Elliott Sober

We learned from Good that there is no saying whether a black raven confirms the generalization that all ravens are black unless one is prepared to make substantive background assumptions. The same point, applied to the problem of other minds, is that the mere observation that Self and Other share certain behaviors and that Self has a mind is not enough. The problem of other minds turns into the problem of searching out common causes. This paper presents a probabilistic representation of the problem of other minds, and shows that the likelihood concept provides a framework for understanding the Self and Other problem.

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. Although the points I’ll make are rather elementary ones, their interest is not restricted to those who have never heard of the evolutionary problem. The reason for this is that there is some amount of confusion about evolutionary altruism among evolutionary biologists themselves.

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.

The positivists suggest that some truths may be immune from empirical refutation and yet lacking in rational justification. Quine holds that every proposition is in principle empirically refutable so there are no a priori truths. I’ll provide a working characterization of the idea of “rational revisability” and argue it’s impossible for us to take a chain of rational revision and end up revising everything which we now believe. Quine's position on revisability is also in tension with certain theses about epistemic holism. Finally, I discuss a more general context in which rational argument is viewed as one mechanism among many for reliably modifying beliefs. This more biological perspective allows us to formulate Quine's claims about revisability in a new way and to raise some interesting questions about the potential impact of natural selection on our cognitive capacities.

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.

Philosophy of mind is, and for a long while has been, 99% metaphysics and 1% epistemology. Attention is lavished on the question of the nature of mind, but questions concerning how we know about minds are discussed much less thoroughly. University courses in philosophy of mind routinely devote a lot of time to dualism, logical behaviourism, the mind/brain identity theory, and functionalism. But what gets said about the kinds of evidence that help one determine what mental states, if any, an individual occupies? Well, Skinner's puritanical disdain for postulating mental states gets raked over the coals, the problem of other minds gets solved by a perfunctory invocation of the principle of inference to the best explanation, and the Turing test gets discussed, mainly in order to emphasize that it can lead to mistaken answers.

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.