Fundamental physics makes no clear use of causal notions; it uses laws that operate in relevant respects in both temporal directions and that relate whole systems across times. But by relating causation to evidence, we can explain how causation fits in to a physical picture of the world and explain its temporal asymmetry. This paper takes up a deliberative approach to causation, according to which causal relations correspond to the evidential relations we need when we decide on one thing in (...) order to achieve another. Tamsin's taking her umbrella is a cause of her staying dry, for example, if and only if her deciding to take her umbrella for the sake of staying dry is adequate grounds for believing she'll stay dry. This correspondence explains why causation matters: knowledge of causal structure helps us make decisions that are evidence of outcomes we seek. The account also explains why we can control the future and not the past, and why causes come before their effects. When agents properly deliberate, their decisions can never count as evidence for any outcomes they may seek in the past. From this it follows that causal relations don't run backwards. This deliberative asymmetry is itself traced back to asymmetries of evidence and entropy, providing a new way of deriving causal asymmetry from temporally symmetric laws. (shrink)

Probabilism is committed to two theses: 1) Opinion comes in degrees—call them degrees of belief, or credences. 2) The degrees of belief of a rational agent obey the probability calculus. Correspondingly, a natural way to argue for probabilism is: i) to give an account of what degrees of belief are, and then ii) to show that those things should be probabilities, on pain of irrationality. Most of the action in the literature concerns stage ii). Assuming that stage i) has been (...) adequately discharged, various authors move on to stage ii) with varied and ingenious arguments. But an unsatisfactory response at stage i) clearly undermines any gains that might be accrued at stage ii) as far as probabilism is concerned: if those things are not degrees of belief, then it is irrelevant to probabilism whether they should be probabilities or not. In this paper we scrutinize the state of play regarding stage i). We critically examine several of the leading accounts of degrees of belief: reducing them to corresponding betting behavior (de Finetti); measuring them by that behavior (Jeffrey); and analyzing them in terms of preferences and their role in decision-making more generally (Ramsey, Lewis, Maher). We argue that the accounts fail, and so they are unfit to subserve arguments for probabilism. We conclude more positively: ‘degree of belief’ should be taken as a primitive concept that forms the basis of our best theory of rational belief and decision: probabilism. (shrink)

Philosophers have explored objective interpretations of probability mainly by considering empirical probability statements. Because of this focus, it is widely believed that the logical interpretation and the actual-frequency interpretation are unsatisfactory and the hypothetical-frequency interpretation is not much better. Probabilistic assertions in pure mathematics present a new challenge. Mathematicians prove theorems in number theory that assign probabilities. The most natural interpretation of these probabilities is that they describe actual frequencies in finite sets and limits of actual frequencies in infinite sets. (...) This interpretation vindicates part of what the logical interpretation of probability aimed to establish. (shrink)

Counter-intuitive consequences of both causal decision theory and evidential decision theory are dramatized. Each of those theories is thereby put under some pressure to supply an error theory to explain away intuitions that seem to favour the other. Because trouble is stirred up for both sides, complacency about Newcomb’s problem is discouraged.

(1) Suppose that you care only about speaking the truth, and are confident that some particular deterministic theory is true. If someone asks you whether that theory is true, are you rationally required to answer "yes"? -/- (2) Suppose that you face a problem in which (as in Newcomb's problem) one of your options---call it "taking two boxes"---causally dominates your only other option. Are you rationally required to take two boxes? -/- Those of us attracted to causal decision theory are (...) under pressure to answer "yes" to both questions. However, it has been shown that many existing decision theories are inconsistent with doing so (Ahmed 2014). A simple proof shows that the same goes for an even wider class of theories: all "suppositional" decision theories. The moral is that causal decision theorists must either answer "no" to one of the above questions, or else abandon suppositional decision theories. (shrink)

For those who maintain that free will is incompatible with causal determinism, a persistent problem is to give a coherent characterization of action that is neither determined by prior events nor random, arbitrary, lucky or in some way insufficiently under the control of the agent to count as free action. One approach—that of Roderick Chisholm and others—is to say that a third alternative is for an action to be caused by an agent in a way that is not reducible to (...) event causal terms. A different approach than the Chisholmian appeal to primitive substance causation is one that, instead, involves causal relations purely among events. This paper presents a particular event-causal indeterminist account of free action, describing both its attractions and recent objections to it, and then proposes a revised version, with the aim of supporting the plausibility of an event-causal indeterminist approach to free will. (shrink)

