Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

Recently, a number of epistemologists (notably Feldman [2007], [2009] and White [2005], [2013]) have argued for the rational uniqueness thesis, the principle that any set of evidence permits only one rationally acceptable attitude toward a given proposition. In contrast, this paper argues for extreme rational permissivism, the view that two agents with the same evidence may sometimes arrive at contradictory beliefs rationally. This paper identifies different versions of uniqueness and permissivism that vary in strength and range, argues that evidential peers (...) with different interests need not rationally endorse all the same hypotheses, argues that evidential peers who weigh the theoretic virtues differently can sometimes rationally endorse contradictory conclusions, and finally defends the permissivist appeal to standards against objections in the works of Feldman and White. (shrink)

Some adaptationist explanations are regarded as maximally solid and others fanciful just-so stories. Just-so stories are explanations based on very little evidence. Lack of evidence leads to circular-sounding reasoning: “this trait was shaped by selection in unseen ancestral populations and this selection must have occurred because the trait is present.” Well-supported adaptationist explanations include evidence that is not only abundant but selected from comparative, populational, and optimality perspectives, the three adaptationist subdisciplines. Each subdiscipline obtains its broad relevance in evolutionary biology (...) via assumptions that can only be tested with the methods of the other subdisciplines. However, even in the best-supported explanations, assumptions regarding variation, heritability, and fitness in unseen ancestral populations are always present. These assumptions are accepted given how well they would explain the data if they were true. This means that some degree of “circularity” is present in all evolutionary explanations. Evolutionary explanation corresponds not to a deductive structure, as biologists usually assert, but instead to ones such as abduction or induction. With these structures in mind, we show the way to a healthier view of “circularity” in evolutionary biology, and why integration across the comparative, populational, and optimality approaches is necessary. (shrink)

Abduction is a widely used but deductively invalid type of reasoning. In this paper I will develop a tool for the assessment of argumentation based on abduction that can be used to analyse and evaluate the type of argumentation as it occurs in institutionalized contexts like science and medical diagnosis. I will summarize the most important definitions of abduction and propose an argumentative pattern on the basis of a critical examination of two extant dialectical accounts of the argument scheme involved.

This paper continues a recent exchange in this journal concerning explanationist accounts of epistemic justification. In the first paper in this exchange, Byerly argues that explanationist views judge that certain beliefs about the future are unjustified when in fact they are justified. In the second paper, McCain defends a version of explanationism which he argues escapes Byerly’s criticism. Here we contribute to this exchange in two ways. In the first section, we argue that McCain’s defense of explanationism against Byerly’s objection (...) is unsuccessful. Then, in the second section, we develop an independent objection to explanationism from a different direction. If our arguments in each section are sound, then not only do explanationist accounts of epistemic justification judge beliefs that are justified to be unjustified, but they judge beliefs that are unjustified to be justified. Explanationism faces problems on both sides. (shrink)

Scientific theories are hard to find, and once scientists have found a theory, H, they often believe that there are not many distinct alternatives to H. But is this belief justified? What should scientists believe about the number of alternatives to H, and how should they change these beliefs in the light of new evidence? These are some of the questions that we will address in this article. We also ask under which conditions failure to find an alternative to H (...) confirms the theory in question. This kind of reasoning is frequently used in science and therefore deserves a careful philosophical analysis. 1 Introduction2 The Conceptual Framework3 The No Alternatives Argument4 Discussion I: A Quantitative Analysis of the No Alternatives Argument5 Discussion II: The Number of Alternatives and the Problem of Underdetermination6 ConclusionsAppendix AAppendix B. (shrink)

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is provided, which sheds light on explanatory (...) unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

In this paper, I argue that van Fraassen's "bad lot objection" against Inference to the Best Explanation [IBE] severely misses its mark. First, I show that the objection holds no special relevance to IBE; if the bad lot objection poses a serious problem for IBE, then it poses a serious problem for any inference form whatever. Second, I argue that, thankfully, it does not pose a serious threat to any inference form. Rather, the objection misguidedly blames a form of inference (...) for not achieving what it never set out to achieve in the first place. (shrink)

