Tight correlations between mental states and brain states have been observed time and again within the ethology of biologically ingrained animal behaviors, the comparative psychology of animal minds, the evolutionary psychology of mental adaptations, the behavioral genetics of inherited mental traits, the developmental psychology of the maturing mind, the psychopharmacology of mind-altering substances, and cognitive neuroscience more generally. They imply that our mental lives are only made possible because of brain activity—that having a functioning brain is a necessary condition for (...) having conscious experiences. This mind-brain dependence thesis yields predictions that have been spectacularly confirmed by the evidence, whereas its antithesis has been massively disconfirmed—at least so long as it is not formulated so vaguely as to yield no specific empirical consequences at all. Dualists are thus forced to make a difficult choice: either retain a belief in personal survival at the expense of ignoring or dismissing the implications of our best evidence, or accept those implications at the expense of acknowledging that the prospects for personal survival are extremely dim. -/- 1. Introduction: A Probabilistic Argument -- 2. Scientific Reasoning I: Mill’s Methods and Modern Epidemiological Principles - 2.1 When Correlation Indicates Causation -- 3. Scientific Reasoning II: Inference to the Best Explanation, Testability, and Predictive Success - 3.1 Parsimony: Tempering Explanations to Minimize False Beliefs - 3.2 Plausibility: Harmonizing Explanations with Background Knowledge - 3.3 Testability and Confirmation: Checking Hypotheses Against the Data - 3.3.1 Confirmation of the Dependence Thesis from Failed Attempts to Falsify It - 3.3.2 Confirmation of the Dependence Thesis from the Falsification of its Rival - 3.4 Scope: Bringing Disparate Facts Together - 3.5 Fertility: Generating New Lines of Research - 3.6 Overview -- 4. Scientific Reasoning III: Bayesian and Information-Theoretic Approaches - 4.1 Bayesian Probability - 4.2 Bayesian Confirmation Theory - 4.3 A Bayesian Approach to the Dependence and Independence Theses - 4.4 The Probabilistic Price of Ad Hoc Accommodation: Simplicity vs. Goodness of Fit - 4.4.1 Simplicity Reflected in the Likelihood - 4.4.2 Simplicity Reflected in the Prior Probability - 4.5 Prediction vs. Accommodation - 4.6 Bayesian Analysis of the Dependence and Independence Theses -- 5. The Dualist’s Dilemma: Reject Science, or Reject Personal Survival? - 5.1 What’s Left for a Soul to Do? -- 6. Conclusion. (shrink)

Models are a principle instrument of modern science. They are built, applied, tested, compared, revised and interpreted in an expansive scientific literature. Throughout this paper, I will argue that models are also a valuable tool for the philosopher of science. In particular, I will discuss how the methodology of Bayesian Networks can elucidate two central problems in the philosophy of science. The first thesis I will explore is the variety-of-evidence thesis, which argues that the more varied the supporting evidence, the (...) greater the degree of confirmation for a given hypothesis. However, when investigated using Bayesian methodology, this thesis turns out not to be sacrosanct. In fact, under certain conditions, a hypothesis receives more confirmation from evidence that is obtained from one rather than more instruments, and from evidence that confirms one rather than more testable consequences of the hypothesis. The second challenge that I will investigate is scientific theory change. This application highlights a different virtue of modeling methodology. In particular, I will argue that Bayesian modeling illustrates how two seemingly unrelated aspects of theory change, namely the (Kuhnian) stability of (normal) science and the ability of anomalies to over turn that stability and lead to theory change, are in fact united by a single underlying principle, in this case, coherence. In the end, I will argue that these two examples bring out some metatheoretical reflections regarding the following questions: What are the differences between modeling in science and modeling in philosophy? What is the scope of the modeling method in philosophy? And what does this imply for our understanding of Bayesianism? (shrink)