It is bad news to find out that one's cognitive or perceptual faculties are defective. Furthermore, it’s not always transparent how one ought to revise one's beliefs in light of such news. Two sorts of news should be distinguished. On the one hand, there is news that a faculty is unreliable -- that it doesn't track the truth particularly well. On the other hand, there is news that a faculty is anti-reliable -- that it tends to go positively wrong. These (...) two sorts of news call for extremely different responses. We provide accounts of these responses, and prove bounds on the degree to which one can reasonably count oneself as mistaken about a given subject matter. (shrink)

I defend evidential decision theory and the theory of deliberation-probability dynamics from a recent criticism advanced by Jordan Howard Sobel. I argue that his alleged counterexample to the theories, called the Popcorn Problem is not a genuine counterexample.

I argue that to the extent to which philosophical theories of objective probability have offered theoretically adequateconceptions of objective probability (in connection with such desiderata as causal and explanatory significance, applicability to single cases, etc.), they have failed to satisfy amethodological standard — roughly, a requirement to the effect that the conception offered be specified with the precision appropriate for a physical interpretation of an abstract formal calculus and be fully explicated in terms of concepts, objects or phenomena understood independently (...) of the idea of physical probability. The significance of this, and of the suggested methodological standard, is then briefly discussed. (shrink)

I argue that to the extent to which philosophical theories of objective probability have offered theoretically adequate conceptions of objective probability , they have failed to satisfy a methodological standard -- roughly, a requirement to the effect that the conception offered be specified with the precision appropriate for a physical interpretation of an abstract formal calculus and be fully explicated in terms of concepts, objects or phenomena understood independently of the idea of physical probability. The significance of this, and of (...) the suggested methodological standard, is then briefly discussed. (shrink)

Many philosophers have become worried about the use of standard real numbers for the probability function that represents an agent's credences. They point out that real numbers can't capture the distinction between certain extremely unlikely events and genuinely impossible ones—they are both represented by credence 0, which violates a principle known as “regularity.” Following Skyrms 1980 and Lewis 1980, they recommend that we should instead use a much richer set of numbers, called the “hyperreals.” This essay argues that this popular (...) view is the result of two mistakes. The first mistake, which this essay calls the “numerical fallacy,” is to assume that a distinction that isn't represented by different numbers isn't represented at all in a mathematical representation. In this case, the essay claims that although the real numbers do not make all relevant distinctions, the full mathematical structure of a probability function does. The second mistake is that the hyperreals make too many distinctions. They have a much more complex structure than credences in ordinary propositions can have, so they make distinctions that don't exist among credences. While they might be useful for generating certain mathematical models, they will not appear in a faithful mathematical representation of credences of ordinary propositions. (shrink)

This paper shows how a particular resiliency-centered approach to chance lends support for two conditions characterizing chance. The first condition says that the present chance of some proposition A conditional on the proposition about some later chance of A should be set equal to that later chance of A. The second condition requires the present chance of some proposition A to be equal to the weighted average of possible later chances of A. I first introduce, motivate, and make precise a (...) resiliency-centered approach to chance whose basic idea is that any chance distribution should be maximally invariant under variation of experimental factors. Second, I show that any present chance distribution that violates the two conditions can be replaced by another present chance distribution that satisfies them and is more resilient under variation of experimental factors. This shows that the two conditions are an essential feature of chances that maximize resiliency. Finally, I explore the relationship between the idea of resilient chances so understood and so-called Humean accounts of chance—one of the most promising recent philosophical accounts of chance. (shrink)

This paper examines the Transference Theory of causation, developed originally by Aronson (1971) and Fair (1979). Three difficulties for that theory are presented: firstly, problems associated with the direction of transference and causal asymmetry; secondly, the case of persistence as causation, for example where a body's own inertia is the cause of its motion; and thirdly the problematic notion of identity through time of physical quantities such as energy or momentum. Finally, the theory is compared with the Conserved Quantity Theory (...) (Dowe 1992c), and it is shown that that account embodies the modifications that the transference theory needs to adopt. (shrink)

