Is it right to convict a person of a crime on the basis of purely statistical evidence? Many who have considered this question agree that it is not, posing a direct challenge to legal probabilism – the claim that the criminal standard of proof should be understood in terms of a high probability threshold. Some defenders of legal probabilism have, however, held their ground: Schoeman (1987) argues that there are no clear epistemic or moral problems with (...) convictions based on purely statistical evidence, and speculates that our aversion to such convictions may be nothing more than an irrational bias. More recently, Hedden and Colyvan (2019, section VI) describe our reluctance to convict on the basis of purely statistical evidence as an ‘intuition’, but suggest that there may be no ‘in principle’ problem with such convictions (see also Papineau, forthcoming, section 6). In this paper, I argue that there is, in some cases, an in principle problem with a conviction based upon statistical evidence alone – namely, it commits us to a precedent which, if consistently followed through, could lead to the deliberate conviction of an innocent person. I conclude with some reflections on the idea that the criminal justice system should strive to maximise the accuracy of its verdicts – and the related idea that we should each strive to maximise the accuracy of our beliefs. (shrink)

Journal of Political Philosophy, EarlyView.

Journal of Political Philosophy, EarlyView.

Discusses whether legal proof is merely probabilistic, focusing on the famous proof paradox.

In this paper, I provide an argument for rejecting Sarah Moss's recent account of legal proof. Moss's account is attractive in a number of ways. It provides a new version of a knowledge-based theory of legal proof that elegantly resolves a number of puzzles about mere statistical evidence in the law. Moreover, the account promises to have attractive implications for social and moral philosophy, in particular about the impermissibility of racial profiling and other harmful kinds of statistical generalisation. (...) In this paper, I show that Moss's account of legal proof crucially depends on a moral norm called the rule of consideration. I argue that we have a number of reasons to be sceptical of this rule. Once we reject the rule, it is not clear that Moss's account of legal proof is either plausible or attractive. (shrink)

Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. In this book, Moss argues that in addition to full beliefs, credences can constitute knowledge. For instance, your .4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, (...) but of probabilistic contents. -/- The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other. (shrink)

Legal probabilism is the view that juridical fact-finding should be modeled using Bayesian methods. One of the alternatives to it is the narration view, according to which instead we should conceptualize the process in terms of competing narrations of what happened. The goal of this paper is to develop a reconciliatory account, on which the narration view is construed from the Bayesian perspective within the framework of formal Bayesian epistemology.

An annotated bibliography of legal epistemology.

When surprising events occur, people naturally try to generate explanations of them. Such explanations usually involve hypothesizing causes that have the events as effects. Reasoning from effects to prior causes is found in many domains, including: Social reasoning: when friends are acting strange, we conjecture about what might be bothering them. Legal reasoning: when a crime has been committed, jurors must decide whether the prosecution's case gives a convincing explanation of the evidence. Medical diagnosis: given a set of symptoms, (...) a physician tries to decide what disease or diseases produced them. Fault diagnosis in manufacturing: when a piece of equipment breaks down, a trouble shooter must try to determine the cause of the breakdown. Scientific theory evaluation: scientists seek an acceptable theory to explain experimental evidence. What is the nature of such reasoning? (shrink)

It is argued that the standard way that the criminal justice debate regarding the permissible extent of wrongful convictions is cast is fundamentally flawed. In particular, it is claimed that there is an inherent danger in focussing our attention in this debate on different ways of measuring the probabilistic likelihood of wrongful conviction and then evaluating whether these probabilities are unacceptably high. This is because such probabilistic measures are clumsy ways of capturing the level of risk involved, to the extent (...) that a defendant can be subject to an unacceptably high level of legal risk in this regard even where the relevant probabilities are very low. An alternative conception of legal risk – one that is primarily cast along modal rather than probabilistic lines – is set out which offers a much better way of framing the debate regarding what would be an acceptable level of wrongful conviction. It is further argued that with this modal conception of legal risk in play we can capture an important necessary condition that should be imposed on legal evidence, one that has application beyond the context of the criminal trial. (shrink)

