Elliott Sober

In what follows, I’ll discuss both the metaphysics and the epistemology of supervenience from a probabilistic point of view. The first half of this paper will explore how supervenience claims are related to other issues; these will include the thesis that physics is causally complete, the claim that there are emergent properties, the idea that mental properties are causally efficacious, and the notion that there are scientific laws about supervenient properties that generalize over systems that deploy different physical realizations of the properties in question. The second half will examine the question of how observational evidence can lend support to supervenience claims. This problem turns out to raise some surprisingly deep issues about the nature of hypothesis testing in science.

God and numbers provide two challenges to metaphysical naturalism–the former if God exists and is a supernatural being, the latter if numbers exist and mathematical Platonism is true. Evolutionary theory is often described as having a commitment to naturalism, but this is doubly wrong. The theory is neutral on the question of whether God exists and mathematical evolutionary theory entails that numbers exist. The chapter develops the point about theistic neutrality by considering what evolutionary biologists mean when they say that mutations are “unguided.” Evolutionary theory is logically compatible with deism and also with various interventionist theologies. In connection with mathematical evolutionary theory, the chapter discusses and criticizes the indispensability argument for mathematical Platonism developed by Quine and Putnam. The chapter criticizes their epistemological holism by considering ideas in Bayesian confirmation theory.

Philosophers have explored objective interpretations of probability mainly by considering empirical probability statements. Because of this focus, it is widely believed that the logical interpretation and the actual-frequency interpretation are unsatisfactory and the hypothetical-frequency interpretation is not much better. Probabilistic assertions in pure mathematics present a new challenge. Mathematicians prove theorems in number theory that assign probabilities. The most natural interpretation of these probabilities is that they describe actual frequencies in finite sets and limits of actual frequencies in infinite sets. This interpretation vindicates part of what the logical interpretation of probability aimed to establish.

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.

Ockham's razor, the principle of parsimony, states that simpler theories are better than theories that are more complex. It has a history dating back to Aristotle and it plays an important role in current physics, biology, and psychology. The razor also gets used outside of science - in everyday life and in philosophy. This book evaluates the principle and discusses its many applications. Fascinating examples from different domains provide a rich basis for contemplating the principle's promises and perils. It is obvious that simpler theories are beautiful and easy to understand; the hard problem is to figure out why the simplicity of a theory should be relevant to saying what the world is like. In this book, the ABCs of probability theory are succinctly developed and put to work to describe two 'parsimony paradigms' within which this problem can be solved.

Nelson Goodman suggests that a generalization of the form “all A’s are B” is confirmable by an observed instance only if the generalization is law-like. Jackson and Pargetter deny this and give examples of how accidental generalizations can be confirmed. A possible response from Goodman appears to make these accidental generalizations look law-like, but I show it’s defective. And Jackson and Pargetter's substitute nomological condition fares no better than Goodman’s. Because of the multiplicity of possible background assumptions, I doubt that there is a single “nomological condition” that each and every act of confirmation must obey.

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’.

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.

Realists persuaded by indispensability arguments af- firm the existence of numbers, genes, and quarks. Van Fraassen's empiricism remains agnostic with respect to all three. The point of agreement is that the posits of mathematics and the posits of biology and physics stand orfall together. The mathematical Platonist can take heart from this consensus; even if the existence of num- bers is still problematic, it seems no more problematic than the existence of genes or quarks. If the two positions just described were the only ones possible, there could be no objection to this melding of numbers with genes and quarks. However, the position I call contrastive empiricism (Sober 1990a) stands opposed to both realism and to Van Fraassen's em- piricism. As it turns out, contrastive empiricism entails that coalesc- ing mathematics with empirical science is highly problematic. I believe that there is an important kernel of truth in abductive ar- guments for genes and quarks. But no counterpart argument exists for the case of numbers. Of course, the existence of this third way would be uninteresting, if contrastive empiricism were wholly implausible. However, I will argue that contrastive empiricism captures what makes sense in standard versions of realism and empiricism, while avoiding the excesses of each. This third way is a middle way; it cannot be dismissed out of hand.