Das Thema dieses Bandes ist die Frage, ob die Wissenschaftstheorie eine normative Disziplin ist. Zunächst überrascht die Frage, denn für viele Wissenschaftstheoretiker ist die Antwort ein klares „Ja“; sie halten es für einen Allgemeinplatz, dass die Wissenschaftstheorie ein normatives Unternehmen ist. Bei genauerem Hinsehen stellt sich jedoch heraus, dass die Frage unterschiedliche Interpretationen zulässt, die einzeln diskutiert werden müssen. Dies geschieht im ersten Abschnitt. Im zweiten Abschnitt suchen wir nach möglichen Erklärungen dafür, warum die Wissenschaftstheorie bisher bei dem Projekt, eine (...) allseits akzeptable Methodologie wissenschaftlichen Schließens zu formulieren und zu begründen, so wenig Erfolg hatte. Eine mögliche Erklärung für den ausbleibenden Erfolg ist der Partikularismus, wonach Methoden keine allgemeine, sondern nur eine lokale, bereichsabhängige Gültigkeit haben. Im dritten Abschnitt wollen wir an Hand des Bayesianismus zeigen, dass die Methodologie doch nicht so schlecht da steht, wie es zunächst den Anschein hat. Der Bayesianismus ist für viele Wissenschaftstheoretiker der aussichtsreichste Kandidat für eine allgemeine Theorie induktiven Räsonierens. Wir besprechen seine Vorzüge, stellen aber auch dar, welche Konzessionen er an den Partikularismus machen muss. (shrink)

In The Uses of Argument, Stephen Toulmin proposed a model for the layout of arguments: claim, data, warrant, qualifier, rebuttal, backing. Since then, Toulmin’s model has been appropriated, adapted and extended by researchers in speech communications, philosophy and artificial intelligence. This book assembles the best contemporary reflection in these fields, extending or challenging Toulmin’s ideas in ways that make fresh contributions to the theory of analysing and evaluating arguments.

This book is a defence of the philosophy of common sense in the spirit of Thomas Reid and G.E. Moore, drawing on the work of Aristotle, evolutionary biology and psychology, and historical studies on the origins of early modern philosophy. It defines and explores common sense beliefs, and defends them from challenges from prominent philosophers.

J. Anthony Blair is a prominent international figure in argumentation studies. He is among the originators of informal logic, an author of textbooks on the informal logic approach to argument analysis and evaluation and on critical thinking, and a founder and editor of the journal Informal Logic. Blair is widely recognized among the leaders in the field for contributing formative ideas to the argumentation literature of the last few decades. This selection of key works provides insights into the history of (...) the field of argumentation theory and various related disciplines. It illuminates the central debates and presents core ideas in four main areas: Critical Thinking, Informal Logic, Argument Theory and Logic, Dialectic and Rhetoric. (shrink)

The regress of reasons threatens an epistemic agent’s right to claim that any beliefs are justified. In response, Peter Klein’s infinitism argues that an infinite series of supporting reasons of the right type not only is not vicious but can make for epistemic justification. In order to resist the sceptic, infinitism needs to provide reason to think that there is at least one justified belief in the world. Under an infinitist conception this involves showing that at least one belief is (...) supported by an infinite series of supporting reasons. This paper argues that showing this makes problems for the infinitist. The finite minds problem that prevents completion of an infinite series is well documented. This paper examines alternative attempts to provide evidence of infinity that the infinitist might take, whether by using a notion of justification without infinite reasons or by altering the notion of evidence. It concludes that both of these fail and consequently infinitism is unable to offer a solution to Agrippa’s trilemma. (shrink)

Since at least the 1938 publication of Hans Reichenbach’s Experience and Predication , there has been widespread agreement that, when discussing the beliefs that people have, it is important to distinguish contexts of discovery and contexts of justification. Traditionally, when one conflates the two contexts, the result is a “genetic fallacy”. This paper examines genealogical critiques and addresses the question of whether such critiques are fallacious and, if so, whether this vitiates their usefulness. The paper concludes that while there may (...) be one or more senses in which genealogical critiques are fallacious, this does not vitiate their value. (shrink)

Current practice in logic increasingly accords recognition to abductive, presumptive or plausible arguments, in addition to deductive and inductive arguments. But there is uncertainty about what these terms exactly mean, what the differences between them are (if any), and how they relate. By examining some analyses ofthese terms and some of the history of the subject (including the views of Peirce and Cameades), this paper sets out considerations leading to a set of definitions, discusses the relationship of these three forms (...) of argument to argumentation schemes and sets out a new argumentation scheme for abductive argument. (shrink)

The no-free-lunch theorems promote a skeptical conclusion that all possible machine learning algorithms equally lack justification. But how could this leave room for a learning theory, that shows that some algorithms are better than others? Drawing parallels to the philosophy of induction, we point out that the no-free-lunch results presuppose a conception of learning algorithms as purely data-driven. On this conception, every algorithm must have an inherent inductive bias, that wants justification. We argue that many standard learning algorithms should rather (...) be understood as model-dependent: in each application they also require for input a model, representing a bias. Generic algorithms themselves, they can be given a model-relative justification. (shrink)

