Christopher Hitchcock

A simple counterfactual theory of causation fails because of problems with cases of preemption. This might lead us to expect that preemption will raise problems for counterfactual theories of other concepts that have a causal dimension. Indeed, examples are easy to find. But there is one case where we do not find this. Several versions of causal decision theory are formulated using counterfactuals. This might lead us to expect that these theories will yield the wrong recommendations in cases of preemption. But they do not. The explanation, I argue, is that the ‘cause’ that has been the target of counterfactual analyses is a specific relation, ‘actual causation’, that is not needed for prospective deliberation. A simple counterfactual theory of causation seems to capture the notion of cause needed for causal decision theory. This shows, in opposition to some critics, that counterfactual theories of causation are not barking up the wrong tree.

It it tempting to think that if an outcome had some probability of not occurring, then we cannot explain why that outcome in fact occurred. Despite this intuition, most philosophers of science have come to admit the possibility of indeterministic explanation. Yet some of them continue to hold that if an outcome was not determined, it cannot be explained why that outcome rather than some other occurred. I argue that this is an untenable compromise: if indeterministic explanation is possible, then indeterministic contrastive explanation is possible too. In order to defend this conclusion, I develop an account of contrastive explanation.

It is a commonplace that in philosophy, intuitions supply evidence for and against philosophical theories. Recent work in experimental philosophy has brought to bear the intuitions of philosophically naïve subjects in a number of different ways. One line of response to this work has been to claim that philosophers have expertise that privileges their intuitive judgments, and allows them to disregard the judgments of non-experts. This expertise is supposed to be analogous to the expertise of the mathematician or the physicist. This paper critically evaluates this appeal to philosophical expertise.

an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments.

There are a wide variety of theories of causation available in the philosophical literature. For the philosopher working in philosophy of mind, who makes use of causal concepts, what is to be made of this embarrassment of riches? By considering a variety of theoretical perspectives, she can discover which principles or assumptions about causation are robust, and which hold only within particular frameworks. In particular, she should be suspicious when the different premises in an argument can only be made true by shifting between different theories of causation. I illustrate these themes using the causal exclusion argument

The conserved quantity theory of causation aims to analyze causal processes and interactions in terms of conserved quantities. In order to be successful, the theory must correctly distinguish between causal processes and interactions, on the one hand, and pseudoprocesses and mere intersections on the other.Moreover, it must do this while satisfying two further criteria: it must avoid circularity; and the appeal to conserved quantities must not be redundant. I argue that the theory is not successful in meeting these criteria.

We provide a solution to the well-known “Shooting-Room” paradox, developed by John Leslie in connection with his Doomsday Argument. In the “Shooting-Room” paradox, the death of an individual is contingent upon an event that has a 1/36 chance of occurring, yet the relative frequency of death in the relevant population is 0.9. There are two intuitively plausible arguments, one concluding that the appropriate subjective probability of death is 1/36, the other that this probability is 0.9. How are these two values to be reconciled? We show that only the first argument is valid for a standard, countably additive probability distribution. However, both lines of reasoning are legitimate if probabilities are non-standard. The subjective probability of death rises from 1/36 to 0.9 by conditionalizing on an event that is not measurable, or whose probability is zero. Thus we can sometimes meaningfully ascribe conditional probabilities even when the event conditionalized upon is not of positive finite (or even infinitesimal) measure.

A number of recent papers have criticized what they call the dynamical interpretation of evolutionary theory found in Elliott Sober’s The Nature of Selection. Sober argues that we can think of evolutionary theory as a theory of forces analogous to Newtonian mechanics. These critics argue that there are several important disanalogies between evolutionary and Newtonian forces: Unlike evolutionary forces, Newtonian forces can be considered in isolation, they have source laws, they compose causally in a straightforward way, and they are intermediate causes in causal chains. Here we defend and extend the forces analogy by arguing that each of these criticisms is based on a misunderstanding of Newtonian forces. Our discussion also has the interesting consequence that natural selection turns out to be more similar to forces such as friction and elastic forces rather than the more canonical gravitation.

Causes often influence their effects via multiple routes. Moderate alcohol consumption can raise the level of HDL ('good') cholesterol, which in tum reduces the risk of heart disease. Unfortunately, moderate alcohol consumption can also increase the level of homocysteine, which in tum increases the risk of heart disease. The net or overall effect of alcohol consumption on heart disease will depend upon both of these routes, and no doubt upon many others as well. This is a familiar fact of life for engineers and policy makers, one that often gives rise to unintended consequences. Suppose, for example, that the American Federal Aviation Administration were to institute new regulations requiring that aeroplanes be equipped with some expensive new safety feature. Would this regulation save lives? Not necessarily. Every dollar (or pound, or euro, or yen ... ) that an airline spends to upgrade its fleet is a dollar that must be recouped in some way, most likely through higher fares. Higher fares may, in tum, persuade some travellers to drive instead of fly- especially on shorter routes. But it is inherently more dangerous to drive a given route than to fly it, so the net effect of the new regulation may cost lives, rather than saving them (Glassner 1999: 188).

