According to the evolutionary sceptic, the fact that our cognitive faculties evolved radically undermines their reliability. A number of evolutionary epistemologists have sought to refute this kind of scepticism. This paper accepts the success of these attempts, yet argues that refuting the evolutionary sceptic is not enough to put any particular domain of beliefs – notably scientific beliefs, which include belief in Darwinian evolution – on a firm footing. The paper thus sets out to contribute to this positive justificatory project, (...) underdeveloped in the literature. In contrast to a ‘wholesale’ approach, attempting to secure justification for all of our beliefs on the grounds that our belief-forming mechanisms evolved to track truth, we propose a ‘piecemeal’ approach of assessing the reliability of particular belief-forming mechanisms in particular domains. This stands in contrast to the more familiar attempt to transfer warrant obtained for one domain to another by showing how one is somehow an extension of the other. We offer a naturalist reply to the charge of circularity by appealing to reliabilist work on the problem of induction, notably Peter Lipton's distinction between self-certifying and non-self-certifying inductive arguments. We show how, for scientific beliefs, a non-self-certifying argument might be made for the reliability of our cognitive faculties in that domain. We call this strategy Humean Bootstrapping. (shrink)

Collin Howson (2000) challenges van Cleve’s reliabilist defense of induction (1984) based on an adaptation of Goodman Paradox (or new riddle of induction). I will try to show that Howson’s argument does not succeed once it is self-defeating. Nevertheless, I point out another way which Howson could have employed the new riddle to undermine the reliabilist defense.

According to the "confrontation model," integrated history and philosophy of science operates like an empirical science. It tests philosophical accounts of science against historical case studies much like other sciences test theory against data. However, the confrontation model's critics object that historical facts can neither support generalizations nor genuinely test philosophical theories. Here I argue that most of the model's defects trace to its usual framing in terms of two problematic accounts of empirical inference: the hypothetico-deductive method and enumerative induction. (...) This framing can be taken to suggest an unprofitable one-off confrontation between particular historical facts and general philosophical theories. I outline more recent accounts of empirical inquiry, which describe an iterative back-and-forth movement between concrete empirical exemplars to their abstract descriptions. Reframed along similar lines, the confrontation model continues to offer both conceptual insight and practical guidance for a naturalized philosophy of science. (shrink)

The global pessimistic meta-induction argues from the falsity of scientific theories accepted in the past to the likely falsity of currently accepted scientific theories. I contend that this argument commits a statistical error previously unmentioned in the literature and is self-undermining. I then compare the global pessimistic meta-induction to a local pessimistic meta-induction based on recent negative assessments of the reliability of medical research. If there is any future in drawing pessimistic conclusions from the history of science, it lies in (...) local meta-inductions, but these meta-inductions will not result in global distrust of the results of science. (shrink)

In this paper, I consider the pessimistic induction construed as a deductive argument (specifically, reductio ad absurdum) and as an inductive argument (specifically, inductive generalization). I argue that both formulations of the pessimistic induction are fallacious. I also consider another possible interpretation of the pessimistic induction, namely, as pointing to counterexamples to the scientific realist’s thesis that success is a reliable mark of (approximate) truth. I argue that this interpretation of the pessimistic induction fails, too. If this is correct, then (...) the pessimistic induction is an utter failure that should be abandoned by scientific anti-realists. (shrink)

In this article, through a critical examination of K. Brad Wray's version of the argument from underconsideration against scientific realism, I articulate a modest version of scientific realism. This modest realist position, which I call ‘relative realism’, preserves the scientific realist's optimism about science's ability to get closer to the truth while, at the same time, taking on board the antirealist's premise that theory evaluation is comparative, and thus that there are no good reasons to think that science's best theories (...) are close to the truth. (shrink)

Hume has traditionally been understood as an inductive sceptic with positivist tendencies, reducing causation to regular succession and anticipating the modern distinctions between analytic and synthetic, deduction and induction. The dominant fashion in recent Hume scholarship is to reject all this, replacing the ‘Old Hume’ with various New alternatives. Here I aim to counter four of these revisionist readings, presenting instead a broadly traditional interpretation but with important nuances, based especially on Hume’s later works. He asked that we should treat (...) these— notably the first Enquiry—as his authoritative philosophical statements, and with good reason. (shrink)

