This provocative book refurbishes the traditional account of freedom of will as reasons-guided "agent" causation, situating its account within a general metaphysics. O'Connor's discussion of the general concept of causation and of ontological reductionism v. emergence will specially interest metaphysicians and philosophers of mind.

The law views with suspicion statistical evidence, even evidence that is probabilistically on a par with direct, individual evidence that the law is in no way suspicious of. But it has proved remarkably hard to either justify this suspicion, or to debunk it. In this paper, we connect the discussion of statistical evidence to broader epistemological discussions of similar phenomena. We highlight Sensitivity – the requirement that a belief be counterfactually sensitive to the truth in a specific way – as (...) a way of epistemically explaining the legal suspicion towards statistical evidence. Still, we do not think of this as a satisfactory vindication of the reluctance to rely on statistical evidence. Knowledge – and Sensitivity, and indeed epistemology in general – are of little, if any, legal value. Instead, we tell an incentive-based story vindicating the suspicion towards statistical evidence. We conclude by showing that the epistemological story and the incentive-based story are closely and interestingly related, and by offering initial thoughts about the role of statistical evidence in morality. (shrink)

This book provides a systematic, philosophically informed account of criminal responsibility. It begins by providing a general account of criminal responsibility based on the relationship between the action that the defendent has performed and their character. It then moves on to reconsider some of the central doctrines of criminal responsibility in the light of that account.

The book was planned and written as a single, sustained argument. But earlier versions of a few parts of it have appeared separately. The object of this book is both to establish the existence of the paradoxes, and also to describe a non-Pascalian concept of probability in terms of which one can analyse the structure of forensic proof without giving rise to such typical signs of theoretical misfit. Neither the complementational principle for negation nor the multiplicative principle for conjunction applies (...) to the central core of any forensic proof in the Anglo-American legal system. There are four parts included in this book. Accordingly, these parts have been written in such a way that they may be read in different orders by different kinds of reader. (shrink)

This article explores a long-running debate in evidence theory about the significance of certain puzzling cases where there is reluctance to ascribe liability despite a high probability of liability. It focuses on certain analyses of these puzzles, distinguishing between inferential, moral, and knowledge-based analyses. The article emphasizes the richness and complexity of the puzzle cases and suggests why they are difficult to resolve.

Legal scholarship exploring the nature of evidence and the process of juridical proof has had a complex relationship with formal modeling. As evident in so many fields of knowledge, algorithmic approaches to evidence have the theoretical potential to increase the accuracy of fact finding, a tremendously important goal of the legal system. The hope that knowledge could be formalized within the evidentiary realm generated a spate of articles attempting to put probability theory to this purpose. This literature was both insightful (...) and frustrating. Much light was shed on the legal system, but it also quickly became evident that the tools of probability theory were in many ways ill-constructed for the task. Fundamental incompatibilities between the structure of legal decision making and the extant formal tools were identified, and it became evident that many of the purported explanations of legal phenomena were internally inconsistent. As a consequence, interest in this type of formal modeling declined, and attention was directed toward different kinds of explanations of the phenomena. Perhaps under the influence of a recent trend toward various types of formal modeling in legal scholarship, a recent burst of articles, rather than attempting to explain the macro structure of trials, which was the previous object of interest, attempts to quantify the probative value of various items of evidence in ways consistent with the formal features of various probability theories, and then to study decision making from that perspective. For example, the value of evidence is often purported to be its likelihood ratio, that is, the probability of discovering or receiving the evidence given a hypothesis (e.g., the defendant did it) divided by the probability of discovering or receiving the evidence given the negation of the hypothesis (the defendant didn't do it). Alternatively, the value of evidence is purported (more contextually) to be the information gain it provides, defined as the increase in probability it provides for a hypothesis above the probability of the hypothesis based on the other available evidence. Both conceptions then assume that all of the various probability assessments conform or ought to conform to the dictates of Bayes' theorem (that maintains consistency among such assessments); empirical studies are then done testing the extent to which this is so and proposing how the law can increase the probability that it is so. The general criticisms of using Bayes' theorem as a formal model of juridical proof are well known and were integral to the last wave of interest in formal modeling of the evidentiary process. This paper thus for the most part puts aside that more general issue, and focuses specifically on mathematical modeling of the value of particular items of evidence. The paper demonstrates that formal modeling has only limited value in explaining the value of legal evidence, much more limited than those constructing and discussing the models assume, and thus that the conclusions they draw about the value of evidence are unwarranted. This is done through a discussion of four recent examples that attempt to quantify evidence relating to, respectively, carpet fibers, infidelity, DNA random-match evidence, and character evidence used to impeach a witness. This article thus makes two contributions. First, and most importantly, it is another demonstration of the complex relationship between algorithmic tools and legal decision making. Second, at a minimum it points out serious pitfalls for analytical or empirical studies of juridical proof. (shrink)

