Understanding is an ability manifested by grasping relations of a phenomenon and articulating new explanations. Hence, scientific understanding is inextricably intertwined with and not possible without explanation, and understanding is not a type of propositional knowledge. Anna Elisabeth Höhl provides a novel philosophical account of scientific understanding by developing and defending necessary and sufficient conditions for the understanding that scientists achieve of the phenomena they are researching. This account of scientific understanding is based on and supported by a detailed investigation (...) of an episode from scientific practice in biology. (shrink)

To give a causal explanation is to give information about causal history. But a vast amount of causal history lies behind anything that happens, far too much to be included in any intelligible explanation. This is the Problem of Limitation for explanatory information. To cope with this problem, explanations must select for what is relevant to and adequate for answering particular inquiries. In the present paper this idea is used in order to distinguish two kinds of causal explanation, on the (...) grounds of systematic differences in their conditions of relevance and adequacy. It is further argued that these two forms of causal explanation are interdependent and their interaction provides an instrument through which causal knowledge is acquired and enhanced. What we understand causation in the world to be is neither unconditioned regularity, nor counterfactual dependence, but the sum of correct answers to explanatory inquiries of these two interdependent kinds. (shrink)

ABSTRACT Agents in Frankfurt-style counterexamples only appear to be responsible insofar as they act willingly in the actual sequence, but would need to be manipulated against their will into forming the relevant intention in the alternative sequence. This difference appears ineliminable and unavoidably morally significant. ‘Neo-Frankfurtians’ concede that the sequences must be physically differentiated, but deny their moral differentiation. In contrast, I explore whether the alternatives could be physically undifferentiated, despite their moral difference. The reason there is an ineliminable moral (...) difference is because there is an ineliminable causal one: The agent’s choice must be caused by his own inclinations in one sequence, but by Black’s manipulation in the other. Whether this causal difference entails a physical one depends on whether we suppose causal relations conform to Humean supervenience. The denial of the latter requires us to either reject any broadly Humean view of causation, or else to suppose that we can individuate events or their qualities independently of the physical facts. If these are coherent possibilities, such examples may show that physically differentiated alternatives are not required for moral responsibility. This could support compatibilism, but only if such examples adequately parallel determinism, and I remain sceptical on this point. (shrink)

The nature of scientific explanation is controversial. Some maintain that all scientific explanations have to be contrastive in nature (contrastivism). However, others argue that no scientific explanation is genuinely contrastive (non-contrastivism). In addition, a compatibilist view has been recently devloped. It is argued that the debate between contrastivism and non-contrastivism is merely a linguistic dispute rather than a genuine disagreement on the nature of scientific explanation. Scientific explanations are both contrastive and non-contrastive in some sense (compatibilism). This paper examines the (...) debate between contrastivism and non-contrastivism in scientific explanation. It begins with a critical review of the arguments for contrastivism, for non-contrastivism, and for compatibilism and concludes with some remarks on the prospect of the issue. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of (...) variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Many object to libertarianism by arguing that it manages to solve one problem of luck only by falling prey to another . According to this objection, there is something freedom-undermining about the very circumstances that the libertarian thinks are required for freedom. However, it has proved difficult to articulate precisely what it is about these circumstances that is supposed to undermine freedom—the absence of certain sorts of explanations has perhaps been the most common complaint. In this paper, however, I argue (...) that recent work on the metaphysics of ontological dependence provides the resources for formulating the luck objection in its strongest form. (shrink)

Carl Hempel argued that probabilistic hypotheses are limited in what they can explain. He contended that a hypothesis cannot explain why E is true if the hypothesis says that E has a probability less than 0.5. Wesley Salmon and Richard Jeffrey argued to the contrary, contending that P can explain why E is true even when P says that E’s probability is very low. This debate concerned noncontrastive explananda. Here, a view of contrastive causal explanation is described and defended. It (...) provides a new limit on what probabilistic hypotheses can explain; the limitation is that P cannot explain why E is true rather than A if P assign E a probability that is less than or equal to the probability that P assigns to A. The view entails that a true deterministic theory and a true probabilistic theory that apply to the same explanandum partition are such that the deterministic theory explains all the true contrastive propositions constructable from that partition, whereas the probabilistic theory often fails to do so. (shrink)

