Elliott Sober

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

What thesis is Hume trying to establish in his essay “On Miracles” and does he succeed? John Earman’s answer to the latter question is clearly conveyed by the title of his new book. Earman uses a Bayesian representation of the problem to make his case. For Earman, this mode of analysis is both perspicuous and nonanachronistic, in that probability reasoning was central to the 18th century debate about miracles in particular and testimony in general. Indeed, one of Hume’s most interesting antagonists, Richard Price, was the person to whom Thomas Bayes entrusted his now-famous essay for posthumous publication. For Earman, Price is the proper Bayesian, while Hume’s essay provides only “rhetoric and schein geld”. Earman’s tone is consistently prosecutorial and sometimes snide; he says that his animus is not so much against Hume himself as against those who smugly invoke Hume’s essay as definitively settling the matter. This tone should not deter potential readers who are convinced that Hume’s essay contains something of value. Earman’s book is interesting and provocative in multiple ways—it places Hume’s essay in its historical setting, it offers an insightful close reading of the text, and it shows how the resources of Bayesianism can be powerfully put to work. Besides Earman’s own essay, the volume also contains Hume’s essay and relevant work by others, including Locke, Spinoza, Samuel Clarke, Price, Laplace, and Babbage. The book would be an excellent choice for an advanced undergraduate or graduate seminar.

The examples and concepts that Shoemaker cites are rather heterogeneous. Some distinctions need to be drawn. An optimality thesis involves not just an ordering of options, but a value judgment about them. So let us begin by distinguishing minimality from optimality. And the concept of minimality can play a variety of roles, among which I distinguish between extremum descriptions, statements hypothesizing an optimizing process, and methodological recommendations. Finally, I consider how the three categories relate to Shoemaker’s question that “Who is optimizing: the scientist or nature?”

In our essay ‘What’s Historical About Historical Materialism?’, we drew two contrasts between the Darwinian theory of evolution (ET) and the Marxist theory of historical materialism (HM).1 We described the former as a ‘micro-theory’ and the latter as a ‘macro-theory’. We also argued that, in Darwinian theory, evolution is driven by exogenous forces, specifically, by natural selection induced by environmental factors; whereas historical materialism sees the transformation of a society from feudalism to capitalism and then to socialism as a consequence of an endogenous process, involving ‘contradictions’ between forces and relations of production and class struggle. Nolan has taken issue with both of these contrasts; his view is that the two theories are more similar than our account allows.

Philosophy of mind is, and for a long while has been, 99% metaphysics and 1% epistemology. But the fundamental question cognitive ethologists face is epistemological: what count as evidence that a creature has a mind, and if the creature does have a mind, what evidence is relevant to deciding which mental state should be attributed to it? The usual answer that cognitive ethologists give is that one’s explanation should be “conservative”. It recommends a two-part plausibility ordering: mindless is preferred to minded, and first-order intentionality is preferred to second-order intentionality. I argue that the principle of conservatism is not a parsimony principle, and it doesn’t have any justification. What is needed is observational test. I also suggest a strategy for designing experiments in the future. What I offered here is a methodological version of naturalism.

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

It is a challenge to explain how evolutionary altruism can evolve by the process of natural selection, since altruists in a group will be less fit than the selfish individuals in the same group who receive benefits but do not make donations of their own. Darwin proposed a theory of group selection to solve this puzzle. Very simply, even though altruists are less fit than selfish individuals within any single group, groups of altruists are more fit than groups of selfish individuals. If a population is subdivided into many groups that vary in their altruistic tendencies, altruism will be favored at the level of selection among groups even as it is being disfavored at the level of selection among individuals within groups. Darwin’s scenario became the basis for a theoretical framework called multilevel selection theory.

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.

A phylogeny that allows for lateral gene transfer (LGT) can be thought of as a strictly branching tree (all of whose branches are vertical) to which lateral branches have been added. Given that the goal of phylogenetics is to depict evolutionary history, we should look for the best supported phylogenetic network and not restrict ourselves to considering trees. However, the obvious extensions of popular tree-based methods such as maximum parsimony and maximum likelihood face a serious problem—if we judge networks by fit to data alone, networks that have lateral branches will always fit the data at least as well as any network that restricts itself to vertical branches. This is analogous to the well-studied problem of overfitting data in the curve-fitting problem. Analogous problems often have analogous solutions and we propose to treat network inference as a case of model selection and use the Akaike Information Criterion (AIC). Strictly tree-like networks are more parsimonious than those that postulate lateral as well as vertical branches. This leads to the conclusion that we should not always infer LGT events whenever it would improve our fit-to-data, but should do so only when the improved fit is larger than the penalty for adding extra lateral branches.

