Marc Alspector-Kelly claims that Bas van Fraassen’s primary challenge to the scientific realist is for the realist to find a way to justify the use of some mode of inference that takes him from the world of observables to knowledge of the world of unobservables without thereby abandoning empiricism. It is argued that any effort to justify such an “inferential wand” must appeal either to synthetic a priori or synthetic a posteriori knowledge. This disjunction turns into a dilemma for the (...) empirically-minded realist as either disjunct leads to unwanted consequences. In this paper, I split the horns of this dilemma by arguing that the realist can justify one particular such mode of inference – abduction – without committing himself to rationalism. The realist may justify this mode of inference by appealing to the analytic a priori axioms of the probability calculus. I show that Peter Lipton’s tripartite defense of abduction constitutes such a method of justification. (shrink)

This paper develops a descriptive and normative account of how people respond to testimony. It postulates a default pathway in which people more or less automatically respond to a claim by accepting it, as long as the claim made is consistent with their beliefs and the source is credible. Otherwise, people enter a reflective pathway in which they evaluate the claim based on its explanatory coherence with everything else they believe. Computer simulations show how explanatory coherence can be maximized in (...) real-life cases, taking into account all the relevant evidence including the credibility of whoever is making a claim. The explanatory-coherence account is more plausible both descriptively and normatively than a Bayesian account. (shrink)

Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people’s actual explanatory judgments. Here, I present my own experimental work investigating this question. I argue that one measure in (...) particular is an accurate descriptor of explanatory judgments. Then, I discuss some interesting implications of this result for both the epistemology and the psychology of explanatory reasoning. (shrink)

Barnes, A. and P. Thagard Empathy and analogy. Dialogue: Canadian Philosophical Review, 36: 705-720. HTML Croft, D., & Thagard, P.. Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani and N. Nersessian, Model-based reasoning: Science, technology, values. New York: Kluwer/Plenum, 259-274. PDF only. HTML description of program and code for DIVA.

Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods or (...) priors per se; the virtues may be more accessible epistemically than likelihoods or priors. I then prove a ceteris paribus theorem regarding theoretical consilience, use it to correct a recent application of Reichenbach's common cause principle, and apply it to a test case of scientific reasoning. Explanation and confirmation The heuristic conception of theoretical virtues Abduction and the accessibility of explanatory power Evidential and theoretical consilience A test case: gravitational lensing Conclusion Thus natural science appears completely to lose from sight the large and general questions; but all the more splendid is the success when, groping in the thicket of special questions, we suddenly find a small opening that allows a hitherto undreamt of outlook on the whole. (L. Boltzmann, Theoretical Physics and Philosophical Problems). (shrink)

When a theory is confronted with a problem such as a paradox, an empirical anomaly, or a vicious regress, one may change part of the theory to solve that problem. Sometimes the proposed solution is considered ad hoc. This paper gives a new definition of ‘ad hoc solution’ as used in both philosophy and science. I argue that a solution is ad hoc if it fails to live up to the explanatory requirements of a theory because the solution is not (...) backed by an explanation or because it does not diagnose the problem. Ad hoc solutions are thus magical: they solve a problem without providing insight. This definition helps to explain both why ad hoc solutions are bad and why there may be disagreement about cases. (shrink)

We face reality presented with the data of conscious experience and nothing else. The project of early modern philosophy was to build a complete theory of the world from this starting point, with no cheating. Crucial to this starting point is the data of conscious sensory experience – sense data. Attempts to avoid this project often argue that the very idea of sense data is confused. But the sense-data way of talking, the sense-data language, can be freed from every blemish (...) using ideas from contemporary metaontology. We can adopt a sense-data framework that vindicates the traditional claims of sense-data theories and leads to plausible theories of perception and color. We can, we should, and in a sense, we must. Yet when we do, we face the traditional problem of external world skepticism, head-on. The real challenge of skepticism is forced upon us; it cannot honestly be avoided using externalist tricks, burden of proof shifting, or other razzle dazzle. But the challenge can be met: we are rational to posit the external world as the best explanation of the many synchronic and diachronic patterns over our sense-data. This paper argues for all of these points and ends with a plea for analytic empiricism – a traditional sense-data version of empiricism that uses all of the tools of analytic philosophy while avoiding the more questionable doctrines of the Vienna Circle (phenomenalism, verificationism). Analytic empiricism is our last best hope for completing the great philosophical project of early modern philosophy. (shrink)

