Historically, hypotheses failed in most cases to correctly forecast the workings of complex biological systems. Francis Crick’s adaptor hypothesis, however, stands out as an exceptional case of a confirmed abstract prediction. This hypothesis presciently anticipated the existence of RNA adaptors that function as bridges between amino acids and the chemically different nucleic acid template for proteins. Crick conjectured that the adaptors are enzymatically charged with cognate amino acids, they bind to complementary protein-coding nucleic acid, and their liberated amino acids are (...) incorporated into growing protein chains. Independently from and concomitantly with Crick’s hypothesis, Mahlon Hoagland and Paul Zamecnik conducted experiments with no guiding theory that culminated in discoveries of the actual adaptors, transfer RNA (tRNA) molecules, and their amino acids charging enzymes. This paper traces the parallel histories of Crick’s adaptor hypothesis and of the experimental discovery of tRNA and compares their relative impacts on the scientific community. Remarkably, despite the brilliance of Crick’s confirmed prognostication, it had marginal impact on practicing scientists. Conversely, Hoagland and Zamecnik’s experimental discoveries and their evidence-based model of protein synthesis had immediate and enduring impact. I discuss possible explanations for the different impacts of the theoretical prediction and experimental identifications of the same entities. (shrink)

According to Phenomenal Conservatism (PC), if a subject S has an appearance that P, in the absence of defeaters, S has justification for believing P by virtue of her appearance's inherent justifying power. McCain and Moretti (2021) have argued that PC is affected by the problem of reflective awareness: if S becomes reflectively aware of an appearance, the appearance loses its inherent justifying power. This limits the explanatory power of PC and reduces its antisceptical bite. This paper provides a novel (...) argument to the same conclusion and contends that it does not apply to Phenomenal Explanationism, the appearance-based account of justification alternative to PC defended by McCain and Moretti (2021). (shrink)

A methodology of science must satisfy two requirements: (i) It must be ampliative: the theories which it generates must make statements that go far beyond any data or observations that may have motivated those theories in the first place. (ii) It must be epistemically probative: it must somehow provide a warrant for believing that the theories so produced are correct, or at least partially correct, even if they can never be fully confirmed. These two requirements pull in opposite directions, and (...) attempts to specify the “scientific method” often focus on one to the exclusion of the other. On a few points there now exists something approaching a consensus. (i) Scientific hypotheses — including, particularly, statements about unobserved or unobservable entities or mechanisms — remain conjectural, no matter how frequently predictions based on those hypotheses are found to coincide with data. (ii) A good (best?) indicator of a theory’s verisimilitude is its ability to successfully predict phenomena which it was not specifically designed to predict. I discuss these ideas with particular reference to cosmological theories. (shrink)

Many epidemics consist in individuals spreading infection to others. From the population perspective, they also have population characteristics important in modeling, explaining, and intervening in epidemics. I analyze epidemiology’s contemporary population perspective through the example of epidemics by examining two central principles attributed to Geoffrey Rose: a distinction between the causes of cases and the causes of incidence, and between “high-risk” and “population” strategies of prevention. Both principles require revision or clarification to capture the sense in which they describe distinct (...) perspectives on the same phenomenon, each perspective capturing a different level of contrastive analysis. (shrink)

We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. (...) We conclude from this that topological explanations are autonomous from their mechanistic counterparts. (shrink)

Several metaphysical naturalists argue that the success of science, together with the claim that scientists adhere to methodological naturalism, amounts to strong evidence for metaphysical naturalism. I call this the scientific-success argument. It is argued that the scientific-success argument is similar to the no-miracles argument for realism in philosophy of science. On the no-miracles argument, the success of science is taken as strong evidence that scientific theories are true. Based on this similarity, some considerations relevant to one argument may also (...) be relevant to the other. One particular consideration is explored. The selectionist response to the no-miracles argument states that on an evolutionary model of science, in which scientific theories are accepted only after surviving a rigorous selection process, the no-miracles argument fails. The selectionist response also applies to the scientific-success argument. If scientific theories are selected for success, we do not need to explain the success of science by appealing to metaphysical naturalism. (shrink)

