Elliott Sober

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.

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.

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.

Evidence and Evolution has four chapters: (1) Evidence, (2) Intelligent Design, (3) Natural Selection, and (4) Common Ancestry. The first chapter develops tools that are used in the rest of the book, though more ideas about evidence are added. In Chapter 1, I endorse a pluralistic outlook—Bayesianism is fine in some inference problems, likelihoodism in others, and AIC in still others. In Chapter Two, on intelligent design, I try to develop the strongest possible formulation of the design argument for the existence of God, after which I criticize the argument so conceived. This second chapter also attempts to resuscitate the concept of testability. Chapter 3, on natural selection, discusses how to evaluate competing hypotheses on evolution mechanisms and evaluate the use of the principle of common cause, molecular data, and cladistic parsimony. Chapter 4 is on common ancestry: what it means to say that all life on earth has a common ancestor, and s. Why should the similarity of two species be evidence that they have a common ancestor? The chapter concludes with a discussion of how biologists use cladistic parsimony to infer phylogenetic trees and compare it with explicit statistical approaches.

My critical remarks' on Alexander Rosenberg’s article on fitness have elicited a rejoinder from Mary Williams and Rosenberg himself. They charge that my criticisms are a “tissue of misunderstandings” (738); since they misunderstand my own position in fundamental ways, it may help to try to clarify the points that divide us. In the interest of brevity, I will ignore technical issues concerning the internal correctness of Williams’s axiomatization and will focus on questions of broader philosophical interest.

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.

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 philosophers have argued recently that semantic properties do play a causal role. 1 It is our view that none of these arguments are satisfactory. Our aim is to reveal some of the deficiencies of these arguments, and to reassess the question in our own way. In section 1, we shall explain in more detail what is involved in the pretheoretical idea of a causally efficacious property and so provide a fuller sense of the issue. In section 2 we shall discuss Fodor's and Kim's arguments that the semantic properties of mental events are causally efficacious. Their tactic is to articulate sufficient conditions for the causal efficacy of a property, and then apply these conditions to the psychological properties under consideration. We shall show that both formulations are inadequate. However, each account can remedy some of the defects of the other. We shall argue that by putting the two together, and modifying this combined account in certain ways, we can arrive at something that might just pass as a general sufficient condition for causal efficacy. We believe that the question of causal efficacy of content is best approached as a question in the philosophy of science. If one wants to know whether a given species of property is efficacious, the most productive strategy is to find a science that investigates the properties and examine the role they are assigned. In keeping with this attitude we shall restrict our discussion to the notion of content deployed within cognitive science. In section 3 we examine the role of content in cognitive science and discuss whether this role suits content to the conditions on efficacy articulated in section two. Our conclusion will be conditional and hedged: on certain views of cognitive science, content will meet the sufficient condition for efficacy. If other views are correct, the question remains open.

I want to explore what happens to two philosophical issues when we assume that the mind, a functional device, is to be understood by the same sort of functional analysis that guides biological investigation of other organismic systems and characteristics. The first problem area concerns the concept of rationality, its connection with reliability and reproductive success, and the status of rationality hypotheses in attribution of beliefs. It has been argued that ascribing beliefs to someone requires the assumption that that person is rational. It also has been argued that evolutionary theory can account for the capacity we have for rational thought by appealing to the idea that rational methods for constructing beliefs are reliable and therefore represented a selected advantage. Both of these claims about rationality are critically examined. In the second part of the paper, I turn to some criticisms that have been advanced against "functionalist" solutions to the mind/body problem. These criticisms are defused when that doctrine is understood in terms of a Teleological (rather than a Turing Machine) notion of function. However, functionalism does not emerge totally unscathed. Voltaire's Dr. Pangloss saw everything in terms of its function and its perfect performance of its function. In the philosophy of mind, his influence lives on in the form of two ideas: (i) that we must possess rational methods for constructing beliefs, since our minds are the product of natural selection, and (ii) that psychological states and properties are individuated by their psychological functions. Contemporary biology provides the resources for avoiding Pangloss's wideeyed teleology in the study of adaptation. It is to be hoped that progress in psychology will loosen the grip of Panglossian assumptions in the study of mind.

These essays by leading scientists and philosophers address conceptual issues that arise in the theory and practice of evolutionary biology. The third edition of this widely used anthology has been substantially revised and updated. Four new sections have been added: on women in the evolutionary process, evolutionary psychology, laws in evolutionary theory, and race as social construction or biological reality. Other sections treat fitness, units of selection, adaptationism, reductionism, essentialism, species, phylogenetic inference, cultural evolution, and evolutionary ethics. Each of the twelve sections contains two or three essays that develop different views of the subject at hand. For example, the section on evolutionary psychology offers one essay by two founders of the field and another that questions its main tenets. One sign that a discipline is growing is that there are open questions, with multiple answers still in competition; the essays in this volume demonstrate that evolutionary biology and the philosophy of evolutionary biology are living, growing disciplines.

How could the fundamental mental operations which facilitate scientific theorizing be the product of natural selection, since it appears that such theoretical methods were neither used nor useful "in the cave"-i.e., in the sequence of environments in which selection took place? And if these wired-in information processing techniques were not selected for, how can we view rationality as an adaptation? It will be the purpose of this paper to address such questions as these, and in the process to sketch some of the considerations that an evolutionary account of rationality may involve. By describing the broad framework within which the evolution of rationality may eventually be understood, I hope to undermine the idea that evolutionary theory is somehow incapable of dealing with this characteristic and requires supplementation by some novel principle. A more modest ambition of the paper is to try to provoke those who think that there are special problems involved in this evolutionary inquiry to say what these problems are.

Alexander Rosenberg began his recent article on the concept of fitness with the remark that “debates about the cognitive status of the Darwinian theory of natural selection should have ended long ago.” I agree that this obsession need to be overcome. But Rosenberg repeats some of the old mistakes and invents epicycles on others. In this comment I will not be able to circumscribe fully the range of the topics that an adequate treatment of this cluster of problems demands. A few critical comments will indicate what I find wanting in Rosenberg’s treatment.

Altruism has both an evolutionary and a psychological meaning. As the term is used in evolutionary theory, a trait is deemed altruistic if it reduces the fitness of the actor and enhances the fitness of someone else. In its psychological sense, the thesis that we have altruistic ultimate motives asserts that we care about the welfare of others, not just as a means of enhancing our own well-being, but as an end in itself. In Unto Others (hereafter UO), we consider both evolutionary altruism (Part I) and psychological altruism (Part II) from an evolutionary perspective. We propose a multilevel selection theory to explain how altruism can evolve from group selection, based on Darwin’s solution to the problem. Our presentation of multilevel selection theory expands the range of topics beyond altruism in other respects as well. In Part I1 of UO, we evaluate the arguments, both conceptual and empirical, that philosophers and psychologists have advanced in an attempt to choose between psychological egoism and motivational pluralism. We conclude that these arguments are inconclusive.

Suppose that several observations “coincide,” meaning that they are similar in some interesting respect. Is this coinciding a mere coincidence, or does it derive from a common cause? Those who reason about this kind of question—whether they embrace the first answer or the second—often deploy a mode of inference that I call probabilistic modus tollens. In this chapter I criticize probabilistic modus tollens and consider likelihood and Bayesian frameworks for reasoning about coincidences. I also consider the perspective offered by model selection theory (including the Akaike information criterion), and argue that model selection often provides important insights.