We examine two leading theories of rational belief, the Lockean view and the explanationist view. The first is appealing because it fits with some independently plausible claims about the ways that rational persons pursue their aims. The second is appealing because it seems to account for intuitions that cause trouble for the Lockean view. While fitting the intuitive data is desirable, we are troubled that the explanationist view seems to clash with our theoretical beliefs about what rationality must be like. (...) We think that upon further examination, the intuitive appeal of the explanationist view starts to diminish. We also think that these further intuitions that spell trouble for the explanationist spell trouble for any theory that is not expectationist. We propose a novel expectationist theory of rational belief that improves upon the Lockean and the explanationist views. We think that recent defences of the Lockean view contain an important insight. A substantive theory of rational response should be based on a suitable theory of prizes and a suitable theory of how we should pursue prizes in the face of uncertainty. Most theories of rational belief typically take for granted a truth-centred picture of epistemic prizes (e.g., that epistemic desirability and undesirability can be fully understood in terms of accuracy) and then differ in terms of how they recommend pursuing prizes so understood. We think the Lockeans embrace plausible principles of how prizes should be pursued. We trace the difficulties that this view faces to veritistic assumptions about prizes. We suggest that some prizes are epistemically loaded in that a complete description of the prize will itself make reference to our epistemic states or standards. We argue that knowledge matters to rational belief and choice because in the epistemic domain, knowledge is the prize. We see this in practical domains, too. In some choice settings, what's desired is desired, in part, because it involves a kind of connection to reality only knowledge provides. (shrink)

In consciousness science, theories often differ not only in the account of consciousness they arrive at, but also with respect to how they understand their starting point. Some approaches begin with experimentally gathered data, whereas others begin with phenomenologically gathered data. In this paper, I analyse how the most influential phenomenology-first approach, namely the Integrated Information Theory (IIT) of consciousness, fits its phenomenologically gathered data with explanatory hypotheses. First, I show that experimentally driven approaches hit an explanatory roadblock, since we (...) cannot tell, at the present stage, which model of consciousness is best. Then, I show that IIT’s phenomenology-first approach implies a self-evidencing explanation according to which consciousness can be explained by starting from consciousness itself. I claim that IIT can take advantage of the virtuous circularity of this reasoning, but it also faces a data-fitting issue that is somehow similar to that faced by experiment-driven approaches: we are not given enough information to decide whether the explanatory hypotheses IIT employs to explain its phenomenological data are in fact best. I call this problem “the self-evidencing problem” for IIT, and after introducing it, I propose a possible way for IIT to solve it. (shrink)

In this article, I will provide a critical overview of the form of non-deductive reasoning commonly known as “Inference to the Best Explanation” (IBE). Roughly speaking, according to IBE, we ought to infer the hypothesis that provides the best explanation of our evidence. In section 2, I survey some contemporary formulations of IBE and highlight some of its putative applications. In section 3, I distinguish IBE from C.S. Peirce’s notion of abduction. After underlining some of the essential elements of IBE, (...) the rest of the entry is organized around an examination of various problems that IBE confronts, along with some extant attempts to address these problems. In section 4, I consider the question of when a fact requires an explanation, since presumably IBE applies only in cases where some explanation is called for. In section 5, I consider the difficult question of how we ought to understand IBE in light of the fact that among philosophers, there is significant disagreement about what constitutes an explanation. In section 6, I consider different strategies for justifying the truth-conduciveness of the explanatory virtues, e.g., simplicity, unification, scope, etc., criteria which play an indispensable role in any given application of IBE. In section 7, I survey some of the most recent literature on IBE, much of which consists of investigations of the status of IBE from the standpoint of the Bayesian philosophy of science. (shrink)

I present a cumulative case for the thesis that we only know propositions that are certain for us. I argue that this thesis can easily explain the truth of eight plausible claims about knowledge: -/- (1) There is a qualitative difference between knowledge and non-knowledge. (2) Knowledge is valuable in a way that non-knowledge is not. (3) Subjects in Gettier cases do not have knowledge. (4) If S knows that P, P is part of S’s evidence. (5) If S knows (...) that P, ~P is epistemically impossible for S. (6) If S knows that P, S can rationally act as if P. (7) If S knows that P, S can rationally stop inquiring whether P. (8) If S knows each of {P1, P2, … Pn}, and competently deduces Q from these propositions, S knows that Q. -/- I then argue that the skeptical costs of this thesis are outweighed by its explanatory power. (shrink)

Several theistic arguments are formulated as arguments for the best explanation. This article discusses how one can determine that some phenomenon actually needs an explanation. One way to demonstrate that an explanation is needed is by providing one. The proposed explanation ought to either make the occurrence of the phenomenon in question more probable than it occurring by chance, or it has to sufficiently increase our understanding of the phenomenon. A second way to demonstrate that an explanation is needed is (...) to show that the phenomenon in question both violates our expectations and is particularly noticeable. (shrink)