Contemporary debate surrounding the nature of scientific progress has focused upon the precise role played by justification, with two realist accounts having dominated proceedings. Recently, however, a third realist account has been put forward, one which offers no role for justification at all. According to Finnur Dellsén’s (Stud Hist Philos Sci Part A 56:72–83, 2016) noetic account, science progresses when understanding increases, that is, when scientists grasp how to correctly explain or predict more aspects of the world that they could (...) before. In this paper, we argue that the noetic account is severely undermotivated. Dellsén provides three examples intended to show that understanding can increase absent the justification required for true belief to constitute knowledge. However, we demonstrate that a lack of clarity in each case allows for two contrasting interpretations, neither of which serves its intended purpose. On the first, the agent involved lacks both knowledge and understanding; and, on the second, the agent involved successfully gains both knowledge and understanding. While neither interpretation supports Dellsén’s claim that understanding can be prised apart from knowledge, we argue that, in general, agents in such cases ought to be attributed neither knowledge nor understanding. Given that the separability of knowledge and understanding is a necessary component of the noetic account, we conclude that there is little support for the idea that science progresses through increasing understanding rather than the accumulation of knowledge. (shrink)

According to a version of Infallibilism, if one knows that p, then one’s evidence for p entails p. In her Fallibilism: Evidence and Knowledge, Jessica Brown has recently developed two arguments against Infalliblism, which can both be presented in the form of a dilemma. According to the first dilemma, the infallibilist can avoid scepticism only if she endorses the claim that if one knows that p then p is part of one’s evidence for p. But this seems to come at (...) the cost of making infelicitous claims. According to the second dilemma, the infallibilist cannot make sense of the phenomenon of defeat unless she rejects closure. In this paper, we argue that the infallibilist has the conceptual tools to resist both dilemmas. (shrink)

Occam’s razor is frequently considered to be a cornerstone of the scientific method. Indeed, it was and remains a valuable tool for scientific and philosophical inquiry. However, we provided an overview of some historical instances in which it led science away from a reasonable and sound heuristic approach. Some words of caution are necessary to clarify how, contrary to common belief, a too strict adherence to such a principle did not guarantee scientific rigor but, rather, obstructed further progress.

In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...) prominent account of scientific method, often called “Inference to the Best Explanation”. Later on, in Section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely, the argument due to Roche and Sober Analysis, 73:659–668, that “explanatoriness is evidentially irrelevant.” This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In Section 4, I consider some extant responses to this argument, especially that of Climenhaga Philosophy of Science, 84:359–368,. In Section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In Section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, which states, roughly, that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations,” chance correlations which we should not rely upon for predictive inference. In Section 7, I offer some concluding remarks. (shrink)

The present paper proposes a route to modal claims that allows us to infer to certain possibilities even if they are sensorily unimaginable and beyond the evidential capacity of stipulative imagining. After a brief introduction, Sect. 2 discusses imaginative resistance to help carve a niche for the kinds of inferences about which this essay is chiefly concerned. Section 3 provides three classic examples, along with a discussion of their similarities and differences. Section 4 recasts the notion of potential explanation in (...) Lipton’s (Inference to the best explanation, Routledge, Abingdon, 2004) in order to accommodate inferences to possibility claims; Sect. 5 then attempts to characterise a principle underlying such inferences. Section 6 concludes by discussing how the proposal relates to other modal epistemologies, with emphasis on the potential of such inferences to produce genuinely new ideas. (shrink)

Scientific realism driven by inference to the best explanation (IBE) takes empirically confirmed objects to exist, independent, pace empiricism, of whether those objects are observable or not. This kind of realism, it has been claimed, does not need probabilistic reasoning to justify the claim that these objects exist. But I show that there are scientific contexts in which a non-probabilistic IBE-driven realism leads to a puzzle. Since IBE can be applied in scientific contexts in which empirical confirmation has not yet (...) been reached, realists will in these contexts be committed to the existence of empirically unconfirmed objects. As a consequence of such commitments, because they lack probabilistic features, the possible empirical confirmation of those objects is epistemically redundant with respect to realism. (shrink)

In this BA dissertation, I deploy examples of non-causal explanations of physical phenomena as evidence against the view that causal models of explanation can fully account for explanatory practices in science. I begin by discussing the problems faced by Hempel’s models and the causal models built to replace them. I then offer three everyday examples of non-causal explanation, citing sticks, pilots and apples. I suggest a general form for such explanations, under which they can be phrased as inductive-statistical arguments incorporating (...) plausible assumptions. I then show the applicability of this form to explanatory practices in thermal physics. I explore the possibility that population genetics provides a similar form of explanation, and offer a novel defence of the statistical interpretation of population genetics proposed by Matthen and Ariew (2002). I close with remarks concerning how, when faced with competing causal and non-causal explanations of the same phenomenon, we can perform an Inference to the Best Explanation. (shrink)

