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The task of Philosophy in Science (PinS) is to use philosophical tools to help solve scientific problems. This article describes how I stumbled into this line of work and then addressed several topics in philosophy of biology—units of selection, cladistic parsimony, robustness and trade-offs in model building, adaptationism, and evidence for common ancestry—often in collaboration with scientists. I conclude by offering advice for would-be PinS practitioners.

All extant purely probabilistic measures of explanatory power satisfy the following technical condition: if Pr(E | H1) > Pr(E | H2) and Pr(E | ∼H1) < Pr(E | ∼H2), then H1’s explanatory power with respect to E is greater than H2’s explanatory power with respect to E. We argue that any measure satisfying this condition faces three serious problems—the Problem of Temporal Shallowness, the Problem of Negative Causal Interactions, and the Problem of Nonexplanations. We further argue that many such measures face a fourth problem—the Problem of Explanatory Irrelevance.

The requirement of total evidence is a mainstay of Bayesian epistemology. Peter Fisher Epstein argues that the requirement generates mistaken conclusions about several examples that he devises. Here we examine the example of Epstein’s that we find most interesting and argue that Epstein’s analysis of it is flawed.

According to Michael Friedman’s theory of explanation, a law X explains laws Y1, Y2, …, Yn precisely when X unifies the Y’s, where unification is understood in terms of reducing the number of independently acceptable laws. Philip Kitcher criticized Friedman’s theory but did not analyze the concept of independent acceptability. Here we show that Kitcher’s objection can be met by modifying an element in Friedman’s account. In addition, we argue that there are serious objections to the use that Friedman makes of the concept of independent acceptability.

In their book What Darwin Got Wrong, Jerry Fodor and Massimo Piattelli-Palmarini construct an a priori philosophical argument and an empirical biological argument. The biological argument aims to show that natural selection is much less important in the evolutionary process than many biologists maintain. The a priori argument begins with the claim that there cannot be selection for one but not the other of two traits that are perfectly correlated in a population; it concludes that there cannot be an evolutionary theory of adaptation. This article focuses mainly on the a priori argument.

Akaike's framework for thinking about model selection in terms of the goal of predictive accuracy and his criterion for model selection have important philosophical implications. Scientists often test models whose truth values they already know, and they often decline to reject models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike's framework helps provide instrumentalism with the epistemology it needs. Akaike's criterion for model selection also throws light on the role of parsimony considerations in hypothesis evaluation. I explain the basic ideas behind Akaike's framework and criterion; several biological examples, including the use of maximum likelihood methods in phylogenetic inference, are considered.

Reductionism is often understood to include two theses: (1) every singular occurrence that the special sciences can explain also can be explained by physics; (2) every law in a higher-level science can be explained by physics. These claims are widely supposed to have been refuted by the multiple realizability argument, formulated by Putnam (1967, 1975) and Fodor (1968, 1975). The present paper criticizes the argument and identifies a reductionistic thesis that follows from one of the argument's premises.

Critique de l'ouvrage de W. A. Dembsky intitule «L'inference du dessein» (198) qui examine les contextes non-theologiques de l'argument philosophique du dessein. L'A. rejette la methode epistemologique de Dembsky, fondee sur la hasard et la probabilite, qui ne rend pas compte de la these creationniste ni de la theorie evolutionniste de l'univers.

John Beatty (1995) and Alexander Rosenberg (1994) have argued against the claim that there are laws in biology. Beatty's main reason is that evolution is a process full of contingency, but he also takes the existence of relative significance controversies in biology and the popularity of pluralistic approaches to a variety of evolutionary questions to be evidence for biology's lawlessness. Rosenberg's main argument appeals to the idea that biological properties supervene on large numbers of physical properties, but he also develops case studies of biological controversies to defend his thesis that biology is best understood as an instrumental discipline. The present paper assesses their arguments.

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.

The evolutionary problem of the units of selection has elicited a good deal of conceptual work from philosophers. We review this work to determine where the issues now stand.

Brandon ([1982] 1984, 1990) has argued that Salmon's (1971) concept of screening-off can be used to characterize (i) the idea that natural selection acts directly on an organism's phenotype, only indirectly on its genotype, and (ii) the biological problem of the levels of selection. Brandon also suggests (iii) that screening-off events in a causal chain are better explanations than the events they screen off. This paper critically evaluates Brandon's proposals.

A model of a Markov process is presented in which observing the present state of a system is asymmetrically related to inferring the system's future and inferring its past. A likelihood inference about the system's past state, based on observing its present state, is justified no matter what the parameter values in the model happen to be. In contrast, a probability inference of the system's future state, based on observing its present state, requires further information about the parameter values.