In this paper I offer an 'integrating account' of singular causation, where the term 'integrating' refers to the following program for analysing causation. There are two intuitions about causation, both of which face serious counterexamples when used as the basis for an analysis of causation. The 'process' intuition, which says that causes and effects are linked by concrete processes, runs into trouble with cases of 'misconnections', where an event which serves to prevent another fails to do so on a particular (...) occasion and yet the two events are linked by causal processes. The chance raising intuition, according to which causes raise the chance of their effects, easily accounts for misconnections but faces the problem of chance lowering causes, a problem easily accounted for by the process approach. The integrating program attempts to provide an analysis of singular causation by synthesising the two insights, so as to solve both problems. In this paper I show that extant versions of the integrating program due to Eells, Lewis, and Menzies fail to account for the chance-lowering counterexample. I offer a new diagnosis of the chance lowering case, and use that as a basis for an integrating account of causation which does solve both cases. In doing so, I accept various assumptions of the integrating program, in particular that there are no other problems with these two approaches. As an example of the process account, I focus on the recent CQ theory of Wesley Salmon (1997). (shrink)

Process theories of causality seek to explicate causality as a property of individual causal processes. This paper examines the capacity of such theories to account for the asymmetry of causation. Three types of theories of asymmetry are discussed; the subjective, the temporal, and the physical, the third of these being the preferred approach. Asymmetric features of the world, namely the entropic and Kaon arrows, are considered as possible sources of causal asymmetry and a physical theory of asymmetry is subsequently developed (...) with special reference to the questions of objectivity and backwards causation. (shrink)

Some of the information we receive comes to us in an explicitly conditional form. It is an open question how to model the accommodation of such information in a Bayesian framework. This paper presents data suggesting that there may be no strictly Bayesian account of updating on conditionals. Specifically, the data seem to indicate that such updating at least sometimes proceeds on the basis of explanatory considerations, which famously have no home in standard Bayesian epistemology. The paper also proposes a (...) still broadly Bayesian model of updating on conditionals that explicitly factors in explanation. The model is shown to have clear empirical content and thus to be open to empirical testing. (shrink)

Elqayam & Evans (E&E) argue against prescriptive normativism and in favor of descriptivism. I challenge the assumption, implicit in their article, that there is a choice to be made between the two approaches. While descriptivism may be the right approach for some questions, others call for a normativist approach. To illustrate the point, I briefly discuss two questions of the latter sort.

Epistemic closure under known implication is the principle that knowledge of "p" and knowledge of "p implies q", together, imply knowledge of "q". This principle is intuitive, yet several putative counterexamples have been formulated against it. This paper addresses the question, why is epistemic closure both intuitive and prone to counterexamples? In particular, the paper examines whether probability theory can offer an answer to this question based on four strategies. The first probability-based strategy rests on the accumulation of risks. The (...) problem with this strategy is that risk accumulation cannot accommodate certain counterexamples to epistemic closure. The second strategy is based on the idea of evidential support, that is, a piece of evidence supports a proposition whenever it increases the probability of the proposition. This strategy makes progress and can accommodate certain putative counterexamples to closure. However, this strategy also gives rise to a number of counterintuitive results. Finally, there are two broadly probabilistic strategies, one based on the idea of resilient probability and the other on the idea of assumptions that are taken for granted. These strategies are promising but are prone to some of the shortcomings of the second strategy. All in all, I conclude that each strategy fails. Probability theory, then, is unlikely to offer the account we need. (shrink)

A sourcebook/textbook on the problem of free will and determinism. Contains a history of the free will problem, a taxonomy of current free will positions, the standard argument against free will, the physics, biology, and neuroscience of free will, the most plausible and practical solution of the problem, and reviews of the work of the leading determinist Ted Honderich, the leading libertarian Robert Kane, the well-known compatibilist Daniel Dennett, and the determinism-agnostic Alfred Mele.

To clarify and illuminate the place of probability in science Ellery Eells and James H. Fetzer have brought together some of the most distinguished philosophers ...

Showcasing original arguments for well-defined positions, as well as clear and concise statements of sophisticated philosophical views, this volume is an ...

Theories of rational decision making often abstract away from computational and other resource limitations faced by real agents. An alternative approach known as resource rationality puts such matters front and center, grounding choice and decision in the rational use of finite resources. Anticipated by earlier work in economics and in computer science, this approach has recently seen rapid development and application in the cognitive sciences. Here, the theory of rationality plays a dual role, both as a framework for normative assessment (...) and as a source of scientific hypotheses about how mental processes in fact work. The latter project, often called rational analysis, depends for its success on a fine-grained characterization of the computational problem facing a decision maker, which may in turn depend on realistic assumptions about what the relevant agent is like. As a consequence, resource rationality involves a delicate, but often fruitful interplay between the normative and the descriptive. (shrink)