This article presents a challenge that those philosophers who deny the causal interpretation of explanations provided by population genetics might have to address. Indeed, some philosophers, known as statisticalists, claim that the concept of natural selection is statistical in character and cannot be construed in causal terms. On the contrary, other philosophers, known as causalists, argue against the statistical view and support the causal interpretation of natural selection. The problem I am concerned with here arises for the statisticalists because the (...) debate on the nature of natural selection intersects the debate on whether mathematical explanations of empirical facts are genuine scientific explanations. I argue that if the explanations provided by population genetics are regarded by the statisticalists as non-causal explanations of that kind, then statisticalism risks being incompatible with a naturalist stance. The statisticalist faces a dilemma: either she maintains statisticalism but has to renounce naturalism; or she maintains naturalism but has to content herself with an account of the explanations provided by population genetics that she deems unsatisfactory. This challenge is relevant to the statisticalists because many of them see themselves as naturalists. (shrink)

In a series of papers over the past twenty years, and in a new book, Igor Douven has argued that Bayesians are too quick to reject versions of inference to the best explanation that cannot be accommodated within their framework. In this paper, I survey their worries and attempt to answer them using a series of pragmatic and purely epistemic arguments that I take to show that Bayes’ Rule really is the only rational way to respond to your evidence.

According to the no-miracle argument, scientific realism is the only view that does not render the predictive success of scientific theories miraculous. Against the no-miracle argument, selectionists argue that the predictive success of scientific theories is a product of them being subject to a selection process that weeds out predictively unsuccessful theories. Against selectionism, I argue that the selectionist explanation is not an alternative to the realist one. More precisely, I draw on a standard framework in behavioral biology, known as (...) “Tinbergen’s four questions,” and argue that selectionism and realism are aimed at answering different questions and that they are complementary to each other, instead. (shrink)

In this paper, I take a closer look at Hans Reichenbach’s relation to metaphysics and work out some interesting parallels between his account and that of the proponents of inductive metaphysics, a tradition that emerged in the mid- and late 19th century and the early 20th century in Germany. It is in particular Hans Reichenbach’s conception of the relation between the natural sciences and metaphysics, as displayed in his treatment of the question of the existence of the external world, that (...) shows some very interesting similarities with inductive metaphysics. By a comparison with the position of the inductive metaphysician Erich Becher and his handling of the problem of realism, I work out the parallels between Reichenbach’s program and inductive metaphysics. I come to the conclusion that while there are certainly some respects in which Reichenbach’s logical empiricism is closer to the positions of the representatives of the Vienna Circle, it turns out that with regard to his views on metaphysics there is a greater affinity with the program of inductive metaphysics. (shrink)

Non-causal accounts of action explanation have long been criticized for lacking a positive thesis, relying primarily on negative arguments to undercut the standard Causal Theory of Action The Stanford Encyclopedia of Philosophy, 2016). Additionally, it is commonly thought that non-causal accounts fail to provide an answer to Donald Davidson’s challenge for theories of reasons explanations of actions. According to Davidson’s challenge, a plausible non-causal account of reasons explanations must provide a way of connecting an agent’s reasons, not only to what (...) she ought to do, but to what she actually does. That is, such explanations must be truth-apt, not mere rationalizations. My aim in this paper is to show how a non-causal account of action can provide explanations that are truth-apt and genuinely explanatory. To make this argument, I take as a given an account of the practical syllogism discussed by Michael Thompson and Eric Wiland, according to which the practical syllogism is truly practical rather than propositional in nature. Next, I present my primary positive thesis: reasons for actions have explanatory power in virtue of being parts of a structure—the practical syllogism—that contains the action being explained. I then argue that structural action explanations can meet Davidson’s challenge and that they genuinely explain actions. Finally, I conclude by addressing some objections to my argument. (shrink)

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)

Many philosophers have argued that a hypothesis is better confirmed by some data if the hypothesis was not specifically designed to fit the data. ‘Prediction’, they argue, is superior to ‘accommodation’. Others deny that there is any epistemic advantage to prediction, and conclude that prediction and accommodation are epistemically on a par. This paper argues that there is a respect in which accommodation is superior to prediction. Specifically, the information that the data was accommodated rather than predicted suggests that the (...) data is less likely to have been manipulated or fabricated, which in turn increases the likelihood that the hypothesis is correct in light of the data. In some cases, this epistemic advantage of accommodation may even outweigh whatever epistemic advantage there might be to prediction, making accommodation epistemically superior to prediction all things considered. (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)