Can there be an objective morality without God? Derek Parfit argues that it can and offers a theory of morality that is neither theistic nor naturalistic. This book provides a critical assessment of Parfit's metaethical theory. Jakobsen identifies some problems in Parfit’s theory – problems concerning moral normativity, the ontological status of morality, and evolutionary influence on our moral beliefs – and argues that theological resources can help solve them. By showing how Parfit’s theory may be improved by the help (...) of theology, Jakobsen demonstrates the relevance of theology in philosophical and metaethical debates and argues that Christian theism offers a better explanation of morality than what Parfit’s non-naturalism does. (shrink)

In science and everyday life, we often infer that something is true because it would explain some set of facts better than any other hypothesis we can think of. But what if we have reason to believe that there is a better way to explain these facts that we just haven't thought of? Wouldn't that undermine our warrant for believing the best available explanation? Many philosophers have assumed that we can solve such underconsideration problems by stipulating that a hypothesis should (...) not only be 'the best' explanation available; rather, it should also be 'good enough'. Unfortunately, however, the only current suggestion for what it might mean to say that an explanation is 'good enough' is, well, not good enough. This paper aims to provide a better account of what is required for an explanatory hypothesis to be considered 'good enough'. In brief, the account holds that a `good enough' hypothesis is one that has gone through a process that I call explanatory consolidation, in which accumulating evidence and failed attempts to formulate better alternatives gradually make it more plausible that the explanation we currently have is better than any other that could be formulated. (shrink)

In this article, I consider an important challenge to the popular theory of scientific inference commonly known as ‘inference to the best explanation’, one that has received scant attention.1 1 The problem is that there exists a wide array of rival models of explanation, thus leaving IBE objectionably indeterminate. First, I briefly introduce IBE. Then, I motivate the problem and offer three potential solutions, the most plausible of which is to adopt a kind of pluralism about the rival models of (...) explanation. However, I argue that how ranking explanations on this pluralistic account of IBE remains obscure and pluralism leads to contradictory results. In light of these objections, I attempt to dissolve the problem by showing why IBE does not require a ‘model’ of explanation and by giving an account of what explanation consists in within the context of IBE. (shrink)

A aceitação ou a escolha de uma teoria científica por parte de uma comunidade científica é um evento ou processo central na dinâmica científica. É, também, um evento ou processo complexo –já que dele participam as teorias, a experiência e alguma forma de relação inferencial entre a teoria e a experiência.

Inference to the Best Explanation (IBE) advises reasoners to infer exactly one explanation. This uniqueness claim apparently binds us when it comes to “conjunctive explanations,” distinct explanations that are nonetheless explanatorily better together than apart. To confront this worry, explanationists qualify their statement of IBE, stipulating that this inference form only adjudicates between competing hypotheses. However, a closer look into the nature of competition reveals problems for this qualified account. Given the most common explication of competition, this qualification artificially and (...) radically constrains IBE’s domain of applicability. Using a more subtle, recent explication of competition, this qualification no longer provides a compelling treatment of conjunctive explanations. In light of these results, I suggest a different strategy for accommodating conjunctive explanations. Instead of modifying the form of IBE, I suggest a new way of thinking about the structure of IBE’s lot of considered hypotheses. (shrink)

Hempel’s Converse Consequence Condition (CCC), Entailment Condition (EC), and Special Consequence Condition (SCC) have some prima facie plausibility when taken individually. Hempel, though, shows that they have no plausibility when taken together, for together they entail that E confirms H for any propositions E and H. This is “Hempel’s paradox”. It turns out that Hempel’s argument would fail if one or more of CCC, EC, and SCC were modified in terms of explanation. This opens up the possibility that Hempel’s paradox (...) can be solved by modifying one or more of CCC, EC, and SCC in terms of explanation. I explore this possibility by modifying CCC and SCC in terms of explanation and considering whether CCC and SCC so modified are correct. I also relate that possibility to Inference to the Best Explanation. (shrink)

I develop a probabilistic account of coherence, and argue that at least in certain respects it is preferable to (at least some of) the main extant probabilistic accounts of coherence: (i) Igor Douven and Wouter Meijs’s account, (ii) Branden Fitelson’s account, (iii) Erik Olsson’s account, and (iv) Tomoji Shogenji’s account. Further, I relate the account to an important, but little discussed, problem for standard varieties of coherentism, viz., the “Problem of Justified Inconsistent Beliefs.”.