Causation has always been a philosophically controversial subject matter. While David Hume’s empiricist account of causation has been the dominant influence in analytic philosophy and science during modern times, a minority view has instead connected causation essentially to agency and manipulation. A related approach has for the first time gained widespread popularity in recent years, due to new powerful theories of causal inference in science that are based in a technical notion of intervention, and James Woodward’s closely connected interventionist theory (...) of causation in philosophy. This monograph assesses five manipulationist or interventionist theories of causation, viewed as theories that purport to tell us what causation is by providing us with the meaning of causal claims. It is shown that they cannot do this, as the conditions on causation that they impose are too weak, mainly due to ineliminable circularities in their definitions of causal terms. It is then argued that a subset of Woodward’s theory can nevertheless contribute crucially to an explanation of the unique role that manipulation has in our acquisition of causal knowledge. This explanation differs from the common regularist explanation of the epistemic utility of manipulation and experiment, and it is taken to confirm several important manipulationist intuitions. However, the success of the explanation depends on (this subset of) interventionism not itself being understood as a theory of causation, but as a theory of intervention. (shrink)

“Probabilistic Causation” designates a group of theories that aim to characterize the relationship between cause and effect using the tools of probability theory. The central idea behind these theories is that causes change the probabilities of their effects. This article traces developments in probabilistic causation, including recent developments in causal modeling. A variety of issues within, and objections to, probabilistic theories of causation will also be discussed.

This article explores the connection between objective chance and the randomness of a sequence of outcomes. Discussion is focussed around the claim that something happens by chance iff it is random. This claim is subject to many objections. Attempts to save it by providing alternative theories of chance and randomness, involving indeterminism, unpredictability, and reductionism about chance, are canvassed. The article is largely expository, with particular attention being paid to the details of algorithmic randomness, a topic relatively unfamiliar to philosophers.

Negative causation occurs when an absence serves as cause, effect, or causal intermediary. Negative causation is genuine causation, or so I shall argue. It involves no physical connection between cause and effect. Thus causes need not be physically connected to their effects.

There are three questions associated with Simpson’s Paradox (SP): (i) Why is SP paradoxical? (ii) What conditions generate SP?, and (iii) What should be done about SP? By developing a logic-based account of SP, it is argued that (i) and (ii) must be divorced from (iii). This account shows that (i) and (ii) have nothing to do with causality, which plays a role only in addressing (iii). A counterexample is also presented against the causal account. Finally, the causal and logic-based (...) approaches are compared by means of an experiment to show that SP is not basically causal. (shrink)

State of art paper on the topic causation, around the problem of the nature of causation. Central theories of contemporary philosophical literature are discussed and analysed, namely, regularity theories of Hume and Mackie, counterfactual theories of Lewis, probabilistic theories of Reichenbach, Lewis and Menzies and causal processes theories of Salmon and Dowe.

Intellectual progress involves forming a more accurate picture of the world. But it also figuring out which concepts to use for theorizing about the world. Bayesian epistemology has had much to say about the former aspect of our cognitive lives, but little if at all about the latter. I outline a framework for formulating questions about conceptual change in a broadly Bayesian framework. By enriching the resources of Epistemic Utility Theory with a more expansive conception of epistemic value, I offer (...) a picture of our cognitive economy on which adopting new conceptual tools can sometimes be epistemically rational. (shrink)

In this paper, a concept of chance is introduced that is compatible with deterministic physical laws, yet does justice to our use of chance-talk in connection with typical games of chance. We take our cue from what Poincaré called "the method of arbitrary functions," and elaborate upon a suggestion made by Savage in connection with this. Comparison is made between this notion of chance, and David Lewis' conception.

State of art paper on the topic laws of nature, around the problem of identification what is to be a law of nature. The most prominent theories of contemporary philosophical literature are discussed and analysed, such as: the simple regularity theory, from Hume; the Mill-Ramsey-Lewis best systems theory; the Dretske-Tooley-Armstrong theory of laws as relations among universals; Ellis’s essentialist theory; Cartwright’s theory of laws as ceteris paribus laws; the anti-reductionist theories of Lange, Maudlin and Carroll, the anti-realist theories of Mumford, (...) van Fraassen and Giere; etc. (shrink)