Kyle Stanford has recently claimed to offer a new challenge to scientific realism. Taking his inspiration from the familiar Pessimistic Induction (PI), Stanford proposes a New Induction (NI). Contra Anjan Chakravartty’s suggestion that the NI is a ‘red herring’, I argue that it reveals something deep and important about science. The Problem of Unconceived Alternatives, which lies at the heart of the NI, yields a richer anti-realism than the PI. It explains why science falls short when it falls short, and (...) so it might figure in the most coherent account of scientific practice. However, this best account will be antirealist in some respects and about some theories. It will not be a sweeping antirealism about all or most of science. (shrink)

Philosophers have nothing to lose, and much to gain, by paying close attention to developments in the natural sciences. This insight amounts to a case for a tempered, eclectic naturalism. But the case for naturalism is often overstated. We should not overestimate the heuristic benefits of close attention to scientists’ claims, nor should we give up on traditional “armchair” philosophical methods. We should not draw solely on the natural sciences (at the expense of the humanities) when seeking to enrich and (...) discipline our philosophical theorising. Finally, philosophers should not shy away from criticising some scientists’ claims, at the same time as they learn from others. (shrink)

According to the “no-miracles argument” (NMA), truth is the best explanation of the predictive-instrumental success of scientific theories. A standard objection against NMA is that it is viciously circular. In Scientific Realism: How Science Tracks Truth Stathis Psillos has claimed that the circularity objection can be met when NMA is supplemented with a reliabilist approach to justification. I will try to show, however, that scientific realists cannot take much comfort from this policy: if reliabilism makes no qualifications about the domain (...) where inference to the best explanation is reliable, scientific realists flagrantly beg the question. A qualified version of reliabilism, on the other side, does not entitle us to infer the realist conclusion. I conclude, then, that Psillos’s proposal does not make any significant progress for scientific realism. (shrink)

According to Antonia Barkes version of contextualism, epistemic contextualism, a context is defined by a method and its associated assumptions. The subject has to make the assumption that the method is adequate or reliable and that good working conditions hold in order to arrive at knowledge by employing the method. I will criticize Barkes claim that epistemic contextualism can provide a more satisfactory explanation or motivation for context shifts than conversational contextualism (in particular, David Lewiss contextualism). Two more points of (...) criticizm will be presented, which are meant to show that epistemic contextualism presupposes epistemic internalism, and that (epistemic) contextualism leads to an implausible view about which parameters the special achievement that is constitutive of knowledge depends on. I suggest that, contra (epistemic) contextualism, knowledge is a more robust phenomenon that does not depend on whether anyone calls into question any assumptions or raises skeptical doubts in conversation or in his or her mind (as, for example, Fred Dretskes account says). I indicate how this can be reconciled with the phenomenon that knowledge attributions are somewhat unstable and seemingly context-dependent. (shrink)

The Pessimistic Induction over the history of science argues that because most past theories considered empirically successful in their time turn out to be not even approximately true, most present ones probably aren’t approximately true either. But why did past scientists accept those incorrect theories? Kyle Stanford’s ‘Problem of Unconceived Alternatives’ is one answer to that question: scientists are bad at exhausting the space of plausible hypotheses to explain the evidence available to them. Here, I offer another answer, which I (...) call the ‘Problem of Misleading Evidence.’ I argue that this proposal is, in important respects, superior to Stanford’s. (shrink)

As part of his wider critique of the credibility of miraculous testimony, Hume also offers a rather curious argument as to the mutual detriment of conflicting testimony for the miracles of contrary religious worldviews. Scholarship on this aspect of Hume’s reasoning has debated whether or not the considerations are to be understood as essentially probabilistic, and as to whether or not a probabilistic interpretation of the argument is logically valid. The consensus would appear to offer a positive answer to the (...) first question and a negative answer to the second. In this paper I expose a deeper fallacy in Hume’s reasoning that undermines both probabilistic and non-probabilistic readings. My critique is closely based upon analogous considerations in the philosophy of science, and the equally intriguing issue as to the epistemological relevance of conflicting scientific theories throughout the history of science. (shrink)