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

Although in the past three decades interest in mathematical explanation revived, recent literature on the subject seems to neglect the strict connection between explanation and discovery. In this paper I sketch an alternative approach that takes such connection into account. My approach is a revised version of one originally considered by Descartes. The main difference is that my approach is in terms of the analytic method, which is a method of discovery prior to axiomatized mathematics, whereas Descartes’s approach is in (...) terms of the analytic–synthetic method, which is a heuristic pattern in already axiomatized mathematics. (shrink)

Roche and Sober (2013; 2014; 2017; 2019) have offered an important new argument that explanatoriness lacks confirmatory significance. My aim in this paper is not only to contend that their argument fails to show that in confirmation ‘there is nothing special about explanatoriness’ (Roche & Sober, 2017: 589), but also to reveal what is special confirmationwise about explanatoriness. I will argue that much of the heavy work in Roche and Sober's argument is done by the dichotomy into which they carve (...) up the philosophical options: either explanatory considerations per se are confirmatorily relevant or they acquire whatever confirmatory significance they may possess only by way of background beliefs and so no differently from non‐explanatory considerations. I will argue that this is a false dichotomy: Explanatoriness per se can have confirmatory relevance even while explanatory considerations acquire their confirmatory relevance only through background opinions. Furthermore, there is ‘something special’ about the background opinions concerning explanations that allow explanatoriness in itself to have confirmatory impact. Unlike other sorts of background, having some background opinions expressly about explanations is indispensable to being an observer at all. (shrink)

Several scholars observed that narratives about the human past are evaluated comparatively. Few attempts have been made, however, to explore how such evaluations are actually done. Here I look at a lengthy “contest” among several historiographic narratives, all constructed to make sense of another one—the biblical story of the conquest of Canaan. I conclude that the preference of such narratives can be construed as a rational choice. In particular, an easily comprehensible and emotionally evocative narrative will give way to a (...) complex and mundane one, when the latter provides a more coherent account of the consensually accepted body of evidence. This points to a fundamental difference between historiographic narratives and fiction, contrary to some influential opinions in the philosophy of historiography. Such historiographic narratives have similarities with hypotheses and narrative explanations in natural science. (shrink)

This paper discusses two senses in which a hypothesis may be said to unify evidence. One is the ability of the hypothesis to increase the mutual information of a set of evidence statements; the other is the ability of the hypothesis to explain commonalities in observed phenomena by positing a common origin for them. On Bayesian updating, it is only mutual information unification that contributes to the incremental support of a hypothesis by the evidence unified. This poses a challenge for (...) the view that explanation is a confirmatory virtue that contributes to such incremental support; its advocates must ground it in some relevant difference between humans and a Bayesian agent. (shrink)

There are two important philosophical research programmes on explanation in the twentieth century—the search for an account or model of scientific explanation, and the defence of inference to the best explanation as a rational form of inference. These two research programmes have largely developed independently from one another. This paper argues that bringing the two research programmes in contact promises to yield fruitful discussion. I consider and reject two arguments for keeping the two research programmes separate. I outline several issues (...) related to both research programmes that would benefit from inter(sub)disciplinary dialogue. (shrink)

This book examines the philosophical conception of abductive reasoning as developed by Charles S. Peirce, the founder of American pragmatism. It explores the historical and systematic connections of Peirce's original ideas and debates about their interpretations. Abduction is understood in a broad sense which covers the discovery and pursuit of hypotheses and inference to the best explanation. The analysis presents fresh insights into this notion of reasoning, which derives from effects to causes or from surprising observations to explanatory theories. The (...) author outlines some logical and AI approaches to abduction as well as studies various kinds of inverse problems in astronomy, physics, medicine, biology, and human sciences to provide examples of retroductions and abductions. The discussion covers also everyday examples with the implication of this notion in detective stories, one of Peirce’s own favorite themes. The author uses Bayesian probabilities to argue that explanatory abduction is a method of confirmation. He uses his own account of truth approximation to reformulate abduction as inference which leads to the truthlikeness of its conclusion. This allows a powerful abductive defense of scientific realism. This up-to-date survey and defense of the Peircean view of abduction may very well help researchers, students, and philosophers better understand the logic of truth-seeking. (shrink)