It is well known that de se (or ‘self-locating’) propositions complicate the standard picture of how we should respond to evidence. This has given rise to a substantial literature centered around puzzles like Sleeping Beauty, Dr. Evil, and Doomsday—and it has also sparked controversy over a style of argument that has recently been adopted by theoretical cosmologists. These discussions often dwell on intuitions about a single kind of case, but it’s worth seeking a rule that can unify our treatment of (...) all evidence, whether de dicto or de se. -/- This paper is about three candidates for such a rule, presented as replacements for the standard updating rule. Each rule stems from the idea that we should treat ourselves as a random sample, a heuristic that underlies many of the intuitions that have been pumped in treatments of the standard puzzles. But each rule also yields some strange results when applied across the board. This leaves us with some difficult options. We can seek another way to refine the random-sample heuristic, e.g. by restricting one of our rules. We can try to live with the strange results, perhaps granting that useful principles can fail at the margins. Or we can reject the random-sample heuristic as fatally flawed—which means rethinking its influence in even the simplest cases. (shrink)

Ordinary Language Philosophy has largely fallen out of favour, and with it the belief in the primary importance of analyses of ordinary language for philosophical purposes. Still, in their various endeavours, philosophers not only from analytic but also from other backgrounds refer to the use and meaning of terms of interest in ordinary parlance. In doing so, they most commonly appeal to their own linguistic intuitions. Often, the appeal to individual intuitions is supplemented by reference to dictionaries. In recent times, (...) Internet search engine queries for expressions of interest have become quite popular. Apparently, philosophers attempt to surpass the limits of their own linguistic intuitions by appealing to experts or to factual uses of language. I argue that this attempt is commendable but that its execution is wanting. Instead of appealing to dictionaries or Internet queries, philosophers should employ computer-based linguistic corpora in order to confirm or falsify hypotheses about the factual use of language. This approach also has some advantages over methods employed by experimental philosophers. If the importance of ordinary language is stressed, the use of linguistic corpora is hardly avoidable. (shrink)

A decision problem where Causal Decision Theory (CDT) declines a free $1,000, with the foreseeable effect that the agent is $1,000 poorer, and in no other way better off, than if she had taken the offer.

In this dissertation I develop a pluralist theory of actual causation. I argue that we need to distinguish between total, path-changing, and contributing actual causation. The pluralist theory accounts for a set of example cases that have raised problems for extant unified theories and it is supported by considerations about the various functions of causal concepts. The dissertation also analyses the context-sensitivity of actual causation. I show that principled accounts of causal reasoning in legal inquiry face limitations and I argue (...) that the context-sensitivity of actual causation is best represented by a distinction between default and deviant states in causal models. (shrink)

Disagreement is a hot topic in epistemology. A fast-growing literature centers around a dispute between the ‘steadfast’ view, on which one may maintain one’s beliefs even in the light of disagreement with epistemic peers who have all the same evidence, and the ‘conciliationist’ view, on which such disagreement requires a revision of attitudes. In this paper, however, I argue that there is less separating the main rivals in the debate about peer disagreement than is commonly thought. The extreme versions of (...) both views are clearly indefensible, while more moderate versions of the views converge on the idea that how much revision of belief is called for by an instance of peer disagreement varies from case to case. Those tempted by this diagnosis are sometimes pessimistic about the prospects for giving a unified account which clearly predicts when more or less extensive revisions will be called for. By contrast, in this paper I give an account that aspires to such unity and predictive power, centering on the notion of the net resilience of your estimate of your own reliability against your estimate of your interlocutor’s reliability. The view I present thus amounts to a new, moderate theory of how one should respond to disagreement. I argue that ultimately, when we weaken conciliationism and the steadfast view to account for exception cases and to make them adequately plausible, they end up converging on the moderate view I present. Much of the seeming disagreement about disagreement is, then, illusory. (shrink)

I argue that there are at least two concepts of law of nature worthy of philosophical interest: strong law and weak law. Strong laws are the laws investigated by fundamental physics, while weak laws feature prominently in the “special sciences” and in a variety of non-scientific contexts. In the first section, I clarify my methodology, which has to do with arguing about concepts. In the next section, I offer a detailed description of strong laws, which I claim satisfy four criteria: (...) (1) If it is a strong law that L then it also true that L; (2) strong laws would continue to be true, were the world to be different in some physically possible way; (3) strong laws do not depend on context or human interest; (4) strong laws feature in scientific explanations but cannot be scientifically explained. I then spell out some philosophical consequences: (1) is incompatible with Cartwright’s contention that “laws lie” (2) with Lewis’s “best-system” account of laws, and (3) with contextualism about laws. In the final section, I argue that weak laws are distinguished by (approximately) meeting some but not all of these criteria. I provide a preliminary account of the scientific value of weak laws, and argue that they cannot plausibly be understood as ceteris paribus laws. (shrink)