This paper looks at an appeal to the authority of biomedical research that has recently been used by empirical economists to motivate and justify their methods. I argue that those who make this appeal mistake the nature of biomedical research. Randomised trials, which are said to have revolutionised biomedical research, are a central methodology, but according to only one paradigm. There is another paradigm at work in biomedical research, the inferentialist paradigm, in which randomised trials play no special role. I (...) outline the inferentialist alternative in broad strokes, apply it to a recent controversy in econometrics and draw some general conclusions concerning econometric methodology. (shrink)

Recently, biologists have argued that data - driven biology fosters a new scientific methodology; namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data - driven studies can be included into the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful (...) generalizations to complement the procedure of prioritization. Overall this paper aims to shed light on the structure of contemporary research in molecular biology. (shrink)

Less discussed than Hume’s skepticism about what grounds there could be for projecting empirical hypotheses is his concern with a skeptical regress that he thought threatened to extinguish any belief when we reflect that our reasoning is not perfect. The root of the problem is the fact that a reflection about our reasoning is itself a piece of reasoning. If each reflection is negative and undermining, does that not give us a diminution of our original belief to nothing? It requires (...) much attention to detail, we argue, to determine whether or not there is a skeptical problem in this neighborhood. Consider that if we subsequently doubt a doubt we had about our reasoning, that would suggest a restoration of some of the force of our original belief. We would then have instead of runaway skepticism an alternating sequence of pieces of skeptical reasoning that cancel each others’ effects on our justification in the original proposition, at least to some degree. We will argue that the outcome of the sequence of reflections Hume is imagining depends on information about a given case that is not known a priori. We conclude this from the fact that under three precise, explanatory, and viable contemporary reconstructions of what this kind of reasoning about reasoning could be like and how it has the potential to affect our original beliefs, a belief-extinguishing regress is not automatic or necessary. (shrink)

A central problem facing a probabilistic approach to the problem of induction is the difficulty of sufficiently constraining prior probabilities so as to yield the conclusion that induction is cogent. The Principle of Indifference, according to which alternatives are equiprobable when one has no grounds for preferring one over another, represents one way of addressing this problem; however, the Principle faces the well-known problem that multiple interpretations of it are possible, leading to incompatible conclusions. I propose a partial solution to (...) the latter problem, drawing on the notion of explanatory priority. The resulting synthesis of Bayesian and inference-to-best-explanation approaches affords a principled defense of prior probability distributions that support induction. (shrink)

This paper places formal learning theory in a broader philosophical context and provides a glimpse of what the philosophy of induction looks like from a learning-theoretic point of view. Formal learning theory is compared with other standard approaches to the philosophy of induction. Thereafter, we present some results and examples indicating its unique character and philosophical interest, with special attention to its unified perspective on inductive uncertainty and uncomputability.

Eliminative reasoning is a method that has been employed in many significant episodes in the history of science. It has also been advocated by some philosophers as an important means for justifying well-established scientific theories. Arguments for how eliminative reasoning is able to do so, however, have generally relied on a too narrow conception of evidence, and have therefore tended to lapse into merely heuristic or pragmatic justifications for their conclusions. This paper shows how a broader conception of evidence not (...) only can supply the needed justification but also illuminates the methodological significance of eliminative reasoning in a variety of contexts. (shrink)

I argue that Bayesians need two distinct notions of probability. We need the usual degree-of-belief notion that is central to the Bayesian account of rational decision. But Bayesians also need a separate notion of probability that represents the degree to which evidence supports hypotheses. Although degree-of-belief is well suited to the theory of rational decision, Bayesians have tried to apply it to the realm of hypothesis confirmation as well. This double duty leads to the problem of old evidence, a problem (...) that, we will see, is much more extensive than usually recognized. I will argue that degree-of-support is distinct from degree-of-belief, that it is not just a kind of counterfactual degree-of-belief, and that it supplements degree-of-belief in a way that resolves the problems of old evidence and provides a richer account of the logic of scientific inference and belief. (shrink)

The paper examines Wesley Salmon’s claim that the primary role of plausibility arguments in the history of science is to impose constraints on the prior probability of hypotheses. A detailed look at Copernicanism and Darwinism and, more briefly, Rutherford’s discovery of the atomic nucleus reveals a further and arguably more important role of plausibility arguments. It resides in the consideration of likelihoods, which state how likely a given hypothesis makes a given piece of evidence. In each case the likelihoods raise (...) the probability of one of the competing hypotheses and diminish the credibility of its rival, and this may happen either on the basis of ‘old’ or ‘new’ evidence.Keywords: Copernicanism; Darwinism; Atom models; Bayesianism; Likelihoods; Probability arguments. (shrink)