When the likelihood ratio approach is employed for evidential reasoning in law, it is often necessary to employ subjective probabilities, which are probabilities derived from the opinions and judgement of a human. At least three concerns arise from the use of subjective probabilities in legal applications. Firstly, human beliefs concerning probabilities can be vague, ambiguous and inaccurate. Secondly, the impact of this vagueness, ambiguity and inaccuracy on the outcome of a probabilistic analysis is not necessarily fully understood. Thirdly, the (...) provenance of subjective probabilities and the associated potential sources of vagueness, ambiguity and inaccuracy tend to be poorly understood, making it difficult for the outcome of probabilistic reasoning to be explained and validated, which is crucial in legal applications. The former two concerns have been addressed by a wide body of research in AI. The latter, however, has received little attention. This paper presents a novel approach to employ argumentation to reason about probability distributions in probabilistic models. It introduces a range of argumentation schemes and corresponding sets of critical questions for the construction and validation of argument models that define sets of probability distributions. By means of an extended example, the paper demonstrates how the approach, argumentation schemes and critical questions can be employed for the development of models and their validation in legal applications of the likelihood ratio approach to evidential reasoning. (shrink)

In this paper I argue that economic theories have never been able to provide a coherent explanation of the causation requirement in tort law. The economic characterization of this requirement faces insurmountable difficulties, because discourse on tort liability cannot be reduced to a cost-benefit analysis without a loss of meaning. More seriously, I try to show that by describing causation in economic terms, economic theories offer an image of the practice in which the participants incur in logical contradictions and develop (...) patterns of inference that are far from intuitive. For this reason, efficiency cannot be the fundamental principle underlying tort law. Finally, I suggest that economic analysis of law can provide a genuine explanation of certain aspects of legal practice if it relinquishes its reductionist claims. (shrink)

I discuss the knowledge account of legal proof in Moss (2023) and develop an alternative. The unifying thread throughout this article are reflections on the beyond reasonable doubt (BRD) standard of proof. In Section 1, I will introduce the details of Moss’s account and how she motivates it via the BRD standard. In Section 2, I will argue that there are important disanalogies between BRD and knowledge that undermine Moss’s argument. There is however another motivation for the knowledge account: (...) combined with auxiliary claims, that is probabilistic knowledge and moral encroachment, it can provide a general solution to the puzzle of statistical evidence. Section 3 spells out the details. In Section 4, I suggest to combine the knowledge account with pragmatic encroachment, instead of moral encroachment, in order to stay clear of the thorny issues whether corporations have moral rights. In Section 5, I argue that the verdicts of Moss’s account in cases of false justified beliefs and non-luminous knowledge conflict with the BRD standard and thus call for abandoning the account. Based on the social function of the BRD standard, I suggest a replacement for the knowledge account that is also just as potent as a general solution for the puzzle of statistical evidence. While I will grant that knowledge is neither always necessary nor always sufficient for convictions, I will argue that the concept of knowledge nonetheless plays a significant and ineliminable role in legal decision-making. (shrink)

Legal judgments are complex in nature and hence a brief summary of the judgment, known as a headnote , is generated by experts to enable quick perusal. Headnote generation is a time consuming process and there have been attempts made at automating the process. The difficulty in interpreting such automatically generated summaries is that they are not coherent and do not convey the relative relevance of the various components of the judgment. A legal judgment can be segmented into (...) coherent chunks based on the rhetorical roles played by the sentences. In this paper, a comprehensive system is proposed for labeling sentences with their rhetorical roles and extracting structured head notes automatically from legal judgments. An annotated data set was created with the help of legal experts and used as training data. A machine learning technique, Conditional Random Field, is applied to perform document segmentation by identifying the rhetorical roles. The present work also describes the application of probabilistic models for the extraction of key sentences and composing the relevant chunks in the form of a headnote. The understanding of basic structures and distinct segments is shown to improve the final presentation of the summary. Moreover, by adding simple additional features the system can be extended to other legal sub-domains. The proposed system has been empirically evaluated and found to be highly effective on both the segmentation and summarization tasks. The final summary generated with underlying rhetorical roles improves the readability and efficiency of the system. (shrink)

In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge or jury. In previous work, techniques were proposed to represent narratives in a Bayesian network and to use narratives as a basis for systematizing the construction of a Bayesian network for a (...) class='Hi'>legal case. In this paper, these techniques are combined to form a design method for constructing a Bayesian network based on narratives. This design method is evaluated by means of an extensive case study concerning the notorious Dutch case of the Anjum murders. (shrink)