I focus on a key argument for global external world scepticism resting on the underdetermination thesis: the argument according to which we cannot know any proposition about our physical environment because sense evidence for it equally justifies some sceptical alternative (e.g. the Cartesian demon conjecture). I contend that the underdetermination argument can go through only if the controversial thesis that conceivability is per se a source of evidence for metaphysical possibility is true. I also suggest a reason to doubt that (...) conceivability is per se a source of evidence for metaphysical possibility, and thus to doubt the underdetermination argument. (shrink)

According to Jim Pryor’s dogmatism, when you have an experience with content p, you often have prima facie justification for believing p that doesn’t rest on your independent justification for believing any proposition. Although dogmatism has an intuitive appeal and seems to have an antisceptical bite, it has been targeted by various objections. This paper principally aims to answer the objections by Roger White according to which dogmatism is inconsistent with the Bayesian account of how evidence affects our rational credences. (...) If this were true, the rational acceptability of dogmatism would be seriously questionable. I respond that these objections don’t get off the ground because they assume that our experiences and our introspective beliefs that we have experiences have the same evidential force, whereas the dogmatist is uncommitted to this assumption. I also consider the question whether dogmatism has an antisceptical bite. I suggest that the answer turns on whether or not the Bayesian can determine the priors of hypotheses and conjectures on the grounds of their extra-empirical virtues. If the Bayesian can do so, the thesis that dogmatism has an antisceptical bite is probably false. (shrink)

This article generalizes the explanationist account of inference to the best explanation. It draws a clear distinction between IBE and abduction and presents abduction as the first step of IBE. The second step amounts to the evaluation of explanatory power, which consist in the degree of explanatory virtues that a hypothesis exhibits. Moreover, even though coherence is the most often cited explanatory virtue, on pain of circularity, it should not be treated as one of the explanatory virtues. Rather, coherence should (...) be equated with explanatory power and considered to be derivable from the other explanatory virtues: unification, explanatory depth and simplicity. (shrink)

This article argues that the credibility of both theoretical and empirical models in economics is best understood through their connection with the empirical aspects of the real world. The discussion herein demonstrates that the similarity between the model and the real world is not enough to justify a theoretical model’s explanatory power. The best way to secure the model’s credibility is to prove the existence of representation theorems.

In this article, I seek to assess the extent to which Theism, the claim that there is a God, can provide a true fundamental explanation for the instantiation of the grounding relation that connects the various entities within the layered structure of reality. More precisely, I seek to utilise the explanatory framework of Richard Swinburne within a specific metaphysical context, a ground-theoretic context, which will enable me to develop a true fundamental explanation for the existence of grounding. And thus, given (...) the truth of this type of explanation, we will have a further reason to believe in the existence of God. (shrink)

In this article, I seek to assess the extent to which Theism, the claim that there is a God, can provide a true fundamental explanation for the existence of the infinite plurality of concrete and abstract possible worlds, posited by David K. Lewis and Alvin Plantinga. This assessment will be carried out within the (modified) explanatory framework of Richard Swinburne, which will lead to the conclusion that the existence of God provides a true fundamental explanation for these specific entities. And (...) thus, given the truth of this type of explanation, we have another good abductive argument for God’s existence and grounds for affirming a weaker form of the principle of methodological naturalism in our metaphysical theorising. (shrink)

In this paper, we set out to investigate the following question: if science relies heavily on induction, does philosophy of science rely heavily on induction as well? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database (n = 14,199) in order to answer this question empirically. If philosophy of science relies heavily on induction, just as science supposedly does, then we would expect to find significantly more inductive arguments than (...) deductive arguments and abductive arguments in the published works of philosophers of science. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we search through our corpus to find patterns of argumentation. Overall, the results of our study suggest that philosophers of science do rely on inductive inference. But induction may not be as foundational to philosophy of science as it is thought to be for science, given that philosophers of science make significantly more deductive arguments than inductive arguments. Interestingly, our results also suggest that philosophers of science do not rely on abductive arguments all that much, even though philosophers of science consider abduction to be a cornerstone of scientific methodology. (shrink)