I evaluate Schurz's proposed meta-inductive justification of induction, a refinement of Reichenbach's pragmatic justification that rests on results from the machine learning branch of prediction with expert advice. My conclusion is that the argument, suitably explicated, comes remarkably close to its grand aim: an actual justification of induction. This finding, however, is subject to two main qualifications, and still disregards one important challenge. The first qualification concerns the empirical success of induction. Even though, I argue, Schurz's argument does not need (...) to spell out what inductive method actually consists in, it does need to postulate that there is something like the inductive or scientific prediction strategy that has so far been significantly more successful than alternative approaches. The second qualification concerns the difference between having a justification for inductive method and for sticking with induction for now. Schurz's argument can only provide the latter. Finally, the remaining challenge concerns the pool of alternative strategies, and the relevant notion of a meta-inductivist's optimality that features in the analytic step of Schurz's argument. Building on the work done here, I will argue in a follow-up paper that the argument needs a stronger dynamic notion of a meta-inductivist's optimality. (shrink)

We explore which types of probabilistic updating commute with convex IP pooling. Positive results are stated for Bayesian conditionalization, imaging, and a certain parameterization of Jeffrey conditioning. This last observation is obtained with the help of a slight generalization of a characterization of externally Bayesian pooling operators due to Wagner :336–345, 2009). These results strengthen the case that pooling should go by imprecise probabilities since no precise pooling method is as versatile.

The main aim of this paper is to revisit the curve fitting problem using the reliability of inductive inference as a primary criterion for the ‘fittest' curve. Viewed from this perspective, it is argued that a crucial concern with the current framework for addressing the curve fitting problem is, on the one hand, the undue influence of the mathematical approximation perspective, and on the other, the insufficient attention paid to the statistical modeling aspects of the problem. Using goodness-of-fit as the (...) primary criterion for ‘best', the mathematical approximation perspective undermines the reliability of inference objective by giving rise to selection rules which pay insufficient attention to ‘accounting for the regularities in the data'. A more appropriate framework is offered by the error-statistical approach, where (i) statistical adequacy provides the criterion for assessing when a curve captures the regularities in the data adequately, and (ii) the relevant error probabilities can be used to assess the reliability of inductive inference. Broadly speaking, the fittest curve (statistically adequate) is not determined by the smallness if its residuals, tempered by simplicity or other pragmatic criteria, but by the nonsystematic (e.g. white noise) nature of its residuals. The advocated error-statistical arguments are illustrated by comparing the Kepler and Ptolemaic models on empirical grounds. ‡I am grateful to Deborah Mayo and Clark Glymour for many valuable suggestions and comments on an earlier draft of the paper; estimating the Ptolemaic model was the result of Glymour's prompting and encouragement. †To contact the author, please write to: Department of Economics, Virginia Tech 3019 Pamplin Hall (0316), Blacksburg, VA 24061; e-mail: [email protected]. (shrink)

The main objective of the paper is to propose a frequentist interpretation of probability in the context of model-based induction, anchored on the Strong Law of Large Numbers (SLLN) and justifiable on empirical grounds. It is argued that the prevailing views in philosophy of science concerning induction and the frequentist interpretation of probability are unduly influenced by enumerative induction, and the von Mises rendering, both of which are at odds with frequentist model-based induction that dominates current practice. The differences between (...) the two perspectives are brought out with a view to defend the model-based frequentist interpretation of probability against certain well-known charges, including [i] the circularity of its definition, [ii] its inability to assign ‘single event’ probabilities, and [iii] its reliance on ‘random samples’. It is argued that charges [i]–[ii] stem from misidentifying the frequentist ‘long-run’ with the von Mises collective. In contrast, the defining characteristic of the long-run metaphor associated with model-based induction is neither its temporal nor its physical dimension, but its repeatability (in principle); an attribute that renders it operational in practice. It is also argued that the notion of a statistical model can easily accommodate non-IID samples, rendering charge [iii] simply misinformed. (shrink)

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. (shrink)

The orthodoxy that conditional probabilities reflect what are for a subject evidential bearings is seconded. This significance suggests that there should be principles equating rationally revised probabilities on new information with probabilities reached by conditionalizing on this information. Several principles, two of which are endorsed, are considered. A book is made against a violator of these, and it is argued that there must be something wrong with a person against whom such books can be made. Appendices comment on Popper-functions, elaborate (...) on bets and odds, and relate dutch books and strategies to conditions of inconsistency (Ramsey's idea) and imperfection. (shrink)

