Elliott Sober

After clarifying how Darwin understood natural selection and common ancestry, I consider how the two concepts are related in his theory. I argue that common ancestry has an evidential priority. For Darwin, arguments about natural selection often make use of the assumption of common ancestry, whereas defending common ancestry does not require the assumption that natural selection has been at work. In fact, Darwin held that the key evidence for common ancestry comes from characters whose evolution is not caused by natural selection. This raises the question of why Darwin puts natural selection first and foremost in the Origin.

In this paper I want to clarify what biologists are talking about when they talk about the evolution of altruism. I'll begin by saying something about the common sense concept. This familiar idea I'll call 'vernacular altruism.' One point of doing this is to make it devastatingly obvious that the common sense concept is very different from the concept as it's used in evolutionary theory. After that preliminary, I'll describe some features of the evolutionary concept. Then I'll conclude by briefly considering what explanatory relation might obtain between vernacular altruism and evolutionary altruism.

In what follows I will discuss an example of the Duhem-Quine problem in which Pr(H A), Pr(A H), and Pr(OI +H& ?A) (where H is the hypothesis, A the auxiliary assumptions, and O the observational prediction) can be construed objectively; however, only some of those quantities are relevant to the analysis that I provide. The example involves medical diagnosis. The goal is to test the hypothesis that someone has tuberculosis; the auxiliary assumptions describe the er- ror characteristics of the test procedure. Although it can make sense to talk about the objective probability that someone (randomly drawn from a given population) has tuberculosis and it also can make sense to talk about the objective probability that a test procedure has a certain set of error characteristics, neither of these quantities will enter into the analysis. The analysis proceeds entirely via likelihoods, what one needs to consider is just the probability of the observations conditional on four conjunctions of the form (?H & +A).' It is a special feature of the example that all four of these conjunctions are simple statistical hypotheses in the technical sense that each unambigu-ously confers a probability on the observations.'o After describing how the likelihood concept applies to the example concerning medical diagnosis, I will show how similar patterns can arise in the context of a second inferential framework-that of H. Akaike's criterion of model selection;" this time the example will involve phylogenetic inference.

The debate over the relative importance of natural selection as compared to other forces affecting the evolution of organisms is a long-standing and central controversy in evolutionary biology. The theory of adaptationism argues that natural selection contains sufficient explanatory power in itself to account for all evolution. However, there are differing views about the efficiency of the adaptation model of explanation. If the adaptationism theory is applied, are energy and resources being used to their optimum? This book presents an up-to-date view of this controversy and reflects the dramatic changes in our understanding of evolution that have occurred in the last twenty years. The volume combines contributions from biologists and philosophers, and offers a systematic treatment of foundational, conceptual, and methodological issues surrounding the theory of adaptationism. The essays examine recent developments in topics such as phylogenetic analysis, the theory of optimality and ess models, and methods of testing models.

In this brief space I want to describe how Chomsky's analysis of "psychological reality" departs from what I think is a fairly standard construal of the idea. This familiar formulation arises from distinguishing between someone's following a rule and someone's acting in conformity with a rule. The former idea, but not the latter, involves the idea that the person has some mental representation of the rule that plays a certain causal role in determining behavior. Although there may be many grammatical rules to which a person's verbal behavior (ignoring slips of the tongue and other performance interferences) conforms, only some of those rules have psychological reality; these are the ones that are internalized in thought and play some appropriate causal role.

My critical remarks' on Alexander Rosenberg’s article on fitness have elicited a rejoinder from Mary Williams and Rosenberg himself. They charge that my criticisms are a “tissue of misunderstandings” (738); since they misunderstand my own position in fundamental ways, it may help to try to clarify the points that divide us. In the interest of brevity, I will ignore technical issues concerning the internal correctness of Williams’s axiomatization and will focus on questions of broader philosophical interest.

In a recent article, Kim Sterelny and Philip Kitcher5 defend a version of genic selectionism and attempt to refute the criticisms I made of that doctrine. Their defense has two components. First, they find fault with the account I gave of the units-of-selection controversy-an account which uses the idea of probabilistic causality as a tool of explication. Second, they provide a positive account of their own of what that controversy concerns, one which they think allows genic selectionism to emerge as a successful thesis. I believe that the position they sketch is mistaken, both in its general orientation and in its details. I believe that the Sterelny/ Kitcher position misunderstands what the biological question of the units of selection is about and that their criticisms of my own proposal are mistaken as well.