Do the hard problem of consciousness and the simulation argument potentially resolve each other? Here we will argue for four possible views: that consciousness may be possible only (a) outside of, (b) inside and/or outside of, (c) inside of, or (d) interfacing with simulations. The first two of these views have been developed at length by David Chalmers and are used as jumping off points to introduce and develop the latter two views here. If any one of these views could (...) be proven true, it would simultaneously both support a kind of account of properties of consciousness and also provide a kind of sign as to whether or not we are indeed living in the kind of immersive computer simulation that Nick Bostrom hypothesizes about. However, given that none of these views are proven true but all are plausible, these considerations should tend to neutralize our credence that we are either simulated or not simulated, by themselves giving us no sign one way or the other. (shrink)

What is an inference and when is an inference deductive rather than inductive, abductive, etc. The goal of this paper is precisely to determine what is that we, humans, do when we engage in deduction, i.e., whether there is something that satisfies both our pre-theoretical intuitions and theoretical presuppositions about deduction, as a cognitive process. The paper is structured in two parts: the first one deals with the issue of what is an inference. There, I will defend the hypothesis that (...) an inference is a causal process where an initial cognitive state causes another in such a way that the causal translation depends essentially on the content of the involved states. In other words, in an inference, a mental state A causes another B, partially because they have the content they have. Based on the conclusion from the first part, I will develop an account of deductive inference in the second part of the article. In order to achieve this, I will start by setting the stage and developing four constraints that an adequate account of deductive inference ought to satisfy. Then, I will present six different hypotheses that one might propose to characterize inferences of this kind. I have divided the proposals in two groups, the first one – which I will call the “logical proposals” – assume that whether an inference is a deduction or not depends exclusively on the content of the mental states involved in the inference, while the second – which I will call the “cognitive proposals” – reject the aforementioned assumption and instead recognize that extra cognitive information is required to determine whether an inference is a deduction or not. I will evaluate each proposal in turn, according to whether they satisfy the constraints introduced at the beginning of this second part. As a result of such evaluation, I will conclude that only one of the cognitive proposals actually satisfies the four constraints and therefore should be considered to give an adequate characterization of deductive inference. (shrink)

While the epistemic significance of disagreement has been a popular topic in epistemology for at least a decade, little attention has been paid to logical disagreement. This monograph is meant as a remedy. The text starts with an extensive literature review of the epistemology of (peer) disagreement and sets the stage for an epistemological study of logical disagreement. The guiding thread for the rest of the work is then three distinct readings of the ambiguous term ‘logical disagreement’. Chapters 1 and (...) 2 focus on the Ad Hoc Reading according to which logical disagreements occur when two subjects take incompatible doxastic attitudes toward a specific proposition in or about logic. Chapter 2 presents a new counterexample to the widely discussed Uniqueness Thesis. Chapters 3 and 4 focus on the Theory Choice Reading of ‘logical disagreement’. According to this interpretation, logical disagreements occur at the level of entire logical theories rather than individual entailment-claims. Chapter 4 concerns a key question from the philosophy of logic, viz., how we have epistemic justification for claims about logical consequence. In Chapters 5 and 6 we turn to the Akrasia Reading. On this reading, logical disagreements occur when there is a mismatch between the deductive strength of one’s background logic and the logical theory one prefers (officially). Chapter 6 introduces logical akrasia by analogy to epistemic akrasia and presents a novel dilemma. Chapter 7 revisits the epistemology of peer disagreement and argues that the epistemic significance of central principles from the literature are at best deflated in the context of logical disagreement. The chapter also develops a simple formal model of deep disagreement in Default Logic, relating this to our general discussion of logical disagreement. The monograph ends in an epilogue with some reflections on the potential epistemic significance of convergence in logical theorizing. (shrink)

A key question in the philosophy of logic is how we have epistemic justification for claims about logical entailment (assuming we have such justification at all). Justification holism asserts that claims of logical entailment can only be justified in the context of an entire logical theory, e.g., classical, intuitionistic, paraconsistent, paracomplete etc. According to holism, claims of logical entailment cannot be atomistically justified as isolated statements, independently of theory choice. At present there is a developing interest in—and endorsement of—justification holism (...) due to the revival of an abductivist approach to the epistemology of logic. This paper presents an argument against holism by establishing a foundational entailment-sentence of deduction which is justified independently of theory choice and outside the context of a whole logical theory. (shrink)