Legal reasoning requires identification through search of authoritative legal texts (such as statutes, constitutions, or prior judicial opinions) that apply to a given legal question. In this paper, using a network representation of US Supreme Court opinions that integrates citation connectivity and topical similarity, we model the activity of law search as an organizing principle in the evolution of the corpus of legal texts. The network model and (parametrized) probabilistic search behavior generates a Pagerank-style ranking of (...) the texts that in turn gives rise to a natural geometry of the opinion corpus. This enables us to then measure the ways in which new judicial opinions affect the topography of the network and its future evolution. While we deploy it here on the US Supreme Court opinion corpus, there are obvious extensions to large evolving bodies of legal text (or text corpora in general). The model is a proxy for the way in which new opinions influence the search behavior of litigants and judges and thus affect the law. This type of “legal search effect” is a new legal consequence of research practice that has not been previously identified in jurisprudential thought and has never before been subject to empirical analysis. We quantitatively estimate the extent of this effect and find significant relationships between search-related network structures and propensity of future citation. This finding indicates that “search influence” is a pathway through which judicial opinions can affect future legal development. (shrink)

Illuminates legal reasoning -- and its justification At least since plato and Aristotle, thinkers have pondered the relationship between philosophical arguments and the "sophistical" arguments offered by the Sophists -- who were the first professional lawyers. Judges wield substantial political power, and the justifications they offer for their decisions are a vital means by which citizens can assess the legitimacy of how that power is exercised. However, to evaluate judicial justifications requires close attention to the method of reasoning behind (...) decisions. This new collection illuminates and explains the political and moral importance in justifying the exercise of judicial power. Explores enduring questions Focusing on work over the past century, the essays address important recurring questions, such as: When a judge or a lawyer reasons to a conclusion about what is legally required in a given case, must he also ask what is morally required? To what extent do a judge's personal, political, or moral biases affect his legal reasoning? What is the impact of such biases? Can all such biases be avoided? Is legal reasoning similar to reasoning in mathematics, logic, and linguistics, the physical sciences, the social sciences, or literature and history? Do formal logical modes of argument play any roles in legal reasoning? Solid coverage, well organized The articles were chosen to present some of the most influential works on the topic, as well as less familiar works that are thought provoking and informative. Each volume also offers a representative range of theoretical approaches to its topic, contains an introduction that locates the subject within the larger framework oftheories of legal reasoning and jurisprudence, and includes bibliographical notes on further readings. Many 19th century legal theorists argued that deduction is the central mode of legal reasoning, and that legal argument is like a deductive proof in mathematics or logic. They were attracted to this "deductivist" concept because it suggested that legal reasoning could be politically and morally neutral. This volume brings together some of the most thought-provoking articles on both sides of the debate. It also contains several leading articles that explain the role of probabilistic judgments and presumptions in various types of legal arguments, including the laws of evidence and criminal procedure. The collection is a solid introduction to the basic modes of logical argument in legal reasoning. (shrink)

Walton’s book aims to supply a fresh method for evaluating logical reasoning and legal argumentation. Drawn from philosophy, law and science, Walton’s method rests on a theory of “plausibilistic” reasoning or “probabilism”. According to plausibilistic reasoning, we can logically infer conclusions from a set of premises even though the premises are neither definite nor of a measurable probability. We may tentatively draw such inferences so long as they rest on generally valid premises. To illustrate this method, Walton cites (...) a famous example from Wigmore: A man had no money before a robbery, but suddenly came into a great deal of money following the robbery. It is therefore plausible to infer that the man committed the robbery. (shrink)

The new evidence scholarship addresses three distinct approaches: legal probabilism, Bayesian decision theory and relative plausibility theory. Each has major insights to offer, but none seems satisfactory as it stands. This paper proposes that relative plausibility theory be modified in two substantial ways. The first is by defining its key concept of plausibility, hitherto treated as primitive, by generalising the standard axioms of probability. The second is by complementing the descriptive component of the theory with a normative decision (...) theory adapted to legal process. Because this version of decision theory is based on plausibilities rather than probabilities, it generates plausibilistic expectations as outputs. Because these outputs are comparable, they function as relative plausibilities. Hence the resulting framework is an extension of relative plausibility theory, but it retains deep ties to legal probabilism, through the proposed definition of plausibility, and to Bayesian decision theory, through the normative use of decision theory. (shrink)