The main purpose of this paper is to refute the metaphysicians ‘methodological continuation’ argument supporting epistemic realism in metaphysics. This argument aims to show that scientific realists have to accept that metaphysics is as rationally justified as science given that they both employ inference to the best explanation, i.e. that metaphysics and science are methodologically continuous. I argue that the reasons given by scientific realists as to why inference to the best explanation is reliable in science do not constitute a (...) reason to believe that it is reliable in metaphysics. The justification of IBE in science and the justification of IBE in metaphysics are two distinct issues with only superficial similarities, and one cannot rely on one for the other. This becomes especially clear when one analyses the debate about the legitimacy of IBE that has taken place between realists and empiricists. The metaphysician seeking to piggyback on the realist defense of IBE in science by the methodological continuation argument presupposes that the defense is straightforwardly applicable to metaphysics. I will argue that it is, in fact, not. The favoured defenses of IBE in scientific realism make extensive use of empirical considerations, predictive power and inductive evidence, all of which are paradigmatically absent in the metaphysical context. Furthermore, I argue that the metaphysician, even if the realist would concede to the methodological continuation argument, fails to offer any agreed upon conclusions resulting from its application in metaphysics. As a result, the scientific realist is not committed to believing that there is metaphysical knowledge. (shrink)

A good definition of process tracing should highlight what is distinctive about process tracing as a methodology of causal inference. I look at eight criteria that are used to define process tracing in the methodological literature, and I dismiss all eight criteria as unhelpful (some because they are too restrictive, and others because they are vacuous). In place of these criteria, I propose four alternative criteria, and I draw a distinction between process tracing for the ultimate aim of testing a (...) start--end hypothesis versus process tracing as an ultimate end in itself. Although it is clear enough how the former method works, there is still much methodological work to be done in understanding the latter method as a distinctive method of causal inference, I argue. (shrink)

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational achievement. (...) Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning. (shrink)

This chapter presents a typology of the different kinds of inductive inferences we can draw from our evidence, based on the explanatory relationship between evidence and conclusion. Drawing on the literature on graphical models of explanation, I divide inductive inferences into (a) downwards inferences, which proceed from cause to effect, (b) upwards inferences, which proceed from effect to cause, and (c) sideways inferences, which proceed first from effect to cause and then from that cause to an additional effect. I further (...) distinguish between direct and indirect forms of downwards and upwards inferences. I then show how we can subsume canonical forms of inductive inference mentioned in the literature, such as inference to the best explanation, enumerative induction, and analogical inference, under this typology. Along the way, I explore connections with probability and confirmation, epistemic defeat, the relation between abduction and enumerative induction, the compatibility of IBE and Bayesianism, and theories of epistemic justification. (shrink)

The notion of strength has featured prominently in recent debates about abductivism in the epistemology of logic. Following Williamson and Russell, we distinguish between logical and scientific strength and discuss the limits of the characterizations they employ. We then suggest understanding logical strength in terms of interpretability strength and scientific strength as a special case of logical strength. We present applications of the resulting notions to comparisons between logics in the traditional sense and mathematical theories.

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 paper I provide a novel argument for scientific realism. In contrast to most recent defenses of SR, my defense of SR does not rely on the no-miracles argument. Instead, I take a more unconventional approach: I focus on the different kinds of justification available to different individuals in relation to different kinds of propositions. I maintain that this alternative focus shows that most people are warranted in believing many propositions about unobservables. The paper is divided into three main (...) sections. In the first, I rehearse the main moves in the recent debate about SR. In the second, I argue that the discussion in section one enables us to see that most of the arguments in the recent debate about SR mistake their target: instead of being about SR, they are about meta-SR. I argue that what I call the JJ-principle should be rejected and, further, that if the JJ-principle is rejected, then meta-SR may be cleaved from SR. This enables me to advance to a position I call thin realism in the third and final section of the paper. (shrink)

