demonstrate the incommensurability of ‘Darwinian fitness’ with the numeric values associated with reproductive rates used in population genetics. While sometimes both are called ‘fitness’, they are distinct concepts coming from distinct explanatory schemes. Further, we try to outline a possible answer to the following question: from the natural properties of organisms and a knowledge of their environment, can we construct an algorithm for a particular kind of organismic life-history pattern that itself will (...) allow us to predict whether a type in the population will increase or decrease relative to other types? 1. Introduction2. Darwinian fitness3. Reproductive fitness and genetical models of evolution4. The models of reproductive fitness4.1 The Standard Viability Model4.2 Frequency-dependent selection4.3 Fertility models4.4 Overlapping generations5. Fitness as outcome5.1 Fitness as actual increase in type5.2 Fitness as expected increase in type5.2.1 Expected increase within a generation5.2.2 Expected increase between generations5.2.3 Postponed reproductive fitness effects6. The book-keeping problem7. Conclusion. (shrink)

It’s recently been argued that biological fitness can’t change over the course of an organism’s life as a result of organisms’ behaviors. However, some characterizations of biological function and biological altruism tacitly or explicitly assume that an effect of a trait can change an organism’s fitness. In the first part of the paper, I explain that the core idea of changing fitness can be understood in terms of conditional probabilities defined over sequences of events in an organism’s life. The result (...) is a notion of “conditional fitness” which is static but which captures intuitions about apparent behavioral effects on fitness. The second part of the paper investigates the possibility of providing a systematic foundation for conditional fitness in terms of spaces of sequences of states of an organism and its environment. I argue that the resulting “organism–environment history conception” helps unify diverse biological perspectives, and may provide part of a metaphysics of natural selection. (shrink)

1 The Zero-Force Evolutionary Law 2 Randomness, Hierarchy, and Constraint 3 Diversity 4 Complexity 5 Evidence, Predictions, and Tests 6 Philosophical Foundations 7 Implications.

Compares classic and contemporary theories of genetics and evolution and explores the role of teleological thought in biology.

In this important new study Ian Hacking continues the enquiry into the origins and development of certain characteristic modes of contemporary thought undertaken in such previous works as his best selling Emergence of Probability. Professor Hacking shows how by the late nineteenth century it became possible to think of statistical patterns as explanatory in themselves, and to regard the world as not necessarily deterministic in character. Combining detailed scientific historical research with characteristic philosophic breath and verve, The Taming of Chance (...) brings out the relations among philosophy, the physical sciences, mathematics and the development of social institutions, and provides a unique and authoritative analysis of the "probabilization" of the Western world. (shrink)

How do fitness and natural selection relate to other evolutionary factors like architectural constraint, mode of reproduction, and drift? In one way of thinking, drawn from Newtonian dynamics, fitness is one force driving evolutionary change and added to other factors. In another, drawn from statistical thermodynamics, it is a statistical trend that manifests itself in natural selection histories. It is argued that the first model is incoherent, the second appropriate; a hierarchical realization model is proposed as a basis for a (...) statistical treatment. It emerges that natural selection does not cause evolution; it just is evolution. The theory incorporates relations of statistical correlation, but not the kind of causation found in fundamental physical processes. (shrink)

This article explores the connection between objective chance and the randomness of a sequence of outcomes. Discussion is focussed around the claim that something happens by chance iff it is random. This claim is subject to many objections. Attempts to save it by providing alternative theories of chance and randomness, involving indeterminism, unpredictability, and reductionism about chance, are canvassed. The article is largely expository, with particular attention being paid to the details of algorithmic randomness, a topic relatively unfamiliar to philosophers.

There have been many claims that quantum mechanics plays a key role in the origin and/or operation of biological organisms, beyond merely providing the basis for the shapes and sizes of biological molecules and their chemical affinities. These range from Schr¨odinger’s suggestion that quantum fluctuations produce mutations, to Hameroff and Penrose’s conjecture that quantum coherence in microtubules is linked to consciousness. I review some of these claims in this paper, and discuss the serious problem of decoherence. I advance some further (...) conjectures about quantum information processing in bio-systems. Some possible experiments are suggested. © 2004 Elsevier Ireland Ltd. All rights reserved. (shrink)

I deny that the world is fundamentally causal, deriving the skepticism on non-Humean grounds from our enduring failures to find a contingent, universal principle of causality that holds true of our science. I explain the prevalence and fertility of causal notions in science by arguing that a causal character for many sciences can be recovered, when they are restricted to appropriately hospitable domains. There they conform to loose and varying collections of causal notions that form folk sciences of causation. This (...) recovery of causation exploits the same generative power of reduction relations that allows us to recover gravity as a force from Einstein's general relativity and heat as a conserved fluid, the caloric, from modern thermal physics, when each theory is restricted to appropriate domains. Causes are real in science to the same degree as caloric and gravitational forces. (shrink)

When philosophers defend epiphenomenalist doctrines, they often do so by way of a priori arguments. Here we suggest an empirical approach that is modeled on August Weismann’s experimental arguments against the inheritance of acquired characters. This conception of how epiphenomenalism ought to be developed helps clarify some mistakes in two recent epiphenomenalist positions – Jaegwon Kim’s (1993) arguments against mental causation, and the arguments developed by Walsh (2000), Walsh, Lewens, and Ariew (2002), and Matthen and Ariew (2002) that natural selection (...) and drift are not causes of evolution. A manipulationist account of causation (Woodward 2003) leads naturally to an account of how macro- and micro-causation are related and to an understanding of how epiphenomenalism at different levels of organization should be understood. (shrink)

I deny that the world is fundamentally causal, deriving the skepticism on non-Humean grounds from our enduring failures to find a contingent, universal principle of causality that holds true of our science. I explain the prevalence and fertility of causal notions in science by arguing that a causal character for many sciences can be recovered, when they are restricted to appropriately hospitable domains. There they conform to a loose collection of causal notions that form a folk science of causation. This (...) recovery of causation exploits the same generative power of reduction relations that allows us to recover gravity as a force from Einstein's general relativity and heat as a conserved fluid, the caloric, from modern thermal physics, when each theory is restricted to appropriate domains. Causes are real in science to the same degree as caloric and gravitational forces. (shrink)

Evolutionary theory is awash with probabilities. For example, natural selection is said to occur when there is variation in fitness, and fitness is standardly decomposed into two components, viability and fertility, each of which is understood probabilistically. With respect to viability, a fertilized egg is said to have a certain chance of surviving to reproductive age; with respect to fertility, an adult is said to have an expected number of offspring.1 There is more to evolutionary theory than the theory of (...) natural selection, and here too one finds probabilistic concepts aplenty. When there is no selection, the theory of neutral evolution says that a gene’s chance of eventually reaching fixation is 1/(2N), where N is the number of organisms in the generation of the diploid population to which the gene belongs. The evolutionary consequences of mutation are likewise conceptualized in terms of the probability per unit time a gene has of changing from one state to another. The examples just mentioned are all “forwarddirected” probabilities; they describe the probability of later events, conditional on earlier events. However, evolutionary theory also uses “backwards probabilities” that describe the probability of a cause conditional on its effects; for example, coalescence theory allows one to calculate the expected number of generations in the past that the genes in the present generation find their most recent common ancestor. (shrink)