This paper has three interdependent aims. The first is to make Reichenbach’s views on induction and probabilities clearer, especially as they pertain to his pragmatic justification of induction. The second aim is to show how his view of pragmatic justification arises out of his commitment to extensional empiricism and moots the possibility of a non-pragmatic justification of induction. Finally, and most importantly, a formal decision-theoretic account of Reichenbach’s pragmatic justification is offered in terms both of the minimax principle and the (...) dominance principle. (shrink)

This article suggests a ‘best alternative' justification of induction (in the sense of Reichenbach) which is based on meta-induction . The meta-inductivist applies the principle of induction to all competing prediction methods which are accessible to her. It is demonstrated, and illustrated by computer simulations, that there exist meta-inductivistic prediction strategies whose success is approximately optimal among all accessible prediction methods in arbitrary possible worlds, and which dominate the success of every noninductive prediction strategy. The proposed justification of meta-induction is (...) mathematically analytical. It implies, however, an a posteriori justification of object-induction based on the experiences in our world. *Received November 2005; revised March 2008. †To contact the author, please write to: Department of Philosophy, University of Duesseldorf, Universitaetsstrasse 1, Geb. 23.21, Duesseldorf, Germany D-40225; e-mail: [email protected]. (shrink)

Extant literature on Goodman’s ‘New Riddle of Induction’ deals mainly with two versions. I consider both of them, starting from the (‘epistemic’) version of Goodman’s classic of 1954. It turns out that it belongs to the realm of applications of inductive logic, and that it can be resolved by admitting only significant evidence (as I call it) for confirmations of hypotheses. Sect. 1 prepares some ground for the argument. As much of it depends on the notion of evidential significance, this (...) concept is defined and its introduction motivated. Further, I introduce and explain the distinction between support and confirmation: put in a slogan, ‘confirmation is support by significant evidence’. The second section deals with the Riddle itself. I demonstrate that, given the provisions of the first section, not ‘anything confirms anything’: significant green-evidence confirms only green-hypotheses (and no grue-hypotheses), and significant grue-evidence confirms only grue-hypotheses (and no green-hypotheses), whichever terms we use for expressing these evidences or hypotheses. The third section rounds off my treatment. First I show that Frank Jackson’s use of his counterfactual condition is unsuccessful. Further, I argue that no unwanted consequences result, if one starts from the other, ‘objective’, definition of ‘grue’, as it constitutes no more than a mere fact of logic that cannot do any harm. Finally, I present a grue-case involving both kinds of definition, where the exclusive confirmation of either the green- or the grue-hypothesis is shown. (shrink)

I will attempt to draw analogies between the problems of inductionand problems of deduction with Carroll’s paradox and Susan Haack’sarguments. These analogies either strengthen a justification of induction by showing that deduction faces similar problems, or weaken our justification of deduction by showing it is not entirely justified. I will show that although deduction does face similar problems any justification that can work for induction will also be applicable to deduction, but not vice versa. Finally, I will show that Reichenbach’s (...) system of vindicating induction will also provide vindication for deduction, and argue that deduction preserves truth to a greaterextent than induction. (shrink)

Taken as a model for how groups should make collective judgments and decisions, the ideal of deliberative democracy is inherently ambiguous. Consider the idealised case where it is agreed on all sides that a certain conclusion should be endorsed if and only if certain premises are admitted. Does deliberative democracy recommend that members of the group debate the premises and then individually vote, in the light of that debate, on whether or not to support the conclusion? Or does it recommend (...) that members individually vote on the premises, and then let their commitment to the conclusion be settled by whether or not the group endorses the required premises? Is deliberative democracy to enforce the discipline of reason at the individual level, as in the first possibility, or at the collective level, as in the second? (shrink)

The problem of induction is formulated as a set of three questions, namely: ‘What is the nature of the attitude of acceptance that we adopt in relation to certain theories?’ ‘What are the rules according to which we select those theories which we accept?’ and, ‘What is the justification for the adoption of those rules?’. An original answer is proposed for each question in turn, with the help of the new concepts of sub-theory, established sub-theory, aberrant, arbitrary and degenerate theories. (...) The answer to the third question follows the lines of Reichenbach's pragmatic strategy. (shrink)