The luck argument raises a serious challenge for libertarianism about free will. In broad outline, if an action is undetermined, then it appears to be a matter of luck whether or not one performs it. And if it is a matter of luck whether or not one performs an action, then it seems that the action is not performed with free will. This argument is most effective against event-causal accounts of libertarianism. Recently, Franklin (Philosophical Studies 156:199–230, 2011) has defended event-causal (...) libertarianism against four formulations of the luck argument. I will argue that three of Franklin’s responses are unsuccessful and that there are important versions of the luck challenge that his defense has left unaddressed. (shrink)

The proposition that Tweety is a bird coheres better with the proposition that Tweety has wings than with the proposition that Tweety cannot fly. This relationship of contrastive coherence is the focus of the present paper. Based on recent work in formal epistemology we consider various possibilities to model this relationship by means of probability theory. In a second step we consider different applications of these models. Among others, we offer a coherentist interpretation of the conjunction fallacy.

A central argument of Alfred Mele's Free Will and Luck (2006) is that the problem of luck poses essentially the same problem for all the main indeterministic accounts of free will. Consequently, there is no advantage is certain theories (notably, agent-causal theories) in their capacity to respond to the problem of luck. I argue that Mele has not made a persuasive case for these claims.

The distribution of matter in our universe is strikingly time asymmetric. Most famously, the Second Law of Thermodynamics says that entropy tends to increase toward the future but not toward the past. But what explains this time-asymmetric distribution of matter? In this paper, I explore the idea that time itself has a direction by drawing from recent work on grounding and metaphysical fundamentality. I will argue that positing such a direction of time, in addition to time-asymmetric boundary conditions, enables a (...) better explanation of the thermodynamic asymmetry than is available otherwise. (shrink)

Probabilistic phenomena are often perceived as being problematic targets for contrastive explanation. It is usually thought that the possibility of contrastive explanation hinges on whether or not the probabilistic behaviour is irreducibly indeterministic, and that the possible remaining contrastive explananda are token event probabilities or complete probability distributions over such token outcomes. This paper uses the invariance-under-interventions account of contrastive explanation to argue against both ideas. First, the problem of contrastive explanation also arises in cases in which the probabilistic behaviour (...) of the explanandum is due to unobserved causal heterogeneity. Second, it turns out that, in contrast to the case of pure indeterminism, the plausible contrastive explananda under causal heterogeneity are not token event probabilities, but population-level statistical facts. (shrink)

This article considers the popular thesis that a more proportional relationship between a cause and its effect yields a more abstract causal explanation of that effect, which in turn produces a deeper explanation. This thesis is taken to have important implications for choosing the optimal granularity of explanation for a given explanandum. In this article, I argue that this thesis is not generally true of probabilistic causal relationships. In light of this finding, I propose a pragmatic, interest-relative measure of explanatory (...) depth. This measure uses a decision-theoretic model of information pricing to determine the optimal granularity of explanation for a given explanandum, agent, and decision problem. (shrink)

Jonathan Kvanvig has argued that “objectual” understanding, i.e. the understanding we have of a large body of information, cannot be reduced to explanatory concepts. In this paper, I show that Kvanvig fails to establish this point, and then propose a framework for reducing objectual understanding to explanatory understanding.

Explanatory contrastivists hold that we often explain phenomena of the form p rather than q. In this paper, I present a new, social‐epistemological model of contrastive explanation—accountabilism. Specifically, my view is inspired by social‐scientific research that treats explanations fundamentally as accounts; that is, communicative actions that restore one's social status when charged with questionable behaviour. After developing this model, I show how accountabilism provides a more comprehensive model of contrastive explanation than the causal models of contrastive explanation that are currently (...) en vogue. (shrink)

I argue that results from foraging theory give us good reason to think some evolutionary phenomena are indeterministic and hence that evolutionary theory must be probabilistic. Foraging theory implies that random search is sometimes selectively advantageous, and experimental work suggests that it is employed by a variety of organisms. There are reasons to think such search will sometimes be genuinely indeterministic. If it is, then individual reproductive success will also be indeterministic, and so too will frequency change in populations of (...) organisms employing such search. (shrink)