During the first half of the twentieth century, many philosophers of memory opposed the postulation of memory traces based on the claim that a satisfactory account of remembering need not include references to causal processes involved in recollection. However, in 1966, an influential paper by Martin and Deutscher showed that causal claims are indeed necessary for a proper account of remembering. This, however, did not settle the issue, as in 1977 Malcolm argued that even if one were to buy Martin (...) and Deutscher’s argument for causal claims, we still don’t need to postulate the existence of memory traces. This paper reconstructs the dialectic between realists and anti-realists about memory traces, suggesting that ultimately realists’ arguments amount to inferences to the best explanation. I then argue that Malcolm’s anti-realist strategy consists in the suggestion that causal explanations that do not invoke memory traces are at least as good as those that do. But then, Malcolm, I argue that there are a large number of memory phenomena for which explanations that do not postulate the existence of memory traces are definitively worse than explanations that do postulate them. Next, I offer a causal model based on an interventionist framework to illustrate when memory traces can help to explain memory phenomena and proceed to substantiate the model with details coming from extant findings in the neuroscience of memory. (shrink)

Evolutionary scepticism holds that the evolutionary account of the origins of the human cognitive apparatus has sceptical implications for at least some of our beliefs. A common target of evolutionary scepticism is moral realism. Scientific realism, on the other hand, is much less frequently targeted, though the idea that evolutionary theory should make us distrustful of science is by no means absent from the literature. This line of thought has received unduly little attention. I propose to remedy this by advancing (...) what I will call an evolutionary sceptical challenge to scientific realism. I argue that, given standard evolutionary theory, our possession of sound innate metaphysical intuitions would have taken an epistemically problematic ‘lucky accident’. This, as I will show, entails that scientific realism is a self-undermining position. I discuss objections to my argument’s two premises, including ones that appeal to the success of the sciences and to the possibility that sound innate metaphysical intuitions evolved as an evolutionary ‘by-product’. I then draw out an advantage of my argument over a similar one recently put forward by Graber and Golemon. I finish by submitting that scientific realism, given the soundness of my argument, is faced with a new ‘Darwinian Dilemma’, and briefly address the significance of this for the debate between realists and anti-realists in the philosophy of science. (shrink)

Suppose that A explains B. Do A and B need to be true? Provided that we have metaphysical explanation in mind, orthodoxy answers “yes:” metaphysical explanation is factive. This article introduces and defends a non-factive notion of metaphysical explanation. I argue that we need a non-factive notion of explanation in order to make sense of explanationist arguments where we motivate a view by claiming that it offers better explanations than its competitors. After presenting and rejecting some initially plausible rivals, I (...) account for non-factive metaphysical explanation by drawing on existing applications of structural equation models to metaphysical grounding. (shrink)

This paper challenges the appeal to theory virtues in theory choice as well as the appeal to the intellectual and moral virtues of an agent as determining unique choices between empirically equivalent theories. After arguing that theoretical virtues do not determine the choice of one theory at the expense of another theory, I argue that nor does the appeal to intellectual and moral virtues single out one agent, who defends a particular theory, and exclude another agent defending an alternative theory. (...) I analyse Duhem’s concept of good sense and its recent interpretation in terms of virtue epistemology. I argue that the virtue epistemological interpretation does not show how good sense leads to conclusive choices and scientific progress. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (shrink)

The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities are (...) not determined in this way—these are the basic probabilities which determine values for all other probabilities. The substantive question asks how the values of these basic probabilities are determined. I defend an answer to the structural question on which basic probabilities are the probabilities of atomic propositions conditional on potential direct explanations. I defend this against the view, implicit in orthodox mathematical treatments of probability, that basic probabilities are the unconditional probabilities of complete worlds. I then apply my answer to the structural question to clear up common confusions in expositions of Bayesianism and shed light on the “problem of the priors.”. (shrink)

Priority Theory is an increasingly popular view in metaphysics. By seeing metaphysical questions as primarily concerned with what explains what, instead of merely what exists, it promises not only an interesting approach to traditional metaphysical issues but also the resolution of some outstanding disputes. In a recent paper, Louis deRosset argues that Priority Theory isn’t up to the task: Priority Theory is committed to there being explanations that violate a formal constraint on any adequate explanation. This paper critically examines deRosset’s (...) challenge to Priority Theory. We argue that deRosset’s challenge ultimately fails: his proposed constraint on explanation is neither well-motivated nor a general constraint. Nonetheless, lurking behind his criticism is a deep problem for prominent ways of developing Priority Theory, a problem which we develop. (shrink)