The logical empiricists said some good things about epistemology and scientific method. However, they associated those epistemological ideas with some rather less good ideas about philosophy of language. There is something epistemologically suspect about statements that cannot be tested. But to say that those statements are meaningless is to go too far. And there is something impossible about trying to figure out which of two empirically equivalent theories is true. But to say that those theories are synonymous is also to go too far. My goal in this paper is not to resuscitate all these positivist ideas, but to revisit just one of them. Instrumentalism is the idea that theories are instruments for making predictions. Of course, no one would disagree that this is one of the things we use theories to do. In just the same way, no one could disagree with the emotivist claim that one of the things we do with ethical terms like "good" and "right" is to express our feelings of approval and disapproval. Instrumentalism and emotivism become contentious, and therefore interesting, when these claims are supplemented.

This paper proposes a game-theoretic solution of the surprise examination problem. It is argued that the game of “matching pennies” provides a useful model for the interaction of a teacher who wants her exam to be surprising and students who want to avoid being surprised. A distinction is drawn between prudential and evidential versions of the problem. In both, the teacher should not assign a probability of zero to giving the exam on the last day. This representation of the problem provides a diagnosis of where the backwards induction argument, which “proves” that no surprise exam is possible, is mistaken.

This paper defends two theses about probabilistic reasoning. First, although modus ponens has a probabilistic analog, modus tollens does not – the fact that a hypothesis says that an observation is very improbable does not entail that the hypothesis is improbable. Second, the evidence relation is essentially comparative; with respect to hypotheses that confer probabilities on observation statements but do not entail them, an observation O may favor one hypothesis H1 over another hypothesis H2 , but O cannot be said to confirm or disconfirm H1 without such relativization. These points have serious consequences for the Intelligent Design movement. Even if evolutionary theory entailed that various complex adaptations are very improbable, that would neither disconfirm the theory nor support the hypothesis of intelligent design. For either of these conclusions to follow, an additional question must be answered: With respect to the adaptive features that evolutionary theory allegedly says are very improbable, what is their probability of arising if they were produced by intelligent design? This crucial question has not been addressed by the ID movement.

The chapter discusses the principle of conservatism and traces how the general principle is related to the specific one. This tracing suggests that the principle of conservatism needs to be refined. Connecting the principle in cognitive science to more general questions about scientific inference also allows us to revisit the question of realism versus instrumentalism. The framework deployed in model selection theory is very general; it is not specific to the subject matter of science. The chapter outlines some non-Bayesian ideas that have been developed in model selection theory. The principle of conservatism, like C. Lloyd Morgan's canon, describes a preference concerning kinds of parameters. It says that a model that postulates only lower-level intentionality is preferable to one that postulates higher-level intentionality if both fit the data equally well. The model selection approach to parsimony helps explain why unification is a theoretical virtue.

According to information processing models of cognition, such as Chomsky's, the set of well-formed formulae of any natural language must be recursively enumerable (RE), otherwise, human learning language is impossible. I argue that there is nothing unlearnable about languages that are not RE. Insofar as natural languages turn out to be RE, this is to be accounted for on grounds of simplicity and not by appeal to the mistaken claim that nonRE languages are ruled out a priori. A consequence of this position is that grammars will be somewhat depsychologized, and the acquisition of competence will come to be seen as a matter of degree - perhaps admitting of refinement and improvement without end.

Maximum Parsimony (MP) and Maximum Likelihood (ML) are two methods for evaluating which phlogenetic tree is best supported by data on the characteristics of leaf objects (which may be species, populations, or individual organisms). MP has been criticized for assuming that evolution proceeds parsimoniously -- that if a lineage begins in state i and ends in state j, the way it got from i to j is by the smallest number of changes. MP has been criticized for needing to assume some model or other of the evolutionary process even though biologists often do not know what that process really is. This paper critically evaluates both criticisms.

Elliott Sober is one of the leading philosophers of science and is a former winner of the Lakatos Prize, the major award in the field. This new collection of essays will appeal to a readership that extends well beyond the frontiers of the philosophy of science. Sober shows how ideas in evolutionary biology bear in significant ways on traditional problems in philosophy of mind and language, epistemology, and metaphysics. Amongst the topics addressed are psychological egoism, solipsism, and the interpretation of belief and utterance, empiricism, Ockham's razor, causality, essentialism, and scientific laws. The collection will prove invaluable to a wide range of philosophers, primarily those working in the philosophy of science, the philosophy of mind, and epistemology.