Several evolutionary biologists have used a parsimony argument to argue that the single gene is the unit of selection. Since all evolution by natural selection can be represented in terms of selection coefficients attaching to single genes, it is, they say, “more parsimonious” to think that all selection is selection for or against single genes. We examine the limitations of this genic point of view, and then relate our criticisms to a broader view of the role of causal concepts and the dangers of reification in science.

A common view among statisticians is that convergence (which statisticians call consistency) is a necessary property of an inference rule or estimator. In this paper, this view is challenged by appeal to an example in which a rule of inference has a likelihood rationale but is not convergent. The example helps clarify the significance of the likelihood concept in statistical inference.

Ernst Mayr has argued that Darwinian theory discredited essentialist modes of thought and replaced them with what he has called “population thinking”. In this paper, I characterize essentialism as embodying a certain conception of how variation in nature is to be explained, and show how this conception was undermined by evolutionary theory. The Darwinian doctrine of evolutionary gradualism makes it impossible to say exactly where one species ends and another begins; such line-drawing problems are often taken to be the decisive reason for thinking that essentialism is untenable. However, according to the view of essentialism I suggest, this familiar objection is not fatal to essentialism. It is rather the essentialist's use of what I call thenatural state modelfor explaining variation which clashes with evolutionary theory. This model implemented the essentialist's requirement that properties of populations be defined in terms of properties of member organisms. Requiring suchconstituent definitionsis reductionistic in spirit; additionally, evolutionary theory shows that such definitions are not available, and, moreover, that they are not needed to legitimize population-level concepts. Population thinking involves the thesis that population concepts may be legitimized by showing their connections witheach other, even when they are not reducible to concepts applying at lower levels of organization. In the paper, I develop these points by describing Aristotle's ideas on the origins of biological variation; they are a classic formulation of the natural state model. I also describe how the development of statistical ideas in the 19th century involved an abandoning of the natural state model.

Russell (1948), Reichenbach (1956), and Salmon (1975, 1979) have argued that a fundamental principle of science and common sense is that “matching” events should not be chalked up to coincidence, but should be explained by postulating a common cause. Reichenbach and Salmon provided this intuitive idea with a probabilistic formulation, which Salmon used to argue for a version of scientific realism. Van Fraassen (1980, 1982) showed that the principle, so construed, runs afoul of certain results in quantum mechanics. In this paper a new formulation of the principle is offered that emerges from its use in evolutionary theory. This characterization identifies fairly general conditions in which postulating common causes will be more explanatory than postulating separate causes.

To infer the state of a cause from the states of its effects, independent lines of evidence are preferable to dependent ones. This familiar idea is here investigated, the goal being to identify its presuppositions. Connections are drawn with Reichenbach's (1956) and Salmon's (1984) discussions of the principle of the common cause.

After clarifying the probabilistic conception of causality suggested by Good (1961–2), Suppes (1970), Cartwright (1979), and Skyrms (1980), we prove a sufficient condition for transitivity of causal chains. The bearing of these considerations on the units of selection problem in evolutionary theory and on the Newcomb paradox in decision theory is then discussed.

In a recent article (Sober 1982), I criticized an account of causation proposed by Giere (1979, 1980) by describing a series of examples concerning natural selection. Collier (1983) has criticized my criticisms, saying that I misapplied Giere's proposal and misconstrued the biology. More recently, Giere (1984) has defended his theory against my criticisms. Here I argue that my criticisms still stand.

The likelihood justification of cladistic parsimony suggested in Sober (1984) is here shown to be incomplete. Even so, cladistic parsimony remains a counterexample to the principle of the common cause formulated by Reichenbach (1956) and Salmon (1975, 1979, 1984).

One of us (Eells 1982) has defended traditional evidential decision theory against prima facie Newcomb counterexamples by assuming that a common cause forms a conjunctive fork with its joint effects. In this paper, the evidential theory is defended without this assumption. The suggested rationale shows that the theory's assumptions are not about the nature of causality, but about the nature of rational deliberation. These presuppositions are weak enough for the argument to count as a strong justification of the evidential theory.

Rosenberg (1983), in his comments on our article (Sober and Lewontin 1982) concerning the units of selection controversy, has matters precisely backwards. He chides us for conflating a causal theory with a mathematical model, whereas this is precisely the error we argued is at the core of the position defended by Williams (1966) and Dawkins (1976). Their idea—genic selectionism—confuses the computational adequacy of a mathematical model with a substantive causal theory. The main point of our paper was simply this: the fact that evolution by natural selection can be “represented” in terms of selection coefficients that attach to single genes does not imply that selection is always selection for or against the possession of those single genes.