A prominent type of scientific realism holds that some important parts of our best current scientific theories are at least approximately true. According to such realists, radically distinct alternatives to these theories or theory-parts are unlikely to be approximately true. Thus one might be tempted to argue, as the prominent anti-realist Kyle Stanford recently did, that realists of this kind have little or no reason to encourage scientists to attempt to identify and develop theoretical alternatives that are radically distinct from (...) currently accepted theories in the relevant respects. In other words, it may seem that realists should recommend that scientists be relatively conservative in their theoretical endeavors. This paper aims to show that this argument is mistaken. While realists should indeed be less optimistic of finding radically distinct alternatives to replace current theories, realists also have greater reasons to value the outcomes of such searches. Interestingly, this holds both for successful and failed attempts to identify and develop such alternatives. (shrink)

Enhanced indispensability arguments claim that Scientific Realists are committed to the existence of mathematical entities due to their reliance on Inference to the best explanation. Our central question concerns this purported parity of reasoning: do people who defend the EIA make an appropriate use of the resources of Scientific Realism to achieve platonism? We argue that just because a variety of different inferential strategies can be employed by Scientific Realists does not mean that ontological conclusions concerning which things we should (...) be Scientific Realists about are arrived at by any inferential route which eschews causes, and nor is there any direct pressure for Scientific Realists to change their inferential methods. We suggest that in order to maintain inferential parity with Scientific Realism, proponents of EIA need to give details about how and in what way the presence of mathematical entities directly contribute to explanations. (shrink)

The counterfactual analysis of causation has focused on one particular counterfactual conditional, taking as its starting-point the suggestion that C causes E iff (C E). In this paper, some consequences are explored of reversing this counterfactual, and developing an account starting with the idea that C causes E iff (E C). This suggestion is discussed in relation to the problem of pre-emption. It is found that the 'reversed' counterfactual analysis can handle even the most difficult cases of pre-emption with only (...) minimal complications. The paper closes with a discussion of the wider philosophical implications of developing a reversed counterfactual analysis, especially concerning the differentiation of causes from causal conditions, causation by absences, and the extent to which causes suffice for their effects. (shrink)

This paper seeks to determine the significance, if any, of epidemiological evidence to prove the specific causation element of liability in negligence or other relevant torts—in particular, what importance can be attached to a relative risk > 2, where that figure represents a sound causal inference at the general level. The paper discusses increased risk approaches to epidemiological evidence and concludes that they are a last resort. The paper also criticizes the proposal that the probability of causation can be estimated (...) with reference to the RR, such that RR > 2 is necessary and sufficient for causation. It is argued, following arguments by Sander Greenland and others, that RR > 2 is not necessary for proof of specific causation, except under restrictive biological assumptions that are not known to be satisfied for any important disease, and therefore must never be required. However, the paper argues that in some circumstances RR > 2 can be sufficient to prove causation at law. This position is defended against the widely held judicial and academic view that epidemiological evidence must be accompanied by something else, particular to the case at hand, if it is to have probative force for specific causation. It is argued that far from being epistemically irrelevant, to achieve correct and just outcomes it is in fact mandatory to take epidemiological evidence into account in deciding specific causation. Failing to consider such evidence when it is available leads to error and injustice. The conclusion is that in certain circumstances epidemiological evidence of RR > 2 is not necessary to prove specific causation but that it is sufficient. This “sufficiency” is confined to circumstances where there is no other evidence, as a way of getting clear on what the epidemiological evidence says. Once we have worked out what it says, this must be weighed against the other relevant evidence, if there is any. (shrink)

