Elliott Sober

The propensity interpretation of fitness draws on the propensity interpretation of probability, but advocates of the former have not attended sufficiently to problems with the latter. The causal power of C to bring about E is not well-represented by the conditional probability Pr. Since the viability fitness of trait T is the conditional probability Pr, the viability fitness of the trait does not represent the degree to which having the trait causally promotes surviving. The same point holds for fertility fitness. This failure of trait fitness to capture causal role can also be seen in the fact that coextensive traits must have the same fitness values even if one of them promotes survival and the other is neutral or deleterious. Although the fitness of a trait does not represent the trait’s causal power to promote survival and reproduction, variation in fitness in a population causally promotes change in trait frequencies; in this sense, fitness variation is a population-level propensity

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.

Presented in an engaging lecture-style format, this anthology leads readers through a series of discussions on the basic issues and ideas in philosophy, with lectures supported by related readings from historically important sources. The discussions emphasize the logic of philosophical arguments—and in particular, how they relate to the content of scientific theories such as evolution. This five-part book, made up of “lectures” and readings, covers an introduction to philosophy; the philosophy of religion; theory of knowledge; philosophy of mind; and ethics. For anyone looking for adequate answers to enduring questions.

The design argument for the existence of God took a probabilistic turn in the 17 th and 18 th centuries. Earlier versions, such as Thomas Aquinas' 5 th way, usually embraced the premise that goal-directed systems (things that "act for an end" or have a function) must have been created by an intelligent designer. This idea – which we might express by the slogan "no design without a designer" – survived into the 17 th and 18 th centuries, 1 and it is with us still in the writings of many creationists. The new version of the argument, inspired by the emerging mathematical theory of probability, removed the premise of necessity. It begins with the thought that goal-directed systems might have arisen by intelligent design or by chance; the problem is to discern which hypothesis is more plausible. With the epistemic concept of plausibility characterized in terms of the mathematical concept of probability, the design argument was given a new direction. The new probabilistic perspective did not extinguish the older idea of "no design without a designer." The two conflicting approaches coexisted, often with less than perfect clarity about their fundamental difference. At the same time, the details of how the probabilistic perspective ought to be articulated were slow in emerging. These characteristics of uneven development are exemplified in a debate that took place in the 18 th century among three probabilists – John Arbuthnot, Nicholas Bernoulli, and Abraham DeMoivre – on the proper explanation of human sex ratio. Arbuthnot proposed a probabilistic version of the design argument, claiming that it is intelligent design, not chance, that provides the better explanation of why slightly more boys than girls are born each year. Bernoulli rejected Arbuthnot's argument. DeMoivre defended Arbuthnot against Bernoulli's criticisms. The problem of explaining sex ratio, both in human populations and in the rest of nature, experienced another transformation after 1859 --it became a problem for the theory of evolution by natural selection. Darwin (1871) addressed the question in the first edition of The Descent of Man but withdrew his suggestion in the second (Darwin 1874). Carl Düsing (1884) provided a mathematical model that moved beyond the explanation Darwin offered. Fisher (1930) added the new idea of parental expenditure. Williams (1966) argued that the sex ratios found in nature provide the opportunity to test hypotheses of group selection against hypotheses of individual selection. Hamilton (1967) constructed a model that generalizes Fisher's approach and represents the effects of both group and individual selection. The theory of natural selection gradually developed the ability to predict sex ratios, not just explain them post hoc.

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.

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.

Only one traditional objection to Pascal's wager is telling: Pascal assumes a particular theology, but without justification. We produce two new objections that go deeper. We show that even if Pascal's theology is assumed to be probable, Pascal's argument does not go through. In addition, we describe a wager that Pascal never considered, which leads away from Pascal's conclusion. We then consider the impact of these considerations on other prudential arguments concerning what one should believe, and on the more general question of when and why belief formation ought to be based solely on the evidence.

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.

Realism and empiricism have always been contradictory tendencies in the philosophy of science. The view I will sketch is a synthesis, which I call Contrastive Empiricism. Realism and empiricism are incompatible, so a synthesis that merely conjoined them would be a contradiction. Rather, I propose to isolate important elements in each and show that they combine harmoniously. I will leave behind what I regard as confusions and excesses. The result, I hope, will be neither contradiction nor mishmash.

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.

Carl Hempel1 set the tone for subsequent philosophical work on scientific explanation by resolutely locating the problem he wanted to address outside of epistemology. “Hempel’s problem,” as I will call it, was not to say what counts as evidence that X is the explanation of Y. Rather, the question was what it means for X to explain Y. Hempel’s theory of explanation and its successors don’t tell you what to believe; instead, they tell you which of your beliefs (if any) can be said to explain a given target proposition.

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.

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.

“Absence of evidence isn’t evidence of absence” is a slogan that is popular among scientists and nonscientists alike. This article assesses its truth by using a probabilistic tool, the Law of Likelihood. Qualitative questions (“Is E evidence about H ?”) and quantitative questions (“How much evidence does E provide about H ?”) are both considered. The article discusses the example of fossil intermediates. If finding a fossil that is phenotypically intermediate between two extant species provides evidence that those species have a common ancestor, does failing to find such a fossil constitute evidence that there was no common ancestor? Or should the failure merely be chalked up to the imperfection of the fossil record? The transitivity of the evidence relation in simple causal chains provides a broader context, which leads to discussion of the fine-tuning argument, the anthropic principle, and observation selection effects.