The purpose of this introduction is to give a rough overview of the discussion of the formalization of arguments, focusing on deductive arguments. The discussion is structured around four important junctions: i) the notion of support, which captures the relation between the conclusion and premises of an argument, ii) the choice of a formal language into which the argument is translated in order to make it amenable to evaluation via formal methods, iii) the question of quality criteria for such formalizations, (...) and finally iv) the choice of the underlying logic. This introductory discussion is supplemented by a brief description of the genesis of the special issue, acknowledgements, and summaries of each article. (shrink)

I argue that when we use ‘probability’ language in epistemic contexts—e.g., when we ask how probable some hypothesis is, given the evidence available to us—we are talking about degrees of support, rather than degrees of belief. The epistemic probability of A given B is the mind-independent degree to which B supports A, not the degree to which someone with B as their evidence believes A, or the degree to which someone would or should believe A if they had B as (...) their evidence. My central argument is that the degree-of-support interpretation lets us better model good reasoning in certain cases involving old evidence. Degree-of-belief interpretations make the wrong predictions not only about whether old evidence confirms new hypotheses, but about the values of the probabilities that enter into Bayes’ Theorem when we calculate the probability of hypotheses conditional on old evidence and new background information. (shrink)

A Persistent Interlocutor (PI) is someone who, in argumentative contexts, does not cease to question her opponent’s premises. The epistemic relevance of the PI has been debated throughout the history of philosophy. Pyrrhonians famously claim that our inability to dialectically vindicate our claims against a PI implies scepticism. Adam Leite disagrees (2005). Michael Resorla argues that the debate is based on a false premise (2009). In this paper, I argue that these views all fail to accurately account for the epistemic (...) relevance of the PI. I then briefly present an account that aims to do better in this regard, based on the modal notion of safety. On the account proposed, the PI does not violate epistemic or dialectical norms. Rather, her behaviour tends to be epistemically perverse in the sense that it wastes cognitive resources. Perhaps surprisingly, this defect turns out not to be unique to the PI. (shrink)

The inaugural title in the new, Open Access series BSPS Open, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. The fundamental burden of a theory of inductive inference is to determine which are the good inductive inferences or relations of inductive support and why it is that they are so. The traditional approach is modeled on that taken in accounts of deductive inference. It seeks universally applicable schemas or rules or a single (...) formal device, such as the probability calculus. After millennia of halting efforts, none of these approaches has been unequivocally successful and debates between approaches persist. The Material Theory of Induction identifies the source of these enduring problems in the assumption taken at the outset: that inductive inference can be accommodated by a single formal account with universal applicability. Instead, it argues that that there is no single, universally applicable formal account. Rather, each domain has an inductive logic native to it. Which that is, and its extent, is determined by the facts prevailing in that domain. Paying close attention to how inductive inference is conducted in science and copiously illustrated with real-world examples, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. (shrink)

Abduction is considered the most powerful, but also the most controversially discussed type of inference. Based on an analysis of Peirce’s retroduction, Lipton’s Inference to the Best Explanation and other theories, a new theory of abduction is proposed. It considers abduction not as intrinsically explanatory but as intrinsically conditional: for a given fact, abduction allows one to infer a fact that implies it. There are three types of abduction: Selective abduction selects an already known conditional whose consequent is the given (...) fact and infers that its antecedent is true. Conditional-creative abduction creates a new conditional in which the given fact is the consequent and a defined fact is the antecedent that implies the given fact. Propositional-conditional-creative abduction assumes that the given fact is implied by a hitherto undefined fact and thus creates a new conditional with a new proposition as antecedent. The execution of abductive inferences is specified by theory-specific patterns. Each pattern consists of a set of rules for both generating and justifying abductive conclusions and covers the complete inference process. Consequently, abductive inferences can be formalised iff the whole pattern can be formalised. The empirical consistency of the proposed theory is demonstrated by a case study of Semmelweis' research on puerperal fever. (shrink)