Two apparently mutually exclusive ideas about the relation between contrastive and non-contrastive explanations can be found in the literature. According to contrastivists, all explanation is contrastive explanation and the supposed existence of non-contrastive explanations can be revealed to be an illusion. According to non-contrastivists, on the other hand, contrastive explanation can be fully analysed in terms of non-contrastive explanation, and is thus not of fundamental importance. In the current article, I discuss the main arguments in favour of and against each (...) of the two positions. This discussion leads to the idea that contrastive explanations are to be understood as parts of a bigger, more complete non-contrastive explanation; but that all actual explanations explain only a limited set of contrasts. I conclude that, once the relation between contrastive and non-contrastive explanations is understood correctly, there remains no substantial issue to divide contrastivism and non-contrastivism. (shrink)

:It is often claimed that libertarianism offers an unattractive conception of free will and moral responsibility because it renders free agency inexplicable and irrational. This essay aims, first, to show that the soundness of these objections turns on more basic disagreements concerning the ideals of free agency and, second, to develop and motivate a truly libertarian conception of the ideals of free agency. The central contention of the essay is that the heart of libertarians’ ideal of free agency is the (...) ideal of agential fundamentality. (shrink)

In this paper I seek to defend libertarianism about free will and moral responsibility against two well-known arguments: the luck argument and the Mind argument. Both of these arguments purport to show that indeterminism is incompatible with the degree of control necessary for free will and moral responsibility. I begin the discussion by elaborating these arguments, clarifying important features of my preferred version of libertarianism—features that will be central to an adequate response to the arguments—and showing why a strategy of (...) reconciliation (often referred to as “deliberative libertarianism”) will not work. I then consider four formulations of the luck argument and find them all wanting. This discussion will place us in a favorable position to understand why the Mind argument also fails. (shrink)

I offer a brief review of, and critical response to, Neil Levy’s fascinating recent book Hard Luck, where he argues that no one is ever free or morally responsible not because of determinism or indeterminism, but because of luck. Two of Levy’s central arguments in defending his free will nihilism concern the nature and role of explanation in a theory of moral responsibility and the nature of akrasia. With respect to explanation, Levy argues that an adequate theory of moral responsibility (...) must be able provide contrastive explanations of why an agent performs one action rather than another, and that libertarians lack the resources to provide such explanations. With respect to akrasia, Levy argues that it is impossible to be directly morally responsible for akratic actions. In response I argue that any sense of contrastive explanation that can reasonably be thought to be a requirement on an adequate theory of moral responsibility is a sense that agent-causal libertarians can secure. I then argue that the agent-causal theory of free will offers an alternative and attractive understanding of motivation and self-control that makes it plausible to think that we can be morally responsible for akratic actions. (shrink)

A “contrastive explanation” explains not only why some event A occurred, but why A occurred as opposed to some alternative event B. Some philosophers argue that agents could only be morally responsible for their choices if those choices have contrastive explanations, since they would otherwise be “luck infested”. Assuming that contrastive explanations cannot be offered for causally undetermined events, this requirement entails that no one could be held responsible for a causally undetermined choice. Such arguments challenge incompatibilism, since they entail (...) that causal determinism is a prerequisite for moral responsibility. However, I argue that for a significant class of choices, even if we stipulate that they are determined, we will be unable to provide a relevant contrastive explanation. Hence causal determinism is no remedy for luck infestation, and compatibilists do not fare much better than incompatibilists in the face of this requirement. This should serve to weaken its philosophical appeal. (shrink)

This paper proposes a reconciliation between libertarian freedomand causal indeterminism, without relying on agent-causation asa primitive notion. I closely examine Peter van Inwagen''s recentcase for free will mysterianism, which is based in part on thewidespread worry that undetermined acts are too chancy to befree. I distinguish three senses of the term chance I thenargue that van Inwagen''s case for free will mystrianism fails,since there is no single construal of the term change on whichall of the premises of his argument for (...) free will–causalindeterminism incompatibilism are true. By use of a particularevent-causal indeterminist account of free action, I support thecase for free will–indeterminism compatibilism. (shrink)