In both biology and the human sciences, social groups are sometimes treated as adaptive units whose organization cannot be reduced to individual interactions. This group-level view is opposed by a more individualistic one that treats social organization as a byproduct of self-interest. According to biologists, group-level adaptations can evolve only by a process of natural selection at the group level. Most biologists rejected group selection as an important evolutionary force during the 1960s and 1970s but a positive literature began to grow during the 1970s and is rapidly expanding today. We review this recent literature and its implications for human evolutionary biology. We show that the rejection of group selection was based on a misplaced emphasis on genes as “replicators” which is in fact irrelevant to the question of whether groups can be like individuals in their functional organization. The fundamental question is whether social groups and other higher-level entities can be “vehicles” of selection. When this elementary fact is recognized, group selection emerges as an important force in nature and what seem to be competing theories, such as kin selection and reciprocity, reappear as special cases of group selection. The result is a unified theory of natural selection that operates on a nested hierarchy of units.The vehicle-based theory makes it clear that group selection is an important force to consider in human evolution. Humans can facultatively span the full range from self-interested individuals to “organs” of group-level “organisms.” Human behavior not only reflects the balance between levels of selection but it can also alter the balance through the construction of social structures that have the effect of reducing fitness differences within groups, concentrating natural selection (and functional organization) at the group level. These social structures and the cognitive abilities that produce them allow group selection to be important even among large groups of unrelated individuals.

To evaluate Hume's thesis that causal claims are always empirical, I consider three kinds of causal statement: ?e1 caused e2 ?, ?e1 promoted e2 ?, and ?e1 would promote e2 ?. Restricting my attention to cases in which ?e1 occurred? and ?e2 occurred? are both empirical, I argue that Hume was right about the first two, but wrong about the third. Standard causal models of natural selection that have this third form are a priori mathematical truths. Some are obvious, others less so. Empirical work on natural selection takes the form of defending causal claims of the first two types. I provide biological examples that illustrate differences among these three kinds of causal claim

I am grateful to Philip Kitcher for inviting me to comment on Alexander Rosenberg's (1996) review of Philosophy of Biology (Sober 1993) and to Rosenberg for his kind words about my book at the very beginning and the very end of his review. However, I cannot help feeling that most of the material in Rosenberg's review describes a different book from the one I wrote. Of the four philosophical claims that he ascribes to me, only one of them is asserted or implied in Philosophy of Biology. Rosenberg is right that I have argued that many evolutionary laws turn out, when stated carefully, to be a priori mathematical truths. However, he is mistaken in thinking that I am a "historicist" who holds that "fundamental theory in biology is narrative." Rosenberg also misconstrues my views on the meaning of probability statements in evolutionary theory.

When philosophers discuss the topic of explanation, they usually have in mind the following question: given the beliefs one has and some proposition that one wishes to explain, which subset of the beliefs constitutes an explanation of the target proposition? That is, the philosophical ‘problem of explanation’ typically has bracketed the issue of how one obtains the beliefs; they are taken as given. The problem of explanation has been the problem of understanding the relation ‘x explains y’. Since Hempel did so much to canonize this way of thinking about explanation, it deserves to be called ‘Hempel's problem’.

Writers like Attneave [I960], Fodor [I968], and Dennett [1978] have argued that explanations of a mental capacity can only avoid the emptiness of Moliere's dormative virtue by decomposing the capacity into a set of components which are more rudimentary. But What is wrong with smart homunculi? I argue that smart homunculi may explain token events, such as why I now see the page in front of me, but they do not explain what seeing is. It is the importance of the latter explanatory problem which explains why homunculi must be so stupid.

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.

How should the concept of evidence be understood? And how does the concept of evidence apply to the controversy about creationism as well as to work in evolutionary biology about natural selection and common ancestry? In this rich and wide-ranging book, Elliott Sober investigates general questions about probability and evidence and shows how the answers he develops to those questions apply to the specifics of evolutionary biology. Drawing on a set of fascinating examples, he analyzes whether claims about intelligent design are untestable; whether they are discredited by the fact that many adaptations are imperfect; how evidence bears on whether present species trace back to common ancestors; how hypotheses about natural selection can be tested, and many other issues. His book will interest all readers who want to understand philosophical questions about evidence and evolution, as they arise both in Darwin's work and in contemporary biological research.

Human nature is intriguing in such that it can express both negative and positive emotions, as in kindness and cruelty. The question is whether both are a natural part of our nature as human beings, or is one produced to serve as the alternate of the other. Another question that is brought to the table in this chapter is how does one determine what is natural and what is not, being its true definition? The chapter attempts to answer these questions based on evolution theory, whether events earlier in history served as a promoter for the emotions of today. Was the nature of kindness and caring inherent in a human being at the beginning of time, or is it only through the changes and events over time that it has developed? The chapter aims to aid the reader in understanding our human tendencies.