The relationship between Peircean abduction and the modern notion of Inference to the Best Explanation is a matter of dispute. Some philosophers, such as Harman :88–95, 1965) and Lipton, claim that abduction and IBE are virtually the same. Others, however, hold that they are quite different :503, 1998; Minnameier in Erkenntnis 60:75–105, 2004) and there is no link between them :419–442, 2009). In this paper, I argue that neither of these views is correct. I show that abduction and IBE have (...) important similarities as well as differences. Moreover, by bringing a historical perspective to the study of the relationship between abduction and IBE—a perspective that is lacking in the literature—I show that their differences can be well understood in terms of two historic developments in the history of philosophy of science: first, Reichenbach’s distinction between the context of discovery and the context of justification—and the consequent jettisoning of the context of discovery from philosophy of science—and second, underdetermination of theory by data. (shrink)

Cognitive Gadgets is a book about the cultural evolution of distinctively human cognitive mechanisms. Responding to commentators with different and broader interests, I argue that intelligent design has been more important in the formation of grist (technologies, practices and ideas) than of mills (cognitive mechanisms), and that embracing genetic accommodation would leave research on the origins of human cognition empirically unconstrained. I also underline the need to assess empirical methods; query the value of theories that merely accommodate existing data; and (...) ask whether acquiring literacy is more laborious than learning to imitate, to talk and to read minds. (shrink)

It is widely supposed that methodological naturalism, understood as a thesis about the methodology of science, is metaphysically neutral, and that this in turn guarantees the value-neutrality of science. In this paper we argue that methodological naturalism is underpinned by certain ontological and epistemological assumptions including evidentialism and the causal closure of the physical, adoption of which necessitates commitment to metaphysical naturalism.

Recently, many have argued that there are certain kinds of abstract mathematical explanations that are noncausal. In particular, the irrelevancy approach suggests that abstracting away irrelevant causal details can leave us with a noncausal explanation. In this paper, I argue that the common example of Renormalization Group explanations of universality used to motivate the irrelevancy approach deserves more critical attention. I argue that the reasons given by those who hold up RG as noncausal do not stand up to critical scrutiny. (...) As a result, the irrelevancy approach and the line between casual and noncausal explanation deserves more scrutiny. (shrink)

This volume is dedicated to Prof. Dag Prawitz and his outstanding contributions to philosophical and mathematical logic. Prawitz's eminent contributions to structural proof theory, or general proof theory, as he calls it, and inference-based meaning theories have been extremely influential in the development of modern proof theory and anti-realistic semantics. In particular, Prawitz is the main author on natural deduction in addition to Gerhard Gentzen, who defined natural deduction in his PhD thesis published in 1934. The book opens with an (...) introductory paper that surveys Prawitz's numerous contributions to proof theory and proof-theoretic semantics and puts his work into a somewhat broader perspective, both historically and systematically. Chapters include either in-depth studies of certain aspects of Dag Prawitz's work or address open research problems that are concerned with core issues in structural proof theory and range from philosophical essays to papers of a mathematical nature. Investigations into the necessity of thought and the theory of grounds and computational justifications as well as an examination of Prawitz's conception of the validity of inferences in the light of three “dogmas of proof-theoretic semantics” are included. More formal papers deal with the constructive behaviour of fragments of classical logic and fragments of the modal logic S4 among other topics. In addition, there are chapters about inversion principles, normalization of proofs, and the notion of proof-theoretic harmony and other areas of a more mathematical persuasion. Dag Prawitz also writes a chapter in which he explains his current views on the epistemic dimension of proofs and addresses the question why some inferences succeed in conferring evidence on their conclusions when applied to premises for which one already possesses evidence. (shrink)

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the Universe or its initial state this becomes a particularly pressing issue. How to assess the probability of the Universe as a whole is empirically ambiguous, since we can examine only part of a single realisation of the system under investigation: at some point, data will (...) run out. We review the basics of applying Bayesian statistical explanation to the Universe as a whole. We argue that a conventional Bayesian approach to model inference generally fails in such circumstances, and cannot resolve, e.g., the so-called 'measure problem' in inflationary cosmology. Implicit and non-empirical valuations inevitably enter model assessment in these cases. This undermines the possibility to perform Bayesian model comparison. One must therefore either stay silent, or pursue a more general form of systematic and rational model assessment. We outline a generalised axiological Bayesian model inference framework, based on mathematical lattices. This extends inference based on empirical data (evidence) to additionally consider the properties of model structure (elegance) and model possibility space (beneficence). We propose this as a natural and theoretically well-motivated framework for introducing an explicit, rational approach to theoretical model prejudice and inference beyond data. (shrink)

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)

Jaegwon Kim’s views on mental causation and the exclusion argument are evaluated systematically. Particular attention is paid to different theories of causation. It is argued that the exclusion argument and its premises do not cohere well with any systematic view of causation.