This paper proposes a reconciliation between libertarian freedomand causal indeterminism, without relying on agent-causation asa primitive notion. I closely examine Peter van Inwagen's recentcase for free will mysterianism, which is based in part on thewidespread worry that undetermined acts are too chancy to befree. I distinguish three senses of the term ‘chance’ I thenargue that van Inwagen's case for free will mystrianism fails,since there is no single construal of the term ‘change’ on whichall of the premises of his argument for (...) free will–causalindeterminism incompatibilism are true. By use of a particularevent-causal indeterminist account of free action, I support thecase for free will–indeterminism compatibilism. (shrink)

This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon. According to the proposed account, one understands a phenomenon just in case one grasps a sufficiently accurate and comprehensive model of the ways in which it or its features are situated within a network of dependence relations; one’s degree of understanding is (...) proportional to the comprehensiveness and accuracy of such a model. I compare this account with accounts of scientific understanding that explicate understanding in terms of having an explanation of the understood phenomenon. I discuss three distinct types of cases in which scientific understanding does not amount to possessing an explanation of any kind, and argue that the proposed model-based account can accommodate these cases while still retaining a strong link between understanding and explanation. (shrink)

Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...) articulate norms of completeness for mechanistic explanations that have no such unwanted implications. _1_ Introduction _2_ A Balancing Act: When Do Details Matter? _3_ The Norms of Causal Explanation _4_ The Norms of Constitutive Explanation _5_ Salmon-Completeness _6_ From More Details to More Relevant Details _7_ Non-explanatory Virtues of Abstraction _8_ From Explanatory Models to Explanatory Knowledge _9_ Mechanistic Completeness Reconsidered _10_ Conclusion. (shrink)

How do why-interrogatives work? How do they express the questions they express, in the contexts in which they express them? In this essay, I argue that, at a fundamental level, why-interrogatives work just like other wh-interrogatives, particularly other adjunct wh-interrogatives, and they express the questions they express, in the contexts in which they express them, by the same means that other wh-interrogatives do. These conclusions go against a trend in recent work on why-interrogatives, which holds that they are syntactically and (...) semantically unlike other wh-interrogatives. Since the claim that why-interrogatives are unlike other wh-interrogatives has been taken to support various philosophical theses about the nature of why-questions and explanation, showing that why-interrogatives are just like other wh-interrogatives undermines this line of support for these theses. (shrink)

: On a standard libertarian account of free will, an agent acts freely on some occasion only if there remains, until the action is performed, some chance that the agent will do something else instead right then. These views face the objection that, in such a case, it is a matter of luck whether the agent does one thing or another. This paper considers the problem of luck as it bears on agent‐causal libertarian accounts. A view of this type is (...) defended against a recent and challenging version of the argument from luck. (shrink)

I argue for a subsumption of any version of Grice’s first quantity maxim posited to underlie scalar implicature, by developing the idea of implicature recovery as a kind of explanatory inference, as e.g. in science. I take the applicable model to be contrastive explanation, while following van Fraassen’s analysis of explanation as an answer to a why-question. A scalar implicature is embedded in such an answer, one that meets two probabilistic constraints: the probability of the answer, and ‘favoring’. I argue (...) that besides having application at large, outside of linguistic interpretation, these constraints largely account not only for implicatures based on strength order, logical and otherwise, but also for unordered cases. I thus suggest that Grice’s maxim and its descendants are expressions of general explanatory constraints, as they happen to be manifested in this particular explanatory task. I conclude by briefly discussing how I accordingly view Grice’s system outside of scalar implicature. (shrink)