Charles S. Peirce luokitteli 1865 päättelyn lajit deduktioon, induktioon ja hypoteesiin, joista viimeksi mainittua hän luonnehti päättelynä vaikutuksista syihin tai päättelynä selitykseen. Hypoteesi on Peircelle induktion ohella tietoa laajentava päätelmä. 1890-luvun lopun kirjoituksissaan hän alkoi kutsua hypoteettista päättelyä uusilla nimillä ”retroduktio” ja ”abduktio”. Tässä vaiheessa Peirce kuvasi abduktiota tieteellisen päättelyn ensimmäisenä askeleena, mahdollisten arvausten esittämisenä, jonka tulokset on asetettava induktion kautta testeihin. Hänen tunnetuin kaavionsa abduktion loogiselle muodolle on vuodelta 1903: The surprising fact C is observed; But if A were (...) true, C would be a matter of course. Hence, there is reason to think that A is true. Toisin sanoen abduktio päättelee yllättävästä tosiseikasta hypoteettiseen teoriaan, joka selittäisi tämän faktan. Peircen ajatukset tulivat laajemmin tunnetuiksi, kun kuusiosainen Collected Papers ilmestyi 1931-35. Maailmansodan jälkeen hänen ehdotuksiaan on tulkittu kolmessa suunnassa. Hansonin mukaan abduktio on keksimisen logiikkaa. Laudanin mukaan abduktiossa on kyse ohjeesta työskennellä kiinnostavan hypoteesin parissa. Harmanin mukaan abduktio on päättelyä parhaaseen selitykseen. Monet loogikot, tekoälyn tutkijat ja tieteenfilosofit käyttävät termiä ”abduktio” suoraviivaisesti IBE:n synonyyminä, kun taas varovaisemman kannan ottavat mm. Aliseda, Magnani ja Douven. Toisaalta tätä rinnastusta on eri syistä pidetty harhaanjohtavana abduktion todellisen luonteen ja tehtävän perusteella. Myös monet Peirce-tutkijat ovat ottaneet intohimoisesti kantaa asiaan vedoten mestarin monitulkintaisiin kirjoituksiin. Esimerkiksi Minnamaier esittää, että abduktion samaistaminen IBE:n kanssa hämärtäisi Peircen erottelua induktion ja abduktion välillä. Campos argumentoi, että abduktio tulisi rajata selittävien hypoteesien generoimiseen, joten valikointi hypoteesien välillä ei kuulu sen tehtäviin. Gaultierin mukaan skeeman johtopäätös ei ole suositus testata A:n totuutta, vaan selvittää, onko A todellakin mahdollinen selitys C:lle. Sen sijaan Nyrupin mukaan jättää avoimeksi, tukeeko onnistunut selitys hypoteesin totuutta, joten abduktiossa on kyse hypoteesin työstämisestä. Peircen kirjoituksista puolen vuosisadan aikana kuitenkin löytyy aineksia kaikille kolmelle abduktion päätulkinnalle. Abduktio on ainoa menetelmä uusien ideoiden generoimiseksi. Abduktio auttaa tunnistamaan testaamisen arvioisia hypoteeseja. Joissakin tapauksissa, kuten havainnoissa ja historiallisissa päätelmissä, abduktio on ”pakottavaa” tai ”täysin varmaa”, joten sillä voi olla tekemistä myös hypoteesien oikeuttamisen kanssa. Vaikka Peirce päätyi esittämään, ettei abduktiivisiin päätelmiin liity mitään todennäköisyyksiä, hän kuitenkin myöhäisissäkin töissään antoi abduktiolle selkeän loogisen muodon. Lisäksi abduktion ja IBE:n yhteyttä puolustaa käsikirjoitus ”The Logic of Drawing History from Ancient Documents”, jossa Peirce antaa kriteerejä ”abduktiolle eli hypoteesien valinnan prosessille”. Näitä kriteerejä ovat selitysvoima, testattavuus, varovaisuus, laajuus ja yksinkertaisuus. Samantapaisia metodologisia sääntöjä ovat muotoilleet ne tutkijat, jotka ovat kehitelleet eteenpäin IBE:n muotoja. Vastaus otsikon kysymykseen on siis ”kyllä ja ei”. Vaikka Peirce keksi termin ”abduktio”, hänellä ei ole loputonta yksinoikeutta määrätä sen käytöstä. Hän ajatuksensa ovat inspiroivia tavalla, joka voi johtaa abduktion tutkimisessa erilaisiin suuntiin. Näitä linjoja on tarpeetonta oikeaoppisesti pitää toisilleen vastakkaisina. Keksimisen logiikka on kiehtova aihe, mutta samalla tavoin on aihetta analysoida sitä, miten keksittyjen selityshypoteesien paremmuutta voidaan vertailla ja millaisilla ehdoilla voisimme olla oikeutettuja hyväksymään parhaan toistaiseksi löydetyistä selityksistä. Kaikki nämä loogis-metodologiset tutkimuslinjat tekevät omalla tavallaan oikeutta Peircen filosofian suurille oivalluksille. (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 argue that molecules may not have structure in isolation. I support this by investigating how quantum models identify structure for isolated molecules. Specifically, I distinguish between two sets of models: those that identify structure in isolation and those that do not. The former identify structure because they presuppose structural information about the target system via the Born- Oppenheimer approximation. However, it is an idealisation to assume structure in isolation because there is no empirical evidence of this. In fact, whenever (...) structure is empirically examined it is always partially determined by factors that are absent in isolation. Together with the growing empirical evidence that isolated molecules behave in non-classical ways, this shows that the quantum models that do not identify structure are more faithful representations of isolated molecules. (shrink)