The doyen of living English philosophers, by these reflections, took hold of and changed the outlook of a good many other philosophers, if not quite enough. He did so, essentially, by assuming that talk of freedom and responsibility is talk not of facts or truths, in a certain sense, but of our attitudes. His more explicit concern was to look again at the question of whether determinism and freedom are consistent with one another -- by shifting attention to certain personal (...) rather than moral attitudes, first of all gratitude and resentment. In the end, he arrived at a kind of Compatibilist or, as he says, Optimist conclusion. That is no doubt a recommendation but not the largest recommendation of this splendidly rich piece of philosophy. (shrink)

By means of the Rollback Argument, this paper argues that metaphysically robust probabilities are incompatible with a kind of control which can ensure that free actions are not a matter of chance. Our main objection to those (typically agent-causal) theories which both attribute a kind of control to agents that eliminates the role of chance concerning free actions and ascribe probabilities to options of decisions is that metaphysically robust probabilities should be posited only if they can have a metaphysical explanatory (...) role but probabilities can explain anything only if chance has a role. First, we reconstruct the Rollback Argument. Second, we criticize the standard ways of reconciling non-chancy control with metaphysically robust probabilities. Finally, we respond to those worries that are related to the thought experiment of the Rollback Argument. (shrink)

This is a work concerned with justification and freedom and the relationship between these. Its summational aim is to defend a transcendental argument for free will – that we could not be epistemically justified in undermining a strong notion of free will, as a strong notion of free will would be required for any such process of undermining to be itself epistemically justified. The book advances two transcendental arguments – for a deontically internalist conception of epistemic justification and the aforementioned (...) argument for a libertarian conception of free will. In defending each of these arguments, the book both defends and relies upon the principle that ‘ought’ implies ‘can’. In articulating the latter transcendental argument – for freedom – heavy reliance is made on the earlier, epistemic, work: especially on the deontological conception of rational justification (on epistemic internalism). (shrink)

This book presents a comprehensive overview of what the criminal law would look like if organised around the principle that those who deserve punishment should receive punishment commensurate with, but no greater than, that which they deserve. Larry Alexander and Kimberly Kessler Ferzan argue that desert is a function of the actor's culpability, and that culpability is a function of the risks of harm to protected interests that the actor believes he is imposing and his reasons for acting in the (...) face of those risks. The authors deny that resultant harms, as well as unperceived risks, affect the actor's desert. They thus reject punishment for inadvertent negligence as well as for intentions or preparatory acts that are not risky. Alexander and Ferzan discuss the reasons for imposing risks that negate or mitigate culpability, the individuation of crimes, and omissions. (shrink)

In what follows, I shall presuppose the ecumenical core of the causal powers metaphysics. The argument of this paper concerns what may appear at first to be a wholly unrelated matter, the metaphysics of free will. However, an adequate account of freedom requires, in my judgment, a notion of a distinctive variety of causal power, one which tradition dubs ‘agent-causal power’. I will first develop this notion and clarify its relationship to other notions. I will then respond to a number (...) of objections either to the possibility of a power so explicated or to its sufficiency for grounding an adequate account of human freedom. (shrink)

This is the first book to systematically examine the underlying theory of evidence in Anglo-American legal systems. Stein develops a detailed and innovative theory which sets aside the traditional vision of evidence law as facilitating the discovery of the truth. Combining probability theory, epistemology, economic analysis, and moral philosophy, he argues instead that the fundamental purpose of evidence law is to apportion the risk of error in conditions of uncertainty.

Many proponents of libertarian freedom assume that the free choices we might make have particular objective probabilities of occurring. In this paper, I examine two common motivations for positing such probabilities: first, to account for the phenomenal character of decision-making, in which our reasons seem to have particular strengths to incline us to act, and second, to naturalize the role of reasons in influencing our decisions, such that they have a place in the causal order as we know it. I (...) argue, however, that neither introspective reflection nor the metaphysics of causation gives us reason for thinking there are such particular objective probabilities of our free choices. (shrink)

The common cause principle states that correlations have prior common causes which screen off those correlations. I argue that the common cause principle is false in many circumstances, some of which are very general. I then suggest that more restricted versions of the common cause principle might hold, and I prove such a restricted version.