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)

Medicine, like law, is a pragmatic, probabilistic activity. Both require that decisions be made on the basis of available evidence, within a limited time. In contrast to law, medicine, particularly evidence-based medicine as it is currently practiced, aspires to a scientific standard of proof, one that is more certain than the standards of proof courts apply in civil and criminal proceedings. But medicine, as Dr. William Osler put it, is an "art of probabilities," or at best, a "science of uncertainty." (...) One can better practice medicine by using other evidentiary standards in addition to the "scientific." To employ only the scientific standard of proof is inappropriate, if not impossible; furthermore, as this review will show, its application in medicine is fraught with bias. Evidence is information. It supports or undermines a proposition, whether a hypothesis in science, a diagnosis in medicine, or a fact or point in question in a legal investigation. In medicine, physicians marshal evidence to make decisions on how to best prevent, diagnose, and treat disease, and improve health. In law, courts decide the facts and render justice. Judges and juries assess evidence to establish liability, to settle custody and medical issues, and to determine a defendant's guilt or innocence. (shrink)

This work contrasts Giovanni Sartor’s view of inferential semantics of legal concepts with a probabilistic model of theory formation. The work further explores possibilities of implementing Kemp’s probabilistic model of theory formation in the context of mapping legal concepts between two individual legal systems. For implementing the legal concept mapping, we propose a cross-categorization approach that combines three mathematical models: the Bayesian Model of Generalization, the probabilistic model of theory formation, i.e., the Infinite Relational Model first (...) introduced by Kemp et al. and its extended model, i.e., the normal-IRM proposed by Herlau et al.. We apply our cross-categorization approach to datasets where legal concepts related to educational systems are respectively defined by the Japanese- and the Danish authorities according to the International Standard Classification of Education. The main contribution of this work is the proposal of a conceptual framework of the cross-categorization approach that, inspired by Sartor, attempts to explain reasoner’s inferential mechanisms. (shrink)

The risks taken into account in legal decision-mak- ing are, often, matters of life and death, but the way we think about risk is flawed. This is a problem. The dominant account of how emotions are involved in risky decision-making follows the standard probabilistic account of risk. If we entertain a modal ac- count of risk, however, this changes the way in which a host of legal actors—members of the jury, judges, defendants, lawyers, legislators, regulators, and police—ought to (...) think about how emotions impact risk evaluation. In what follows, I examine what taking a modal account of risk would mean for the way we under- stand emotions in the evaluation of legal risk: specifically, the risk of wrongful conviction. The present chapter draws on contemporary research in the epistemology of risk to examine how emotions can influence the evaluation of legal risk. I first review a distinction between two understandings of risk—the probabilistic account and the modal account—and demonstrate how the probabilistic account is in- complete. Next, I highlight how emotion can be seen to mediate decision-making in a series of empirical studies on the assessment of gruesome photographic evidence. I then analyse the standard accounts of how emotions play a role in risk assessment, which build upon a probabilistic account of risk. A modal account of risk and emotion is then offered, demonstrating the ways in which emotions can contribute to the evaluation of risk understood modally. Finally, I consider what legal practices and structures need to be refined or abandoned in order to facilitate the condi- tions most conducive to harnessing the evaluative power of emo- tions in legal decision-making. (shrink)