The traditional Bayesian qualitative account of evidential support (TB) takes assertions of the form 'E evidentially supports H' to affirm the existence of a two-place relation of evidential support between E and H. The analysans given for this relation is $C(H,E) =_{def} Pr(H\arrowvertE) \models Pr(H)$ . Now it is well known that when a hypothesis H entails evidence E, not only is it the case that C(H,E), but it is also the case that C(H&X,E) for any arbitrary X. There is (...) a widespread feeling that this is a problematic result for TB. Indeed, there are a number of cases in which many feel it is false to assert 'E evidentially supports H&X', despite H entailing E. This is known, by those who share that feeling, as the 'tacking problem' for Bayesian confirmation theory. After outlining a generalization of the problem, I argue that the Bayesian response has so far been unsatisfactory. I then argue the following: (i) There exists, either instead of, or in addition to, a two-place relation of confirmation, a three-place, 'contrastive' relation of confirmation, holding between an item of evidence E and two competing hypotheses H₁ and H₂. (ii) The correct analysans of the relation is a particular probabilistic inequality, abbreviated C(H₁, H₂, E). (iii) Those who take the putative counterexamples to TB discussed to indeed be counterexamples are interpreting the relevant utterances as implicitly contrastive, contrasting the relevant hypothesis H₁ with a particular competitor H₂. (iv) The probabilistic structure of these cases is such that ∼C(H₁, H₂, E). This solves my generalization of the tacking problem. I then conclude with some thoughts about the relationship between the traditional Bayesian account of evidential support and my proposed account of the three-place relation of confirmation. (shrink)

I outline four competing probabilistic accounts of contrastive evidential support and consider various considerations that might help arbitrate between these. The upshot of the discussion is that the so-called 'Law of Likelihood' is to be preferred to any of the alternatives considered.

Robert Kane’s libertarian theory is often attacked on the grounds that undetermined self-forming actions are not amenable to contrastive explanation. I propose that we should understand contrastive explanations in terms of an appeal to structuring causes. Doing so reveals that Kane’s claim that there can be no contrastive explanation for self-forming actions is not an unwanted implication of his appeal to indeterminism, but is actually an implication of the fact that the agent’s will is not yet appropriately structured. I then (...) explain how this can assist Kane with the luck objection. (shrink)

Neil Levy mounts two arguments against Robert Kane’s influential libertarian theory. According to the first, because Kanean self-forming actions are undetermined, there can be no contrastive explanation for why agents choose as they do rather than otherwise, in which case how they choose appears to be a matter of luck. According to the second, if one grants Kane the claim that agents are responsible for their undetermined choices in virtue of the fact that they made efforts of will to choose (...) them, the fact that agents engage in dual efforts of will leads to an implausible doubling of the agent’s responsibility. We defend Kane from both objections. We argue against the first by clarifying the nature of contrastive explanation in the context of Kane’s theory and we argue against the second by showing that the kind of doubling of responsibility implied by an agent’s dual efforts of will is, in fact, innocuous. (shrink)

In this paper, we do three things. First, we put forth a novel hypothesis about judgments of moral responsibility according to which such judgments are a species of explanatory judgments. Second, we argue that this hypothesis explains both some general features of everyday thinking about responsibility and the appeal of skeptical arguments against moral responsibility. Finally, we argue that, if correct, the hypothesis provides a defense against these skeptical arguments.

This essay presents an argument, which it calls the Bias Argument, with the dismaying conclusion that (almost) everyone should significantly reduce her confidence in (too many) philosophical beliefs. More precisely, the argument attempts to show that the most precious philosophical beliefs are biased, as the pervasive and permanent disagreement among the leading experts in philosophy cannot be explained by the differences between their evidence bases and competences. After a short introduction, the premises of the Bias Argument are spelled out in (...) the first part. The second part explains why the objections to the Bias Argument are not compelling. Even though the essay does not adopt the conclusion of the Bias Argument, partly because it seems to be self-defeating, the authors know no plausible way to refute its premises. Thus, the primary aim of the essay is to clarify why the aporetic situation of the Bias Argument arises. (shrink)

Explanations contribute to our understanding of the world byembedding phenomena into general nomic patterns that we recognize in the world. Manyof these patterns are, of course, causal ones, but the declaration as ``causal'' often fails to determinethe explanatory power of the pattern. More important is the systematization capacity and the empiricalcontent of the pattern or theory with respect to explanations. We can specify these parameters moreprecisely within the framework of the structuralist view of theories.