The word ‘probability’ in ordinary language has two different senses, here called inductive and physical probability. This paper examines the concept of inductive probability. Attempts to express this concept in other words are shown to be either incorrect or else trivial. In particular, inductive probability is not the same as degree of belief. It is argued that inductive probabilities exist; subjectivist arguments to the contrary are rebutted. Finally, it is argued that inductive probability is an important concept and that it (...) is a mistake to try to replace it with the concept of degree of belief, as is usual today. (shrink)

I conceive of inductive logic as a project of explication. The explicandum is one of the meanings of the word `probability' in ordinary language; I call it inductive probability and argue that it is logical, in a certain sense. The explicatum is a conditional probability function that is specified by stipulative definition. This conception of inductive logic is close to Carnap's, but common objections to Carnapian inductive logic (the probabilities don't exist, are arbitrary, etc.) do not apply to this conception.

In this paper, I defend an inductivist solution to Hume’s Problem of Induction against the popular counterinduction parody argument. Once we examine the structure of the inductivist position closely, we will see that there is no coherent way to parody it.

A familiar adage in the philosophy of science is that general hypotheses are better supported by varied evidence than by uniform evidence. Several studies suggest that young children do not respect this principle, and thus suffer from a defect in their inductive methodology. We argue that the diversity principle does not have the normative status that psychologists attribute to it, and should be replaced by a simple rule of probability. We then report experiments designed to detect conformity to the latter (...) rule in children's inductive judgment. The results suggest that young children in both the United States and Taiwan are sensitive to the constraints imposed by the rule on judgments of probability and evidential strength. We conclude with a suggested reinterpretation of the thesis that children's inductive methodology qualifies them as “little scientists.”. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

In this paper, I present an argument for a rational norm involving a kind of credal attitude called a quantificational credence – the kind of attitude we can report by saying that Lucy thinks that each record in Schroeder’s collection is 5% likely to be scratched. I prove a result called a Dutch Book Theorem, which constitutes conditional support for the norm. Though Dutch Book Theorems exist for norms on ordinary and conditional credences, there is controversy about the epistemic significance (...) of these results. So, my conclusion is that if Dutch Book Theorems do, in general, support norms on credal states, then we have support for the suggested norm on quantificational credences. Providing conditional support for this norm gives us a fuller picture of the normative landscape of credal states. (shrink)

This article illustrates in which sense genetic determinism is still part of the contemporary interactionist consensus in medicine. Three dimensions of this consensus are discussed: kinds of causes, a continuum of traits ranging from monogenetic diseases to car accidents, and different kinds of determination due to different norms of reaction. On this basis, this article explicates in which sense the interactionist consensus presupposes the innate?acquired distinction. After a descriptive Part 1, Part 2 reviews why the innate?acquired distinction is under attack (...) in contemporary philosophy of biology. Three arguments are then presented to provide a limited and pragmatic defense of the distinction: an epistemic, a conceptual, and a historical argument. If interpreted in a certain manner, and if the pragmatic goals of prevention and treatment are taken into account, then the innate?acquired distinction can be a useful epistemic tool. It can help, first, to understand that genetic determination does not mean fatalism, and, second, to maintain a system of checks and balances in the continuing nature?nurture debates. (shrink)

This article illustrates in which sense genetic determinism is still part of the contemporary interactionist consensus in medicine. Three dimensions of this consensus are discussed: kinds of causes, a continuum of traits ranging from monogenetic diseases to car accidents, and different kinds of determination due to different norms of reaction. On this basis, this article explicates in which sense the interactionist consensus presupposes the innate?acquired distinction. After a descriptive Part 1, Part 2 reviews why the innate?acquired distinction is under attack (...) in contemporary philosophy of biology. Three arguments are then presented to provide a limited and pragmatic defense of the distinction: an epistemic, a conceptual, and a historical argument. If interpreted in a certain manner, and if the pragmatic goals of prevention and treatment (ideally specifying what medicine and health care is all about) are taken into account, then the innate?acquired distinction can be a useful epistemic tool. It can help, first, to understand that genetic determination does not mean fatalism, and, second, to maintain a system of checks and balances in the continuing nature?nurture debates. (shrink)