European Journal of Philosophy, Volume 29, Issue 4, Page 864-886, December 2021.

It is usually accepted that deductions are non-informative and monotonic, inductions are informative and nonmonotonic, abductions create hypotheses but are epistemically irrelevant, and both deductions and inductions can’t provide new insights. In this article, I attempt to provide a more cohesive view of the subject with the following hypotheses: (1) the paradigmatic examples of deductions, such as modus ponens and hypothetical syllogism, are not inferential forms, but coherence requirements for inferences; (2) since any reasoner aims to be coherent, any inference (...) must be deductive; (3) a coherent inference is an intuitive process where the premises should be taken as sufficient evidence for the conclusion, which on its turn should be viewed as necessary evidence for the premises in some modal range; (4) inductions, properly understood, are abductions, but there are no abductions beyond the fact that in any inference the conclusion should be regarded as necessary evidence for the premises; (5) monotonicity is not only compatible with the retraction of past inferences given new information, but it is a requirement for it; (6) this explanation of inferences holds true for discovery processes, predictions and trivial inferences. (shrink)

Despite their centrality to the scientific enterprise, both the nature of scientific variables and their relation to inductive inference remain obscure. I suggest that scientific variables should be viewed as equivalence classes of sets of physical states mapped to representations (often real numbers) in a structure preserving fashion, and argue that most scientific variables introduced to expand the degrees of freedom in terms of which we describe the world can be seen as products of an algorithmic inductive inference first identified (...) by William W. Rozeboom. This inference algorithm depends upon a notion of natural kind previously left unexplicated. By appealing to dynamical kinds—equivalence classes of causal system characterized by the interventions which commute with their time evolution—to fill this gap, we attain a complete algorithm. I demonstrate the efficacy of this algorithm in a series of experiments involving the percolation of water through granular soils that result in the induction of three novel variables. Finally, I argue that variables obtained through this sort of inductive inference are guaranteed to satisfy a variety of norms that in turn suit them for use in further scientific inferences. (shrink)

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)

In their recent article, Graber and Golemon (_Sophia_ 1–18, 2019 ) argue that any attempted evolutionary debunking of naturalism faces a dilemma. First, in order to be evolutionarily plausible, the skeptical implications must not be too broad. Second, in order to constitute a genuine challenge to scientific realism, the skeptical implications must not be too narrow. Graber and Golemon further develop an evolutionary debunking argument that avoids both horns of this dilemma. De Ray (_Erkenntnis_ 1–21, 2020 ) criticizes Graber and (...) Golemon’s debunking argument then develops his own, competing debunking argument. We first respond to de Ray’s criticisms by showing how Graber and Golemon’s argument can be extended so as to avoid de Ray’s critique. We then show that de Ray’s argument debunking argument is impaled by both horns of Graber and Golemon’s dilemma. The ultimate result will be both a better understanding of the desiderata and the argumentative contours of a successful evolutionary debunking argument. (shrink)