The hypothesis of group selection fell victim to a seemingly devastating critique in 1960s evolutionary biology. In Unto Others (1998), we argue to the contrary, that group selection is a conceptually coherent and empirically well documented cause of evolution. We suggest, in addition, that it has been especially important in human evolution. In the second part of Unto Others, we consider the issue of psychological egoism and altruism -- do human beings have ultimate motives concerning the well-being of others? We argue that previous psychological and philosophical work on this question has been inconclusive. We propose an evolutionary argument for the claim that human beings have altruistic ultimate motives.

Historical sciences like evolutionary biology reconstruct past events by using the traces that the past has bequeathed to the present. Markov chain theory entails that the passage of time reduces the amount of information that the present provides about the past. Here we use a Moran process framework to show that some evolutionary processes destroy information faster than others. Our results connect with Darwin’s principle that adaptive similarities provide scant evidence of common ancestry whereas neutral and deleterious similarities do better. We also describe how the branching in phylogenetic trees affects the information that the present supplies about the past

Developing a definition of group selection, and applying that definition to the dispute in the social sciences between methodological holists and methodological individualists, are the two goals of this paper. The definition proposed distinguishes between changes in groups that are due to group selection and changes in groups that are artefacts of selection processes occurring at lower levels of organization. It also explains why the existence of group selection is not implied by the mere fact that fitness values of organisms are sensitive to the composition of groups. And, lastly, the definition explains why group selection need not involve selection for altruism. Group selection is thereby seen as an evolutionary force which is objectively distinct from other evolutionary forces. Applying the distinction between group and individual selection to the holism/individualism dispute has the desirable result that the dispute is not decidable a priori. This way of looking at the dispute yields a conception of individualism which is untainted by atomism and a conception of holism which is unspoiled by hypostatis.

Parsimony arguments are advanced in both science and philosophy. How are they related? This question is a test case for Naturalismp, which is the thesis that philosophical theories and scientific theories should be evaluated by the same criteria. In this paper, I describe the justifications that attach to two types of parsimony argument in science. In the first, parsimony is a surrogate for likelihood. In the second, parsimony is relevant to estimating how accurately a model will predict new data when fitted to old. I then consider how these two justifications apply to parsimony arguments in philosophy concerning theism and atheism, the mind/body problem, ethical realism, the question of whether mental properties are causally efficacious, and nominalism versus Platonism about numbers

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

Reconstructing the Past seeks to clarify and help resolve the vexing methodological issues that arise when biologists try to answer such questions as whether human beings are more closely related to chimps than they are to gorillas. It explores the case for considering the philosophical idea of simplicity/parsimony as a useful principle for evaluating taxonomic theories of evolutionary relationships. For the past two decades, evolutionists have been vigorously debating the appropriate methods that should be used in systematics, the field that aims at reconstructing phylogenetic relationships among species. This debate over phylogenetic inference, Elliott Sober observes, raises broader questions of hypothesis testing and theory evaluation that run head on into long standing issues concerning simplicity/parsimony in the philosophy of science. Sober treats the problem of phylogenetic inference as a detailed case study in which the philosophical idea of simplicity/parsimony can be tested as a principle of theory evaluation. Bringing together philosophy and biology, as well as statistics, Sober builds a general framework for understanding the circumstances in which parsimony makes sense as a tool of phylogenetic inference. Along the way he provides a detailed critique of parsimony in the biological literature, exploring the strengths and limitations of both statistical and nonstatistical cladistic arguments.

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.

The problem of simplicity involves three questions: How is the simplicity of a hypothesis to be measured? How is the use of simplicity as a guide to hypothesis choice to be justified? And how is simplicity related to other desirable features of hypotheses -- that is, how is simplicity to be traded-off? The present paper explores these three questions, from a variety of viewpoints, including Bayesianism, likelihoodism, and the framework of predictive accuracy formulated by Akaike (1973). It may turn out that simplicity has no global justification -- that its justification varies from problem to problem.

We address the following issues raised by the commentators of our target article and book: (1) the problem of multiple perspectives; (2) how to define group selection; (3) distinguishing between the concepts of altruism and organism; (4) genetic versus cultural group selection; (5) the dark side of group selection; (6) the relationship between psychological and evolutionary altruism; (7) the question of whether the psychological questions can be answered; (8) psychological experiments. We thank the contributors for their commentaries, which provide a diverse agenda for future study of evolution and morality. Our response will follow the organization of our book, distinguishing between evolutionary issues that concern fitness effects and psychological issues that concern motives.

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.

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’.

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