The basic idea of counterfactual theories of causation is that the meaning of causal claims can be explained in terms of counterfactual conditionals of the form “If A had not occurred, C would not have occurred”. While counterfactual analyses have been given of type-causal concepts, most counterfactual analyses have focused on singular causal or token-causal claims of the form “event c caused event e”. Analyses of token-causation have become popular in the last thirty years, especially since the development in the (...) 1970's of possible world semantics for counterfactuals. The best known counterfactual analysis of causation is David Lewis's (1973b) theory. However, intense discussion over thirty years has cast doubt on the adequacy of any simple analysis of singular causation in terms of counterfactuals. Recent years have seen a proliferation of different refinements of the basic idea to achieve a closer match with commonsense judgements about causation. (shrink)

This dissertation aims to determine the optimal level of granularity for the variables used in probabilistic causal models. These causal models are useful for generating explanations in a number of scientific contexts. In Chapter 1, I argue that there is rarely a unique level of granularity at which a given phenomenon can be causally explained, thereby rejecting various causal exclusion arguments. In Chapter 2, I consider several recent proposals for measuring the explanatory power of causal explanations, and show that these (...) measures fail to track the comparative depth of explanations given at different levels of granularity. In Chapter 3, I offer a pragmatic account of how to partition the measure space of a causal variable so as to optimally explain its effect. My account uses the decision-theoretic notion of value of information, and indexes the relative depth of an explanation to a particular agent faced with a particular decision problem. Chapter 4 applies this same decisiontheoretic framework to answer the epistemic question of how to discover constitutive relationships in nature. In Chapter 5, I describe the formal details of the relationship between random variables that are meant to be coarse-grained and fine-grained representations of the same type of phenomenon. I use this formal framework to rebut a popular argument for the view that special science probabilities can be objective chances. Chapter 6 discusses challenges related to the causal interpretation of Bayes nets that use imprecise rather than precise probabilities. (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)

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

Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 4: Evolutionary Indeterminism.

The argument that free will and indeterminism are incompatible is known as the Luck Argument. This argument has been put forward against the libertarians who deny determinism to prove free will. The basic idea of the argument is that in an undetermined world, free will cannot be imagined. There are various formulations for this argument. They all seek to explain why, if the choice is undetermined, it is by chance; but the focus of this article is on the explanatory formulation. (...) The basic idea of this formulation is that in undetermined situations, there is no contrastive explanation and in this case, there is no free will. This argument is formulated as follows: If a choice is undetermined, it means that it is possible to make a different choice by assuming the past before the choice is completely identical. If it is possible to make different choices with the same past, it is not possible to provide a contrastive explanation for the choice. If there is no contrastive explanation for choice, then that choice is by chance. If a choice happens by chance, it’s not free. Therefore, if a choice is undetermined, it is not free. Libertarian responses to this argument can be divided into three main categories. The first group confesses that the argument is question-begging. The main contention is that since only in determined situations is it possible to have contrastive explanations, it is impossible to seek them for undetermined situations. However, this is not the case in this particular case, and the claim is another form of the combination of the first and second premises. The second group of responses to the Luck Argument focusing on the third premise of the argument argues that although there is no contrastive explanation for undetermined choices, another type of explanation which is non-contrastive is possible. In this case, the choice is no longer by chance and it is free. But it seems that non-contrastive explanations are not sufficient for explaining undetermined choices. The third answer claims that it is not that we do not have contrastive explanations for all undetermined situations, and that there is a contrastive explanation at least for some undetermined choices. In fact, this group argues that the combination of the first and second premise of the Luck Argument – that if a choice is undetermined, there is no contradictory explanation - is wrong. Among the different perspectives of this category, is the focus on describing and evaluating Clark’s response. He proposes different scenarios to answer this argument. Their evaluation shows that in the first and second scenarios, there was a different definition of indeterminism and although at first glance, they were considered a response to the Luck Argument, the evil consequence of this presupposition and its incompatibility with free choices has been explained. Clark’s third scenario is consistent with the definition of indeterminism that the Luck Argument had in the first premise, but Clark himself also acknowledges that we have no contrastive explanations for such situations. Taken together, with all of these scenarios, Clark’s attempt to illustrate the contrast between undetermined choices seems to have failed. In conclusion, Evaluation of the three responses presented in the explanatory formulation of the Luck Argument shows that they have failed to solve the problem and explaining free will in undetermined situations continues to be challenging. (shrink)