According to a widely shared generic conception of inferential justification—‘the standard conception’—an agent is inferentially justified in believing that p only if she has antecedently justified beliefs in all the non-redundant premises of a good argument for p. This conception tends to serve as the starting-point in contemporary debates about the nature and scope of inferential justification: as neutral common ground between various competing, more specific, conceptions. But it’s a deeply problematic starting-point. This paper explores three questions that haven’t been (...) given the attention they deserve, that complicate the application of the standard conception to cases, and that reveal it to be underspecified at the core—in ways that aren’t resolved but inherited by more specific (extant) versions of it. The goal isn’t to answer the questions, but to articulate them, explain what turns on them, and invite a critical re-examination of the standard conception. (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.

In this paper, I discuss the ways in which epistemic anxiety promotes well-being, specifically by examining the positive contributions that feelings of epistemic anxiety make toward intellectually virtuous inquiry. While the prospects for connecting the concept of epistemic anxiety to the two most prominent accounts of intellectual virtue, i.e., “virtue-reliabilism” and “virtue-responsibilism”, are promising, I primarily focus on whether the capacity for epistemic anxiety counts as an intellectual virtue in the reliabilist sense. As I argue, there is a close yet (...) unexplored connection between feelings of epistemic anxiety and the form of inference commonly known as “Inference to the Best Explanation” (IBE). Specifically, I argue that both the recognition that some fact requires an explanation—a necessary first step in applying IBE—and the subsequent motivation to employ IBE are typically facilitated by feelings of epistemic anxiety. So, provided IBE is truth-conducive the capacity for epistemic anxiety should count as an intellectual virtue in the reliabilist sense. After outlining my main argument, I address the challenge that the capacity for epistemic anxiety has the potential to be misleading. To respond to this challenge, I discuss how our recognition that a fact requires an explanation must in part be a species of practical knowledge, rather than theoretical knowledge. For the agent to skillfully distinguish between facts that require an explanation and facts that do not, she must develop the virtuous disposition to feel the appropriate amount of epistemic anxiety. Despite the many negative aspects associated with anxiety, as I conclude, being disposed to feel the appropriate amount of epistemic anxiety is ultimately good for us. (shrink)

The topic of fake news has received increased attention from philosophers since the term became a favorite of politicians (Habgood-Coote 2016; Dentith 2016). Notably missing from the conversation, however, is a discussion of fake news and conspiracy theory media as a market. This paper will take as its starting point the account of noxious markets put forward by Debra Satz (2010), and will argue that there is a pro tanto moral reason to restrict the market for fake news. Specifically, we (...) begin with Satz’s argument that restricting a market may be required when i) that market inhibits citizens from being able to stand in an equal relationship with one another, and ii) this problem cannot be solved without such direct restrictions. Our own argument then proceeds in three parts: first, we argue that the market for fake news fits Satz’s description of a noxious market; second, we argue against explanations of the proliferation of fake news that are couched in terms of “epistemic vice”, and likewise argue against prescribing critical thinking education as a solution to the problem; finally, we conclude that, in the absence of other solutions to mitigate the noxious effects of the fake news market, we have a pro tanto moral reason to impose restrictions on this market. At the end of the paper, we consider one proposal to regulate the fake news market, which involves making social media outlets potentially liable in civil court for damages caused by the fake news hosted on their websites. (shrink)