This paper argues that machine learning and epidemiology are on collision course over causation. The discipline of epidemiology lays great emphasis on causation, while ML research does not. Some epidemiologists have proposed imposing what amounts to a causal constraint on ML in epidemiology, requiring it either to engage in causal inference or restrict itself to mere projection. We whittle down the issues to the question of whether causal knowledge is necessary for underwriting predictions about the outcomes of public health interventions. (...) While there is great plausibility to the idea that it is, conviction that something is impossible does not by itself motivate a constraint to forbid trying. We disambiguate the possible motivations for such a constraint into definitional, metaphysical, epistemological, and pragmatic considerations and argue that “Proceed with caution” is the outcome of each. We then argue that there are positive reasons to proceed, albeit cautiously. Causal inference enforces existing classification schema prior to the testing of associational claims, but associations and classification schema are more plausibly discovered in a back-and-forth process of gaining reflective equilibrium. ML instantiates this kind of process, we argue, and thus offers the welcome prospect of uncovering meaningful new concepts in epidemiology and public health—provided it is not causally constrained. (shrink)

When is a cause of a cause of an effect also a cause of that effect? The right answer is either Sometimes or Always . In favour of Always , transitivity is considered by some to be necessary for distinguishing causes from redundant non-causal events. Moreover transitivity may be motivated by an interest in an unselective notion of causation, untroubled by principles of invidious discrimination. And causal relations appear to add up like transitive relations, so that the obtaining of the (...) overarching relation is not independent of the obtaining of the intermediaries. On the other hand, in favour of Sometimes , often we seem not to treat events that are very spatiotemporally remote from an effect as its causes, even when connected to the effect in question by a chain of counterfactual or chance-raising dependence. Moreover cases of double prevention provide counterexamples to causal transitivity even over short chains. According to the argument of this paper, causation is non-transitive. Transitizing causation provides no viable account of causal redundancy. An unselective approach to causation may motivate resisting the distance counterexamples to transitivity, but it does not help with double prevention, and even makes it more intractable. The strongest point in favour of transitivity is the adding up of causal relations, and this is the point that extant non-transitizing analyses have not adequately addressed. I propose a necessary condition on causation that explains the adding up phenomenon. In doing so it also provides a unifying explanation of distance and double prevention counterexamples to transitivity. (shrink)

I argue that scientific progress is precisely the accumulation of scientific knowledge.

This thesis introduces the Problem of Consciousness as an antinomy between Physicalism and Primitivism about the phenomenal. I argue that Primitivism is implausible, but is supported by two conceptual gaps. The ‘–tivity gap’ holds that physical states are objective and phenomenal states are subjective, and that there is no entailment from the objective to the subjective. The ‘–trinsicality gap’ holds that physical properties are extrinsic and phenomenal qualities are intrinsic, and that there is no entailment from the extrinsic to the (...) intrinsic. Stoljar’s Epistemic View (EV) suggests that we have a limited conception of the physical world, and that the apparent inexplicability of consciousness is merely a symptom of our ignorance. I argue that EV must satisfy two conditions which require it to specify the content of our ignorance. EV’s best hope is a Russellian appeal to our ignorance of intrinsic physical properties. After arguing in favour of this ignorance claim, I show how it undermines the –trinsicality gap. However, I suggest that the –tivity gap cannot be dealt with by the Russellian ignorance hypothesis, nor by any other version of EV. However, I then argue that the Russellian ignorance hypothesis can still be deployed as half of a hybrid account of the phenomenal. Representationalist theories of consciousness have difficulty with the –trinsicality gap, but show promise with the –tivity gap. Specifically, Kriegel’s Self-Representationalism indicates that there can indeed be an entailment from objective physical states to subjective phenomenal states. This paves the way for my hybrid account of consciousness: the subjectivity of a phenomenal state is the product of its self-representational structure, and the qualitative character of a phenomenal state is the product of the epistemically inaccessible intrinsic physical properties involved in its implementation. (shrink)

Worrall argued that structural realism provides a ‘synthesis’ of the main pro-realist argument – the ‘No Miracles Argument’, and the main anti-realist argument – the ‘Pessimistic Induction’. More recently, however, it has been claimed that each of these arguments is an instance of the same probabilistic fallacy – sometimes called the ‘base-rate fallacy’. If correct, this clearly seems to undermine structural realism and Magnus and Callender have indeed claimed that both arguments are fallacious and ‘without [them] we lose the rationale (...) for … structural realism ’. I here argue that what have been shown to be fallacious are simply misguided formalisations of ‘the’ arguments and that when they are properly construed they continue to provide powerful motivation for favouring structural realism. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2012.