Michael Bishop

Scientific realism says of our best scientific theories that (1) most of their important posits exist and (2) most of their central claims are approximately true. Antirealists sometimes offer the pessimistic induction in reply: since (1) and (2) are false about past successful theories, they are probably false about our own best theories too. The contemporary debate about this argument has turned (and become stuck) on the question, Do the central terms of successful scientific theories refer? For example, Larry Laudan offers a list of successful theories that employed central terms that failed to refer, and Philip Kitcher replies with a view about reference in which the central terms of such theories did sometimes refer. This article attempts to break this stalemate by proposing a direct version of the pessimistic induction, one that makes no explicit appeal to a substantive notion or theory of reference. While it is premature to say that this argument succeeds in showing that realism is probably false, the direct pessimistic induction is not subject to any kind of reference-based objection that might cripple a weaker, indirect version of the argument. Any attempt to trounce the direct pessimistic induction with a theory of reference fails.

Standard Analytic Epistemology (SAE) names a contingently clustered class of methods and theses that have dominated English-speaking epistemology for about the past half-century. The major contemporary theories of SAE include versions of foundationalism, coherentism, reliabilism, and contextualism. While proponents of SAE don’t agree about how to define naturalized epistemology, most agree that a thoroughgoing naturalism in epistemology can’t work. For the purposes of this paper, we will suppose that a naturalistic theory of epistemology takes as its core, as its starting-point, an empirical theory. The standard argument against naturalistic approaches to epistemology is that empirical theories are essentially descriptive, while epistemology is essentially prescriptive, and a descriptive theory cannot yield normative, evaluative prescriptions. In short, naturalistic theories cannot overcome the is-ought divide. Our main goal in this paper is to show that the standard argument against naturalized epistemology has it almost exactly backwards.

A heuristic is a rule of thumb. In psychology, heuristics are relatively simple rules for making judgments. A fast heuristic is easy to use and allows one to make judgments quickly. A frugal heuristic relies on a small fraction of the available evidence in making judgments. Typically, fast and frugal heuristics (FFHs) have, or are claimed to have, a further property: They are very reliable, yielding judgments that are about as accurate in the long run as ideal non-fast, non-frugal rules. This paper introduces some well-known examples of FFHs, raises some objections to the FFH program, and looks at the implications of those parts of the FFH program about which we can have some reasonable degree of confidence.

There are simple rules for making important judgments that are more reliable than experts, but people refuse to use them People refuse even when they are told that these rules are more reliable than they are. When we say that people “refuse” to use the rule, we do not mean that people stubbornly refuse to carry out the steps indicated by the rule. Rather, people defect from the rule (i.e., they overturn the rule’s judgment) so often that they end up reasoning about as reliably as they would have without the rule, and less reliably than the rule all by itself. We haue two aims in this paper. First, we will explain why (at least some) simple rules are so reliable and why people too often defect from them. And second, we will argue that this selective defection phenomenon raises a serious problem for all epistemological theories of justification. We will suggest that the best way to escape this problem is to change the focus of contemporary epistemology.

Strategic Reliabilism is a framework that yields relative epistemic evaluations of belief-producing cognitive processes. It is a theory of cognitive excellence, or more colloquially, a theory of reasoning excellence (where 'reasoning' is understood very broadly as any sort of cognitive process for coming to judgments or beliefs). First introduced in our book, Epistemology and the Psychology of Human Judgment (henceforth EPHJ), the basic idea behind SR is that epistemically excellent reasoning is efficient reasoning that leads in a robustly reliable fashion to significant, true beliefs. It differs from most contemporary epistemological theories in two ways. First, it is not a theory of justification or knowledge – a theory of epistemically worthy belief. Strategic Reliabilism is a theory of epistemically worthy ways of forming beliefs. And second, Strategic Reliabilism does not attempt to account for an epistemological property that is assumed to be faithfully reflected in the epistemic judgments and intuitions of philosophers. If SR makes recommendations that accord with our reflective epistemic judgments and intuitions, great. If not, then so much the worse for our reflective epistemic judgments and intuitions.

The generality problem is widely considered to be a devastating objection to reliabilist theories of justification. My goal in this paper is to argue that a version of the generality problem applies to all plausible theories of justification. Assume that any plausible theory must allow for the possibility of reflective justification—S's belief, B, is justified on the basis of S's knowledge that she arrived at B as a result of a highly (but not perfectly) reliable way of reasoning, R. The generality problem applies to all cases of reflective justification: Given that is the product of a process-token that is an instance of indefinitely many belief-forming process-types (or BFPTs), why is the reliability of R, rather than the reliability of one of the indefinitely many other BFPTs, relevant to B's justificatory status? This form of the generality problem is restricted because it applies only to cases of reflective justification. But unless it is solved, the generality problem haunts all plausible theories of justification, not just reliabilist ones.

By making plausible the Diversity Thesis (different people have systematically different and incompatible packages of epistemic intuitions), experimental epistemology raises the specter of the shifting-sands problem: the evidence base for epistemology contains systematic inconsistencies. In response to this problem, some philosophers deny the Diversity Thesis, while others flirt with denying the Evidence Thesis (in normal circumstances, the epistemic intuition that p is prima facie evidence that p is true). We propose to accept both theses. The trick to living with the shifting-sands problem is to expand epistemology’s evidential base so as to include scientific evidence. This evidence can provide principled grounds on which to decide between incompatible intuitions. The idea of resolving inconsistencies in an evidential base by adding more independent lines of evidence is commonplace in science. And in philosophy, it is simplyWide Reflective Equilibrium.We contend that the idea that epistemology would depend crucially on scientific evidence seems radical because many traditional epistemologists practice reflective equilibrium that is WINO, Wide In Name Only. We suggest five different lines of scientific evidence that can be, and have been, used in support of non-WINO epistemological theories.

Bishop and Trout here present a unique and provocative new approach to epistemology (the theory of human knowledge and reasoning). Their approach aims to liberate epistemology from the scholastic debates of standard analytic epistemology, and treat it as a branch of the philosophy of science. The approach is novel in its use of cost-benefit analysis to guide people facing real reasoning problems and in its framework for resolving normative disputes in psychology. Based on empirical data, Bishop and Trout show how people can improve their reasoning by relying on Statistical Prediction Rules (SPRs). They then develop and articulate the positive core of the book. Their view, Strategic Reliabilism, claims that epistemic excellence consists in the efficient allocation of cognitive resources to reliable reasoning strategies, applied to significant problems. The last third of the book develops the implications of this view for standard analytic epistemology; for resolving normative disputes in psychology; and for offering practical, concrete advice on how this theory can improve real people's reasoning. This is a truly distinctive and controversial work that spans many disciplines and will speak to an unusually diverse group, including people in epistemology, philosophy of science, decision theory, cognitive and clinical psychology, and ethics and public policy.