Selection explanations explain some non-accidental generalizations in virtue of a selection process. Such explanations are not particulaizable - they do not transfer as explanations of the instances of such generalizations. This is unlike many explanations in the physical sciences, where the explanation of the general fact also provides an explanation of its instances (i.e. standard D-N explanations). Are selection explanations (e.g. in biology) therefore a different kind of explanation? I argue that to understand this issue, we need to see that (...) a standard D-N explanation of some non-accidental generalization (al Fs are Gs) may also ipso facto explain its contrapositive (all non-Gs are non-Fs), but the explanation is particularizable with respect to the former but not to the latter. This can be seen by noting that the Raven Paradox counterexample to the H-D model of confirmation also generates a counterexample to the D-N model of explanation (all ravens are black does not explain why the non-black shoe is a non-raven). In such cases it is natural to take the generalization with the positive predicates to have a particularizable explanation. However, this need not be the case, and in selection explanations it is the generalization with the positive predicates whose explanation is no particularizable. Thus there is no need to suppose that selection explanations are fundamentally different. (shrink)

In this article, I compare two varieties of abduction as reconstructive models for analysing discovery. The first is 'Hansonian abduction', which is based on N. R. Hanson's formulations of abduction. The other is 'Harmanian abduction', the Inference to the Best Explanation (IBE) model, formulated especially by Gilbert Harman. Peter Lipton has analysed processes of discovery on the basis of his developed form of Harmanian abduction. I argue that Hansonian abduction would, however, be a more apt model for this purpose. As (...) an example, I reconstruct, in a Hansonian manner, Ignaz Semmelweis's research on childbed fever and compare it to the IBE reconstruction of Lipton. I argue that Hansonian abduction is in accordance with Lipton's aim of taking into account the distinction between actual and potential explanations on the one hand, and between likely and lovely explanations on the other. I maintain that a developed version of Hansonian abduction combined with loveliness gives an important, new conceptual means for analysing processes of discovery. (shrink)

We provide a novel Bayesian justification of inference to the best explanation. More specifically, we present conditions under which explanatory considerations can provide a significant confirmatory boost for hypotheses that provide the best explanation of the relevant evidence. Furthermore, we show that the proposed Bayesian model of IBE is able to deal naturally with the best known criticisms of IBE such as van Fraassen?s?bad lot? argument.

This paper considers an application of work on probabilistic measures of coherence to inference to the best explanation. Rather than considering information reported from different sources, as is usually the case when discussing coherence measures, the approach adopted here is to use a coherence measure to rank competing explanations in terms of their coherence with a piece of evidence. By adopting such an approach IBE can be made more precise and so a major objection to this mode of reasoning can (...) be addressed. Advantages of the coherence - based approach are pointed out by comparing it with several other ways to characterize ‘ best explanation ’ and showing that it takes into account their insights while overcoming some of their problems. The consequences of adopting this approach for IBE are discussed in the context of recent discussions about the relationship between IBE and Bayesianism. (shrink)

Special issue. With contributions by Luc Bovens and Stephan Hartmann, David Glass, Keith Lehrer, Erik Olsson, Tomoji Shogenji, Mark Siebel, and Paul Thagard.

This paper aims at elucidating the connection between explanatory considerations and epistemic justification stipulated by explanationism which take epistemic justification to be definable in terms of best explanations. By relying on the notion of truthlikeness, this paper argues that it is rational for a subject to expect the best explanation she has for her evidence to be more truthlike than any of the other potential explanations available to her by virtue of containing a class of propositions that, given her evidence, (...) she is justified in believing. Based on this elucidation of the connection between explanatory considerations and epistemic justification, an explanationist account of the evidential support relation is then offered. (shrink)

This paper argues that there is an important connection between Inference to the Best Explanation and Bayesianism, in the medical context of the interplay between mechanisms and population studies. It is argued that the criteria for evaluating mechanistic evidence can be used in Inference to the Best Explanation and such use thereby increases the resilience of probabilities in a Bayesian framework. This point grows out of the emerging literature on evidence-based medicine and naturally strengthens McCain and Poston's proposal that explanatory (...) information is evidentially relevant. (shrink)

Inference to the Best Explanation is usually employed in the Scientific Realism debates. As far as particular scientific theories are concerned, its most ready usage seems to be that of a theory of confirmation. There are however more uses of IBE, namely as an epistemological theory of testimony and as a means of categorising and justifying the sources of evidence. In this paper, I will present, develop and exemplify IBE as a theory of the quality of evidence - taking examples (...) from medicine and showing that IBE can thereby provide the epistemological underpinning and justify the criteria of grading quality of mechanistic evidence that have been recently provided in the Clarke et al. paper on how evidence of medical mechanisms is to be construed alongside population studies. (shrink)

This article considers the prospects of inference to the best explanation as a method of confirming causal claims vis-à-vis the medical evidence of mechanisms. I show that IBE is actually descriptive of how scientists reason when choosing among hypotheses, that it is amenable to the balance/weight distinction, a pivotal pair of concepts in the philosophy of evidence, and that it can do justice to interesting features of the interplay between mechanistic and population level assessments.