This paper aims to make explicit the methodological conditions that should be satisfied for the Bayesian model to be used as a normative model of human probability judgment. After noticing the lack of a clear definition of Bayesianism in the psychological literature and the lack of justification for using it, a classic definition of subjective Bayesianism is recalled, based on the following three criteria: an epistemic criterion, a static coherence criterion and a dynamic coherence criterion. Then it is shown that (...) the adoption of this framework has two kinds of implications. The first one regards the methodology of the experimental study of probability judgment. The Bayesian framework creates pragmatic constraints on the methodology that are linked to the interpretation of, and the belief in, the information presented, or referred to, by an experimenter in order for it to be the basis of a probability judgment by individual participants. It is shown that these constraints have not been satisfied in the past, and the question of whether they can be satisfied in principle is raised and answered negatively. The second kind of implications consists of two limitations in the scope of the Bayesian model. They regard (1) the background of revision (the Bayesian model considers only revising situations but not updating situations), and (2) the notorious case of the null priors. In both cases Lewis’ rule is an appropriate alternative to Bayes’ rule, but its use faces the same operational difficulties. (shrink)

The thesis of this paper is that we can justify induction deductively relative to one end, and deduction inductively relative to a different end. I will begin by presenting a contemporary variant of Hume ’s argument for the thesis that we cannot justify the principle of induction. Then I will criticize the responses the resulting problem of induction has received by Carnap and Goodman, as well as praise Reichenbach ’s approach. Some of these authors compare induction to deduction. Haack compares (...) deduction to induction, and I will critically discuss her argument for the thesis that we cannot justify the principles of deduction next. In concluding I will defend the thesis that we can justify induction deductively relative to one end, and deduction inductively relative to a different end, and that we can do so in a non-circular way. Along the way I will show how we can understand deductive and inductive logic as normative theories, and I will briefly sketch an argument to the effect that there are only hypothetical, but no categorical imperatives. (shrink)

Work on analogy has been done from a number of disciplinary perspectives throughout the history of Western thought. This work is a multidisciplinary guide to theorizing about analogy. It contains 1,406 references, primarily to journal articles and monographs, and primarily to English language material. classical through to contemporary sources are included. The work is classified into eight different sections (with a number of subsections). A brief introduction to each section is provided. Keywords and key expressions of importance to research on (...) analogy are discussed in the introductory material. Electronic resources for conducting research on analogy are listed as well. (shrink)

In Thinking and Acting John Pollock offers some criticisms of Bayesian epistemology, and he defends an alternative understanding of the role of probability in epistemology. Here, I defend the Bayesian against some of Pollock's criticisms, and I discuss a potential problem for Pollock's alternative account.

As it is standardly conceived, Inference to the Best Explanation (IBE) is a form of ampliative inference in which one infers a hypothesis because it provides a better potential explanation of one’s evidence than any other available, competing explanatory hypothesis. Bas van Fraassen famously objected to IBE thus formulated that we may have no reason to think that any of the available, competing explanatory hypotheses are true. While revisionary responses to the Bad Lot Objection concede that IBE needs to be (...) reformulated in light of this problem, reactionary responses argue that the Bad Lot Objection is fallacious, incoherent, or misguided. This paper shows that the most influential reactionary responses to the Bad Lot Objection do nothing to undermine the original objection. This strongly suggests that proponents of IBE should focus their efforts on revisionary responses, i.e. on finding a more sophisticated characterization of IBE for which the Bad Lot Objection loses its bite. (shrink)

A critical examination of the dialectical approach, focusing on a comparison ofthe illative and the dialectical definitions of argument. I distinguish a moderate, a strong and a hyper dialectical conception of argument. I critique Goldman's argument for the moderate conception and Johnson's argument for the strong conception, and argue that the moderate conception is correct.

A popular three-stage argument appraisal strategy calls for (1) identifying the parts of the argument, (2) classifYing the argument as deductive, inductive, or some other type, and (3) appraising the argument using the standards appropriate for the type. This strategy fails for a number of reasons. I propose a comprehensive alternative approach that distinguishes between inductive, deductive, and other standards; calls for the successive application of standards combined with assumption-ascription, according to policies that depend for their selection on the goals (...) of the appraiser; and provides for qualified reasoning. (shrink)

Defining qualified reasoning as reasoning containing such loose qualifying words as 'probably,' 'usually,' 'probable, 'likely,' 'ceteris paribus,' and 'primafacie, Ennis argues that typical cases of qualified reasoning, though they might be good arguments, are deductively invalid, implying that such arguments fail soundness standards. He considers and rejects several possible alternative ways of viewing such cases, ending with a proposal for applying qualified soundness standards, which requires employment of sufficient background knowledge, sensitivity, experience and understanding of the situation. All of this (...) takes place as part of the process, introduced elsewhere, of successively applying different legitimate sets of standards until one is found that is satisfied, or none is found, the latter calling for rejection of the argument, the former calling for its acceptance. (shrink)