Reductive intellectualists about knowledge-how hold, contra Ryle, that knowing how to do something is just a kind of propositional knowledge. In a similar vein, traditional reductivists about understanding-why insist, in accordance with a tradition beginning with Aristotle, that the epistemic standing one attains when one understands why something is so is itself just a kind of propositional knowledge—viz., propositional knowledge of causes. A point that has been granted on both sides of these debates is that if these reductive proposals are (...) right, then knowledge-how and understanding-why should be susceptible to the same extent as knowledge-that is to being undermined by epistemic luck. This paper reports experimental results that test these luck-based predictions. Interestingly, these results suggest a striking positive correlation between self-reported philosophical expertise and attributions of knowledge-how, understanding-why and knowledge-that which run contrary to reductive proposals. We contextualize these results by showing how they align very well with a particular kind of overarching non-reductive proposal, one that two of the authors have defended elsewhere according to which knowledge-how and understanding-why, but not knowledge-that, essentially involve cognitive achievement. We conclude by situating the interpretive narrative advanced within contemporary discussions about the role of expertise in philosophical judgment. (shrink)

The metaphysics of representation poses questions such as: in virtue of what does a sentence, picture, or mental state represent that the world is a certain way? In the first instance, I have focused on the semantic properties of language: for example, what is it for a name such as ‘London’ to refer to something? Interpretationism concerning what it is for linguistic expressions to have meaning, says that constitutively, semantic facts are fixed by best semantic theory. As here developed, it (...) promises to give a reductive, universal and non-revisionary account of the nature of linguistic representation. -/- Interpretationism in general, however, is threatened by severe internal tension, due to arguments for radical inscrutability. These contend that, given the interpretationist setting, there can be no fact of the matter what object an individual word refers to: for example, that there is no fact of the matter as to whether “London” refers to London or to Sydney. -/- A series of challenges emerge, forming the basis for this thesis. 1. What sort of properties is the interpretationist trying to reduce, and what kind of reductive story is she offering? 2. How are inscrutability theses best formulated? Are arguments for inscrutability effective in their own terms? What kinds of inscrutability arise? 3. Is endorsing radical inscrutability a stable position? 4. Are there theoretical virtues—such as simplicity—that can be appealed to in discrediting the rival (empirically equivalent) theories that underpin inscrutability arguments? -/- In addressing these questions, I concentrate on diagnosing the source of inscrutability, mapping the space of ways of resisting the arguments for radical inscrutability, and examining the challenges faced in developing a principled account of linguistic content that avoids radical inscrutability. -/- The effect is not to close down the original puzzles, but rather to sharpen them into a set of new and deeper challenges. (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)

In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...) the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I’ll argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I’ll suggest, much of the controversy stems from a failure to properly distinguish the “context of justification” from the “context of pursuit”. Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I’ll show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit. (shrink)

The primary aim of this chapter is to explain the nature of evidential reasoning, the characteristic difficulties encountered, and the tools to address these difficulties. Our focus is on evidential reasoning in criminal cases. There is an extensive scholarly literature on these topics, and it is a secondary aim of the chapter to provide readers the means to find their way in historical and ongoing debates.

I begin by distinguishing four different versions of the argument from evil that start from four different moral premises that in various ways link the existence of God to the absence of suffering. The version of the argument from evil that I defend starts from the premise that if God exists, he would not allow excessive, unnecessary suffering. The argument continues by denying the consequent of this conditional to conclude that God does not exist. I defend the argument against Skeptical (...) Theists who say we are in no position to judge that there is excessive, unnecessary suffering by arguing that this defense has absurd consequences. It allows Young Earthers to construct a parallel argument that concludes that we are in no position to judge that God did not create the earth recently. In the last section I consider whether theists can turn the argument from evil on its head by arguing that God exists. I first criticize Alvin Plantinga’s theory of warrant that one might try to use to argue for God’s existence. I then criticize Richard Swinburne’s Bayesian argument to the same conclusion. I conclude that my version of the argument from evil is a strong argument against the existence of God and that several important responses to it do not defeat it. (shrink)