This paper is a sympathetic critique of the argument that Reichenbach develops in Chap. 2 of Experience and Prediction for the thesis that sense experience justifies belief in the existence of an external world. After discussing his attack on the positivist theory of meaning, I describe the probability ideas that Reichenbach presents. I argue that Reichenbach begins with an argument grounded in the Law of Likelihood but that he then endorses a different argument that involves prior probabilities. I try to show how this second step in Reichenbach's approach can be strengthened by using ideas that have been developed recently for understanding causation in terms of the idea of intervention

I want to explain some of the gaps I see between the concepts of morality and altruism. Indeed, there are three concepts here that need to be disentangled, not just two. Evolutionists use the terms “altruism” and “selfishness” in a way that differs from the usage found in ordinary parlance. So my goal is to separate evolutionary altruism, psychological altruism, and morality. Morality includes a variety of characteristics. There is more to morality than altruism. If we can avoid the mistake of thinking we have explained the whole when we have explained only the part, we may yet be able to advance our understanding of what morality is and where it came from.

A distinction is drawn between property causation and token causation. According to the former, a positive causal factor in a population raises the probability of its effects within "background contexts". The latter, which concerns "actual physical connections" between token events, is not explicated here although its distinctness from the first concept and its importance are discussed. The applicability of both is illustrated by two currently controversial issues in evolutionary theory -- the units of selection controversy and the use of parsimony as an inference rule in phylogenetic reconstruction.

I discuss two versions of the doomsday argument. According to ``Gott's Line'',the fact that the human race has existed for 200,000 years licences the predictionthat it will last between 5100 and 7.8 million more years. According to ``Leslie'sWedge'', the fact that I currently exist is evidence that increases the plausibilityof the hypothesis that the human race will come to an end sooner rather than later.Both arguments rest on substantive assumptions about the sampling process thatunderlies our observations. These sampling assumptions have testable consequences,and so the sampling assumptions themselves must be regarded as empirical claims.The result of testing some of these consequences is that both doomsday argumentsare empirically disconfirmed.

In 'Two Dogmas of Empiricism', Quine attacks the analytic/synthetic distinction and defends a doctrine that I call epistemological holism. Now, almost fifty years after the article's appearance, what are we to make of these ideas? I suggest that the philosophical naturalism that Quine did so much to promote should lead us to reject Quine's brief against the analytic/synthetic distinction; I also argue that Quine misunderstood Carnap's views on analyticity. As for epistemological holism, I claim that this thesis does not follow from the logical point that Duhem and Quine made about the role of auxiliary assumptions in hypothesis testing, and that the thesis should be rejected. \\\ [Peter Hylton] Section I of this essay discusses Quine's views about reference, contrasting them with those of Russell. For the latter, our language and thought succeed in being about the world because of our acquaintance with objects; the relation of reference-roughly, the relation between a name and its bearer-is thus fundamental. For Quine, by contrast, the fundamental relation by which our language comes to be about the world, and to have empirical content, is that between a sentence and stimulations of our sensory surfaces; reference, while important, is a derivative notion. Section II shows how this view of reference as derivative makes possible the notorious Quinean doctrine of ontological relativity. Section III raises the issue of realism. It argues that somewhat different notions of realism are in play for Quine and for Russell-for Russell, objects, and our knowledge of objects, play the fundamental role, while for quine objectivity and truth are fundamental, with ontology being derivative.

Adaptationism is a doctrine that has meant different things to different people. In this essay, I want to isolate and discuss a reading of adaptationism that makes it a non-trivial empirical thesis about the history of life. I'll take adaptationism to be the following claim: natural selection has been the only important cause of most of the phenotypic traits found in most species. I won't try to determine whether adaptationism, so defined, is true. Rather, my task will be one of clarification. What does this statement mean, and how is it related to various remarks that biologists have made about adaptationism, pro and con?

The argument from design is best understood as a likelihood inference. Its Achilles heel is our lack of knowledge concerning the aims and abilities that the putative designer would have; in consequence, it is impossible to determine whether the observations are more probable under the design hypothesis than they are under the hypothesis of chance. Hypotheses about the role played by natural selection in the history of life also can be evaluated within a likelihood framework, and here too there are auxiliary assumptions that need to be in place if the likelihoods of selection and chance are to be compared. I describe some problems that arise in connection with the project of obtaining independent evidence concerning those auxiliary assumptions.