This thesis examines some of the legal philosophical issues that are implicated in the problem of outcome luck. In the context of criminal law, the problem asks whether we should hold agents criminally liable for the consequences of their actions given that those consequences are never wholly within anyone’s control. I conclude that outcomes should matter to an agent’s liability and punishment, and I make this argument indirectly by examining some of the foundational questions in legal theory. The (...) thesis begins by considering a current trend in some areas of philosophy. This trend involves attempts to address philosophical problems surrounding luck by doing conceptual analyses on the nature of luck. Chapter 1 critically examines modal theories, which conceptualize luck, as well as the related concept of risk, in terms of close possible worlds rather than probabilistic likelihood. I argue that not only are modal theories uninformative, but conceptual analyses on luck are unhelpful in addressing philosophical questions surrounding luck. Chapter 2 then returns to the traditional notion of luck as lack of control, and focuses on the relationship between luck, risk, and culpability. Some theorists argue that culpability, for any offence, is in part a function of the degree of risk the agent imposes on others. In the context of criminal law, degrees of luck and risk can both be understood in terms of degrees of control, so the suggestion that culpability is a function of the level of risk imposed (and thus of the degree of control an agent exercises) is attractive for insulating culpability judgments from luck. However, I argue that this view is mistaken because culpability is only sensitive to risk in reckless actions, but not in purposeful actions. The problem of outcome luck may raise different questions for reckless actions and purposeful actions. Chapter 3 looks at the mens rea element of criminal attempts, which is crucial for understanding the problem of luck in the context of purposeful actions. I discuss a variation of what are sometimes referred to as impossible attempts, which have helped shape current English law. I argue that the current doctrine is largely correct, and that perhaps with the exception of few paradigm sexual offences, the mens rea element for attempts should require a direct intention as to the consequence element of an offence, and knowledge or belief as to the circumstance element of that offence. Chapters 4 and 5 then look at normative justifications of criminal punishment. In order to understand whether outcomes should matter for punishment, we must first understand whether and why punishment is an appropriate response to criminal offending. Here, I defend a communicative theory, where punishment is a communicative process between the offender, the political community, and the victim. What punishment communicates is the appropriate degree of censure that is warranted in response to the offender’s wrongdoing. And in doing this, it publicly recognizes the wrong that has been committed by the offender. Chapter 4 offers a detailed explanation of this account, and argues that the political community’s recognition of wrongdoing is a valuable aim of communication. Chapter 5 then takes up a crucial challenge against communicative theories of punishment, which is that such theories fail to take crime prevention seriously. Against this criticism, I will show that general prevention can in fact be an essential part of communicative punishment. And I will show that it is specifically the political community’s recognition of wrongdoing that entails punishment’s preventive aims. (shrink)

Dahlman analyzes the case with a version of Bayes’ rule that can handle dependencies. He claims that his method can help a fact finder avoid various kinds of bias in probabilistic reasoning, and he identifies occurrences of these biases in the analyzed decision. While a mathematical analysis may give a false impression of objectivity to fact finders, Dahlman claims as a benefit that it forces to make assumptions explicit, which can then be scrutinized.

In criminal trials, evidence often involves a degree of uncertainty and decision-making includes moving from the initial presumption of innocence to inference about guilt based on that evidence. The jurors’ ability to combine evidence and make accurate intuitive probabilistic judgments underpins this process. Previous research has shown that errors in probabilistic reasoning can be explained by a misalignment of the evidence presented with the intuitive causal models that people construct. This has been explored in abstract and context-free situations. However, less (...) is known about how people interpret evidence in context-rich situations such as legal cases. The present study examined participants’ intuitive probabilistic reasoning in legal contexts and assessed how people’s causal models underlie the process of belief updating in the light of new evidence. The study assessed whether participants update beliefs in line with Bayesian norms and if errors in belief updating can be explained by the causal structures underpinning the evidence integration process. The study was based on a recent case in England where a couple was accused of intentionally harming their baby but was eventually exonerated because the child’s symptoms were found to be caused by a rare blood disorder. Participants were presented with a range of evidence, one piece at a time, including physical evidence and reports from experts. Participants made probability judgments about the abuse and disorder as causes of the child’s symptoms. Subjective probability judgments were compared against Bayesian norms. The causal models constructed by participants were also elicited. Results showed that overall participants revised their beliefs appropriately in the right direction based on evidence. However, this revision was done without exact Bayesian computation and errors were observed in estimating the weight of evidence. Errors in probabilistic judgments were partly accounted for, by differences in the causal models representing the evidence. Our findings suggest that understanding causal models that guide people’s judgments may help shed light on errors made in evidence integration and potentially identify ways to address accuracy in judgment. (shrink)

In ordinary circumstances, we can assess the worth of evidence well enough without benefit of any theory; but when evidence is especially complex, ambiguous, or emotionally disturbing—as it often is in legal contexts—epistemological theory may be helpful. A legal fact-finder is asked to determine whether the proposition that the defendant is guilty, or is liable, is established to the required degree of proof by the [admissible] evidence presented; i.e., to make an epistemological appraisal. The foundherentist theory developed in (...) Evidence and Inquiry can help us understand what this means; and reveals that degrees of proof cannot be construed as mathematical probabilities: a point illustrated by comparing the advantages of a foundherentist analysis with the disadvantages of probabilistic analyses of the evidence in the Sacco and Vanzetti case (1921), and of the role of the statistical evidence in Collins (1968). (shrink)