Humpty, an enthusiastic football fan, is sued for gate-crashing a local football match. He was seen by Alice sneaking through the fence. Alice's visual identification ability is tested and shown to be accurate in nine times out of ten. This case seems straightforward and finding Humpty liable seems intuitively right. In another football match, Hatter, another enthusiastic football fan, is also sued for gate-crashing. This time, the only evidence available is that just one hundred tickets had been sold whilst yet (...) a thousand spectators were counted. Hatter being sued for gate-crashing is based on the fact that nine out of ten spectators gate-crashed. Surprisingly, this case is relatively straightforward too: finding Hatter liable based on this statistical evidence seems intuitively wrong. It is surprising because in both cases, at least prima facie, the risk of error is similar. In both cases, there is a one in ten chance that finding liability would be mistaken. A common intuitive response to the gate-crasher paradox is that the statistical evidence does not prove anything about the particular individual. Whilst this explanation may have an intuitive appeal, it merely serves as a starting point because it immediately begs the question as to why the statistical evidence fails. Fortunately, some writers have tried to develop this intuition into a more detailed and elucidated account. In particular, Zuckerman has argued that imposing liability based on such statistical evidence is a form of corporate liability, which contradicts the commitment of the legal system to an individualised justice. Wasserman, on the other hand, has suggested that using statistical evidence fails to respect the individuality and autonomy of the litigant because it treats the individual as a predetermined mechanism rather than an autonomous individual who is capable of determining his own conduct. Whilst each account suggests a slightly different answer, both put the individual at the centre of their explanations (either through the individualised justice or the individual's autonomy). This paper critically examines whether these individuality accounts could serve as an explanation for this paradox and a justification for restricting the usage of statistical evidence in some circumstances. I will argue that, whilst the individuality accounts have promising potential to provide such explanation and justification, they also suffer from several substantial deficiencies that need to be overcome before this potential is realised. This paper therefore lays the requirements and perhaps the foundations for a comprehensive answer. (shrink)

Many people have an intuition that something is fundamentally different between statistical evidence (e.g. per cent of the market-share) and non-statistical evidence (e.g. eyewitnesses). The intuitive difference between these two types of evidence is demonstrated by empirical research, according to which people tend to disregard the background statistical evidence when non-statistical evidence is available. A popular example is the red/blue bus scenario, in which a lady who was hit by an unidentified bus claims damages from the Red Bus Company on (...) the basis that sixty per cent of the buses in that area are operated by that company. To many, it would seem intuitively wrong to impose liability based solely on this evidence. As a result, it is sometimes thought that statistical evidence is inferior to non-statistical evidence when it is used to prove particular facts in court. The 'epistemic accounts' are attempts to provide a justification for restricting the use of statistical evidence in court by identifying a certain quality that non-statistical evidence has but statistical evidence lacks. The proponents of these accounts share the view that statistical evidence lacks a quality, the effect of which is to make the drawing of inference from the statistical evidence to the particular case epistemologically deficient. Epistemology is the branch of philosophy which addresses questions about the nature, possibility and structure of knowledge, justification, belief and other related conditions. Unlike psychology, which attempts to describe how human beings actually think, epistemology asks how a rational agent ought to think and form his rational beliefs. Epistemology is therefore normative in nature. These accounts are classified as 'epistemic' in this paper because their strategy is to identify a quality that is lacking from statistical evidence which makes it epistemologically unwarranted to establish the fact this evidence is adduced to prove. The paper seeks to show that the existing epistemic accounts fail to provide a justification for restricting the use of statistical evidence in court. The paper presents the major epistemic accounts and argues that each suffers from substantial problems which make it unsuccessful. Some of these accounts are under-inclusive: the alleged epistemic deficiency is not found in some types of evidence which are clearly statistical. Other accounts are over-inclusive: their alleged epistemic deficiency applies to non-statistical evidence too. None of the existing accounts successfully establishes an epistemic deficiency from which (only) statistical evidence suffers. This paper does not argue that statistical evidence should be used freely because there is no epistemic difference between statistical and non-statistical evidence. It may well be the case that there is a good justification for not using statistical evidence to determine our legal rights and liabilities, at least in some situations. However, if there is such a justification, it has not been provided by the epistemic accounts. (shrink)

How should we reason with causal relationships? Much recent work on this question has been devoted to the theses (i) that Bayesian nets provide a calculus for causal reasoning and (ii) that we can learn causal relationships by the automated learning of Bayesian nets from observational data. The aim of this book is to..