Probability theory is a key tool of the physical, mathematical, and social sciences. It has also been playing an increasingly significant role in philosophy: in epistemology, philosophy of science, ethics, social philosophy, philosophy of religion, and elsewhere. This Handbook encapsulates and furthers the influence of philosophy on probability, and of probability on philosophy. Nearly forty articles summarise the state of play and present new insights in various areas of research at the intersection of these two fields. The articles will be of special interest to practitioners of probability who seek a greater understanding of its mathematical and conceptual foundations, and to philosophers who want to get up to speed on the cutting edge of research in this area. The volume begins with a primer on those parts of probability theory that we believe are most important for philosophers to know, and the rest is divided into seven main sections: History; Formalism; Alternatives to Standard Probability Theory; Interpretations and Interpretive Issues; Probabilistic Judgment and Its Applications; Applications of Probability: Science; and Applications of Probability: Philosophy.

There are many ways of attaching two objects together: for example, they can be connected, linked, tied or bound together; and the connection, link, tie or bind can be made of chain, rope, or cement. Every one of these binding methods has been used as a metaphor for causation. What is the real significance of these metaphors? They express a commitment to a certain way of thinking about causation, summarized in the following thesis: ‘In any concrete situation, there is an objective fact of the matter as to whether two events are in fact bound by the causal relation. It is the aim of philosophical inquiry to analyze this objective relation.’ Through a variety of examples, I hope to cast doubt on this seemingly innocuous thesis. The problem lies not with the word ‘objective’, but with the word ‘the’. The goal of a philosophical account of causation should not be to capture the causal relation, but rather to capture the many ways in which the events of the world can be bound together. 1 The metaphors 2 Unpacking the metaphors 3 Theories of causation 4 The two assassins 5 The birth control pills 6 The smoker-protector gene 7 The bicycle thief 8 Further examples 8.1 Indeterminism 8.2 Probability-lowering causes 8.3 Parts vs wholes 8.4 Symmetric overdetermination 8.5 Delayers 8.6 Causation by omission 8.7 Double prevention/disconnection 8.8 Preemptive prevention 8.9 Quantitative variables 9 Conclusion.

Despite the platitude that analytic philosophy is deeply concerned with language, philosophers of science have paid little attention to methodological issues that arise within historical linguistics. I broach this topic by arguing that many inferences in historical linguistics conform to Reichenbach's common cause principle (CCP). Although the scope of CCP is narrower than many have thought, inferences about the genealogies of languages are particularly apt for reconstruction using CCP. Quantitative approaches to language comparison are readily understood as methods for detecting the correlations that serve as premises for common cause inferences, and potential sources of error in historical linguistics correspond to well-known limitations of CCP

Larry Wright and others have advanced causal accounts of functional explanation, designed to alleviate fears about the legitimacy of such explanations. These analyses take functional explanations to describe second order causal relations. These second order relations are conceptually puzzling. I present an account of second order causation from within the framework of Eells' probabilistic theory of causation; the account makes use of the population-relativity of causation that is built into this theory.

Making a Difference presents fifteen original essays on causation and counterfactuals by an international team of experts. Collectively, they represent the state of the art on these topics. The essays in this volume are inspired by the life and work of Peter Menzies, who made a difference in the lives of students, colleagues, and friends. Topics covered include: the semantics of counterfactuals, agency theories of causation, the context-sensitivity of causal claims, structural equation models, mechanisms, mental causation, causal exclusion argument, free will, and the consequence argument.

There is a tradition, tracing back to Kant, of recasting metaphysical questions as questions about the utility of a conceptual scheme, linguistic framework, or methodological rule for achieving some particular end. Following in this tradition, I propose a ‘means-ends metaphysics ’, in which one rigorously demonstrates the suitability of some conceptual framework for achieving a specified goal. I illustrate this approach using a debate about the nature of events. Specifically, the question is whether the time at which an event occurs is an essential property of that event. I argue that this question is naturally transformed into a question about the methodology of causal modeling. In this new framework, the question concerns what kind of variables to use to represent the effects of potential interventions on a system. This question has a demonstrably correct answer, which sheds new light on the original question