Both I and Belnap, motivated the "Belnap-Dunn 4-valued Logic" by talk of the reasoner being simply "told true" (T) and simply "told false" (F), which leaves the options of being neither "told true" nor "told false" (N), and being both "told true" and "told false" (B). Belnap motivated these notions by consideration of unstructured databases that allow for negative information as well as positive information (even when they conflict). We now experience this on a daily basis with the Web. But (...) the 4-valued logic is deductive in nature, and its matrix is discrete: there are just four values. In this paper I investigate embedding the 4-valued logic into a context of probability. Jøsang's Subjective Logic introduced uncertainty to allow for degrees of belief, disbelief, and uncertainty. We extend this so as to allow for two kinds of uncertainty— that in which the reasoner has too little information (ignorance) and that in which the reasoner has too much information (conflicted). Jøsang's "Opinion Triangle" becomes an "Opinion Tetrahedron" and the 4-values can be seen as its vertices. I make/prove various observations concerning the relation of non-classical "probability" to non-classical logic. (shrink)

In a recent paper in this journal, Schramm presents what he takes to be an answer to Goodman’s New Riddle of Induction. His solution relies on the technical notion of evidential significance, which is meant to distinguish two ways that evidence may bear on a hypothesis: either via support or confirmation. As he puts his view in slogan form: “confirmation is support by significant evidence”. Once we make this distinction, Schramm claims, we see that Goodman’s famous riddle is dissolved, and (...) we are no longer forced into the “intolerable result” that anything confirms anything. Schramm makes a number of incisive observations in his paper, but I do not think he has solved the New Riddle. There are two reasons for this. First, Schramm has an overly narrow conception of what the Riddle amounts to; I would venture to guess that it is narrower than that of most contemporary philosophers. Thus his proposal does not address the primary concern. Second, Schramm’s notion of significant evidence relies on a counterfactual condition that bears more than a passing resemblance to that made famous by Jackson in his paper on the topic. However, Jackson’s proposal faces several well-known counterexamples, some of which can be adapted into Schramm’s framework. Schramm’s solution thus inherits a number of outstanding problems from Jackson’s proposal, which he has not shown us how to handle. (shrink)

The current state of inductive logic is puzzling. Survey presentations are recurrently offered and a very rich and extensive handbook was entirely dedicated to the topic just a few years ago [23]. Among the contributions to this very volume, however, one finds forceful arguments to the effect that inductive logic is not needed and that the belief in its existence is itself a misguided illusion , while other distinguished observers have eventually come to see at least the label as “slightly (...) antiquated” .What seems not to have lost any of its currency is the problem which inductive logic is meant to address. Inference from limited ascertained information to uncertain hypotheses is ubiquitous in learning, prediction and discovery. The logical insight that such kind of inference is fallible m .. (shrink)

Informal logic began in the 1970s as a critique of then-current theoretical assumptions in the teaching of argument analysis and evaluation in philosophy departments in the U.S. and Canada. The last 35 years have seen significant developments in informal logic and critical thinking theory. The paper is a pilot study of the influence of these advances in theory on what is taught in courses on argument analysis and critical thinking in U.S. and Canadian philosophy departments. Its finding, provisional and much-qualified, (...) is that the theoretical developments and refinements have had limited impact on instruction in leading philosophy departments. (shrink)

The problem of skepticism is often understood as a paradox: a valid argument with plausible premises whose conclusion is that we lack justification for perceptual beliefs. Typically, this conclusion is deemed unacceptable, so a theory is offered that posits conditions for justification on which some premise is false. The theory defended here is more general, and explains why the paradox arises in the first place. Like Strawson’s (Introduction to logical theory, Wiley, New York, 1952) “ordinary language” approach to induction, the (...) theory posits something built into the very notion of justification: it is loaded with a bias towards the proposition that we are not massively deceived. Beyond the paradox, remaining skeptical problems consist of metaphysical and practical questions: whether we are massively deceived, or why we should use our loaded notion rather than some other. Such challenges have pro- found epistemological significance, but they are not problems that an a priori theory of justification can solve. (shrink)