In this article I elaborate a scientifically based moral realism that I call affordance moral realism, and I offer a promissory note that affordance moral realism is the best current explanation of morality. Affordance moral realism maintains that morality is constituted by the interaction of moral agents and moral affordances. The latter are the natural and social environments in which moral agents’ activities take place and contain the objects of moral agents’ activities whose actualizations are the manifestation of substantive moral (...) goods. In making this argument, I take a scientific naturalistic approach that includes both the natural and social sciences, aiming to make my account both methodologically and substantively naturalistic. On the subject side of my affordance view, I offer a scientific account of moral agency, one based on an extension of social cognitive theories of agency to the realm of morality. And I argue that affordance moral realism explains the nature of moral agency, its acquisition, maintenance, and successful performance. To explain its origin and maintenance, I make use of a general theory of selection that embraces biological, social, cultural, and intentional selection. On the object side, I offer a theory of moral affordances and their actualizations, employing the findings and theories of moral developmental psychology and moral psychology to understand their actualizations through the successful operations of moral agents. I conclude that a scientifically based naturalistic affordance moral realism promises to provide the best current account of morality. It is not only affordable; it’s a bargain. (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)

To demarcate the limits of experimental knowledge, we probe the limits of what might be called an experiment. By appeal to examples of scientific practice from astrophysics and analogue gravity, we demonstrate that the reliability of knowledge regarding certain phenomena gained from an experiment is not circumscribed by the manipulability or accessibility of the target phenomena. Rather, the limits of experimental knowledge are set by the extent to which strategies for what we call ‘inductive triangulation’ are available: that is, the (...) validation of the mode of inductive reasoning involved in the source-target inference via appeal to one or more distinct and independent modes of inductive reasoning. When such strategies are able to partially mitigate reasonable doubt, we can take a theory regarding the phenomena to be well supported by experiment. When such strategies are able to fully mitigate reasonable doubt, we can take a theory regarding the phenomena to be established by experiment. There are good reasons to expect the next generation of analogue experiments to provide genuine knowledge of unmanipulable and inaccessible phenomena such that the relevant theories can be understood as well supported. This article is part of a discussion meeting issue ‘The next generation of analogue gravity experiments’. (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)

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)

In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic assault (...) on superstition that it is sometimes portrayed to be. Then, I offer an extended analysis of the second of the main arguments against divination given by Marcus. Inspired by Marcus’ second main argument, I formulate, explicate, and defend a substantive principle of scientific methodology that I call the “Ciceronian Causal-Nomological Requirement” (CCR). Roughly, this principle states that causal knowledge is essential for relying on correlations in predictive inference. Although I go on to argue that Marcus’ application of the CCR in his debate with Quintus is dialectically inadequate, I conclude that De Divinatione deserves its place in Cicero’s philosophical corpus, and that ultimately, its significance for the history and philosophy of science ought to be recognized. (shrink)

It is often argued that while biases routinely influence the generation of scientific theories, a subsequent rational evaluation of such theories will ensure that biases do not affect which theories are ultimately accepted. Against this line of thought, this paper shows that the existence of certain kinds of biases at the generation-stage implies the existence of biases at the evaluation-stage. The key argumentative move is to recognize that a scientist who comes up with a new theory about some phenomena has (...) thereby gained an unusual type of evidence, viz. information about the space of theories that could be true of the phenomena. It follows that if there is bias in the generation of scientific theories in a given domain, then the rational evaluation of theories with reference to the total evidence in that domain will also be biased. (shrink)

Here, I focus on deviations of intent, from that expressed by the standard or ordinary use of language, in instances where abductive reasoning plays a necessary role. In such cases, speakers usually utter some “mysterious” words based on the assumed abductive capability of their interlocutors. In order to cause the desired effect in the audience, the speaker relies on the hearer’s knowledge of the relevant common dialogue framework and thus uses the utterance as an abductive trigger. For purposes of explanation, (...) I present a curious kind of fallacy: ironic fallacy. (shrink)

In this critical notice, I focus my attention on the chapters that deal with the explanationist response to skepticism.

We argue in Roche and Sober (2013) that explanatoriness is evidentially irrelevant in that Pr(H | O&EXPL) = Pr(H | O), where H is a hypothesis, O is an observation, and EXPL is the proposition that if H and O were true, then H would explain O. This is a “screening-off” thesis. Here we clarify that thesis, reply to criticisms advanced by Lange (2017), consider alternative formulations of Inference to the Best Explanation, discuss a strengthened screening-off thesis, and consider how (...) it bears on the claim that unification is evidentially relevant. (shrink)