Falsificationism has dominated 20th century philosophy of science. It seemed to have eclipsed all forms of inductivism. Yet recent debates have revived a specific form of eliminative inductivism, the basic ideas of which go back to F. Bacon and J.S. Mill. These modern endorsements of eliminative inductivism claim to show that progressive problem solving is possible using induction, rather than falsification as a method of justification. But this common ground between falsificationism and eliminative inductivism has not led to a detailed (...) investigation into the relationship, if any, which may exist between these two methodologies. This paper reviews several versions of eliminative inductivism, establishes a natural relation between eliminative inductivism and falsificationism, which derives from the distinction between models and theories, and carries out this investigation against a case study of the construction of atom models. The result of the investigation is that falsificationism is a form of eliminative inductivism in the limit of certain constraints. (shrink)

In his recent book The Advancement of Science, Philip Kitcher endorses eliminative induction, or the view that confirmation of hypotheses proceeds by the elimination of alternatives. My intention here is to critically examine Kitcher's eliminativist view of confirmation, and his rejection of the widely held Bayesian position, according to which an hypothesis H is confirmed by evidence E just in case the probability of H conditional on E is greater than the simple unconditional probability of H [i.e. p > p]. (...) Here, I will maintain that while there are aspects of the eliminative approach which Bayesianism must incorporate, as has been argued by John Earman, the eliminativism advocated by Kitcher is unsatisfactory. In addition, I will suggest that Kitcher's reasons for rejecting Bayesian confirmation theory are unconvincing and depend on an overly restrictive version of the position and that indeed Bayesianism has resources needed by an eliminativist account of confirmation. (shrink)

Donald Gillies is one of the pioneers in the philosophical analysis of artificial intelligence (AI). In his recent book, Gillies (1996) not only makes a new and rapidly developing field of science accessible to philosophers; he also introduces philosophical topics relevant to researchers in AI and thereby helps establish a dialogue between the two disciplines. His book clearly and convincingly demonstrates the fruitful interplay between AI and philosophy of science.

Eliminative reasoning seems to play an important role in the sciences, but should it be part of our best theory of science? Statistical evidence, prevalent across the sciences, causes problems for eliminative inference, supporting the view that probabilistic theories of confirmation provide a better framework for reasoning about evidence. Here I argue that deductive elimination has an important inferential role to play in science, one that is compatible with probabilistic approaches to evidence. Eliminative inferences help frame testing problems, an essential (...) step that determines the context for evaluating statistical evidence. I illustrate this process with examples from molecular evolutionary biology. (shrink)

Say that an agent is "epistemically humble" if she is less than certain that her opinions will converge to the truth, given an appropriate stream of evidence. Is such humility rationally permissible? According to the orgulity argument : the answer is "yes" but long-run convergence-to-the-truth theorems force Bayesians to answer "no." That argument has no force against Bayesians who reject countable additivity as a requirement of rationality. Such Bayesians are free to count even extreme humility as rationally permissible.

De Finetti is one of the founding fathers of the subjective school of probability. He held that probabilities are subjective, coherent degrees of expectation, and he argued that none of the objective interpretations of probability make sense. While his theory has been influential in science and philosophy, it has encountered various objections. I argue that these objections overlook central aspects of de Finetti’s philosophy of probability and are largely unfounded. I propose a new interpretation of de Finetti’s theory that highlights (...) these aspects and explains how they are an integral part of de Finetti’s instrumentalist philosophy of probability. I conclude by drawing an analogy between misconceptions about de Finetti’s philosophy of probability and common misconceptions about instrumentalism. (shrink)

In der neueren Erkenntnistheorie wird der Bayesianismus immer populärer. In diesem Ansatz werden Überzeugungen mit Glaubensgraden versehen. Dazu möchte ich der Frage nachgehen, ob wir den klassischen Ansatz in der Erkennnistheorie mit seinen kategorischen Überzeugungen komplett durch einen bayesianischen mit einem probabilistischen Überzeugungssystem ersetzen könnten. Um das zu klären, rekonstruiere ich zunächst beide Modelle unserer Überzeugungssysteme und vergleiche sie dann im Hinblick darauf, wie leistungsfähig sie jeweils dafür sind, erkenntnistheoretische Probleme zu lösen und als Grundlage für Entscheidungen zu dienen. Dabei (...) zeigt sich eine gewisse Inkommensurabilität der beiden Ansätze und außerdem erweist sich keine der Konzeptionen als eindeutig überlegen. Deshalb argumentiere ich schließlich für eine bestimmte Hybridkonzeption aus beiden Ansätzen, die die Vorteile beider Konzeptionen vereinen kann. (shrink)