We argue elsewhere that explanatoriness is evidentially irrelevant . Let H be some hypothesis, O some observation, and E the proposition that H would explain O if H and O were true. Then O screens-off E from H: Pr = Pr. This thesis, hereafter “SOT” , is defended by appeal to a representative case. The case concerns smoking and lung cancer. McCain and Poston grant that SOT holds in cases, like our case concerning smoking and lung cancer, that involve frequency data. However, McCain and Poston contend that there is a wider sense of evidential relevance—wider than the sense at play in SOT—on which explanatoriness is evidentially relevant even in cases involving frequency data. This is their main point, but they also contend that SOT does not hold in certain cases not involving frequency data. We reply to each of these points and conclude with some general remarks on screening-off as a test of evidential relevance

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.

This book consists of four essays on Darwin’s theory of evolution and three postscripts on contemporary evolutionary theory. The main questions that the chapters address are: How are common ancestry and natural selection related to each other in Darwin’s theory? What were Darwin’s views about group selection and the evolution of altruism? Why did Darwin change his mind about sex ratio, and how are his ideas related to the creationism that preceded him and the evolutionary biology that followed? Do Darwin’s theory and modern evolutionary theory obey the principle of methodological naturalism and ought they to do so?The book is philosophical because it focuses on the logic of arguments. I attend closely to Darwin’s texts, but I sometimes use tools that Darwin did not have available. These include ideas from contemporary biology and from probability theory. I see merit in this approach because it helps elucidate Darwin’s theory. Darwin pointed to the need for this sort of ..

Is it accurate to label Darwin's theory "the theory of evolution by natural selection," given that the concept of common ancestry is at least as central to Darwin's theory? Did Darwin reject the idea that group selection causes characteristics to evolve that are good for the group though bad for the individual? How does Darwin's discussion of God in The Origin of Species square with the common view that he is the champion of methodological naturalism? These are just some of the intriguing questions raised in this volume of interconnected philosophical essays on Darwin. The author's approach is informed by modern issues in evolutionary biology, but is sensitive to the ways in which Darwin's outlook differed from that of many biologists today. The main topics that are the focus of the book--common ancestry, group selection, sex ratio, and naturalism--have rarely been discussed in their connection with Darwin in such penetrating detail.

Darwin claims in the Origin that similarity is evidence for common ancestry, but that adaptive similarities are ‘almost valueless’ as evidence. This second claim seems reasonable for some adaptive similarities but not for others. Here we clarify and evaluate these and related matters by using the law of likelihood as an analytic tool and by considering mathematical models of three evolutionary processes: directional selection, stabilizing selection, and drift. Our results apply both to Darwin’s theory of evolution and to modern evolutionary biology. 1 Introduction2 The Likelihood Framework3 A Sufficient Condition for a Similarity to Favour Common Ancestry over Separate Ancestry4 The 1/p Criterion and Its Limitations5 Directional Selection versus Drift6 Stabilizing Selection versus Drift7 Going beyond Two Taxa8 ConclusionsAppendix.

In what follows, I propose to evaluate Giere's analysis by applying it to a causal process considered in evolutionary theory, namely, natural selection. To say that there is selection for a given trait is to say that possessing that trait causes differential reproductive success. If there is selection for a trait and if no other evolutionary forces impinge and there is no "sampling error" due to random drift, individuals with the trait will on average have more offspring than individuals without it. But sampling error can't be discounted for finite populations; so the combined effect of selection and drift will be a probability distribution of numbers of offspring. In this event, selection for a trait will imply that the mean value of the distribution associated with the individuals possessing the trait exceeds the mean value for individuals without the trait. Evolutionary theory assigns a probability distribution of possible reproductive outputs to each organism and, thereby, views organisms as stochastic systems. This implies no commitment to indeterminacy at the microlevel, of course.

Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light on the theoretical virtues of parsimoniousness, unification, and non ad hocness, on the dispute about Bayesianism, and on empiricism and scientific realism. * Both of us gratefully acknowledge support from the Graduate School at the University of Wisconsin-Madison, and NSF grant DIR-8822278 (M.F.) and NSF grant SBE-9212294 (E.S.). Special thanks go to A. W. F. Edwards.William Harper. Martin Leckey. Brian Skyrms, and especially Peter Turney for helpful comments on an earlier draft.