In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In this paper we propose a combination of two approaches, combining Bayesian networks with scenarios. Whereas a Bayesian network is a popular tool for analysing (...) parts of a case, constructing and understanding a network for an entire case is not straightforward. We propose an explanation method for understanding a Bayesian network in terms of scenarios. This method builds on a previously proposed construction method, which we slightly adapt with the use of scenario schemes for the purpose of explaining. The resulting structure is explained in terms of scenarios, scenario quality and evidential support. A probabilistic interpretation of scenario quality is provided using the concept of scenario schemes. Finally, the method is evaluated by means of a case study. (shrink)

Substantial advancement in the diagnosis and treatment of psychiatric disorders may come from assembling diverse data streams from clinical notes, neuroimaging, genetics, and real-time digital footprints from smartphones and wearable devices. This is called “deep phenotyping” and often involves machine learning. We argue that incidental findings arising in deep phenotyping research have certain special, morally and legally salient features: They are specific, actionable, numerous, and probabilistic. We consider ethical and legal implications of these features and propose a practical ethics (...) strategy for managing them. (shrink)

Lennart Åqvist (1992) proposed a logical theory of legal evidence, based on the Bolding-Ekelöf of degrees of evidential strength. This paper reformulates Åqvist's model in terms of the probabilistic version of the kappa calculus. Proving its acceptability in the legal context is beyond the present scope, but the epistemological debate about Bayesian Law isclearly relevant. While the present model is a possible link to that lineof inquiry, we offer some considerations about the broader picture of thepotential of AI (...) & Law in the evidentiary context. Whereas probabilisticreasoning is well-researched in AI, calculations about the threshold ofpersuasion in litigation, whatever their value, are just the tip of theiceberg. The bulk of the modeling desiderata is arguably elsewhere, if one isto ideally make the most of AI's distinctive contribution as envisaged forlegal evidence research. (shrink)

In legal proceedings, a fact-finder needs to decide whether a defendant is guilty or not based on probabilistic evidence. We defend the thesis that the defendant should be found guilty just in case it is rational for the fact-finder to believe that the defendant is guilty. We draw on Leitgeb’s stability theory for an appropriate notion of rational belief and show how our thesis solves the problem of statistical evidence. Finally, we defend our account of legal proof against (...) challenges from Staffel and compare it to a recent competitor put forth by Moss. (shrink)

The Adequate Cause Theory: On the relation of Philosophical and Legal Concepts of Causality. The paper discusses the first explicit and logically convincing introduction of a concept of probabilistic causality into legal theories of causation in Germany by Johannes von Kries (1888). First, it is shown how this step was prepared by the failure of the philosophical analysis of causation which took its leading examples from physics to overcome the difficulties which presented themselves in cases of "irreducible multicausality". (...) Secondly, I give the basic ideas of Kries's connection of causal theory and probability theory by presenting his concept of "scope" ("Spielraum"). Finally, I turn to some concepts which are still controversively discussed in legal contexts and which exhibit the logical structure analysed by Kries. It is shown that a certain indefiniteness of the relevant distinctions, which cannot be overcome, does not paralyse their being useful. (shrink)

I discuss the attitude of Jewish law sources from the 2nd–:5th centuries to the imprecision of measurement. I review a problem that the Talmud refers to, somewhat obscurely, as impossible reduction. This problem arises when a legal rule specifies an object by referring to a maximized measurement function, e.g., when a rule applies to the largest part of a divided whole, or to the first incidence that occurs, etc. A problem that is often mentioned is whether there might be (...) hypothetical situations involving more than one maximal value of the relevant measurement and, given such situations, what is the pertinent legal rule. Presumption of simultaneous occurrences or equally measured values are also a source of embarrassment to modern legal systems, in situations exemplified in the paper, where law determines a preference based on measured values. I contend that the Talmudic sources discussing the problem of impossible reduction were guided by primitive insights compatible with fuzzy logic presentation of the inevitable uncertainty involved in measurement. I maintain that fuzzy models of data are compatible with a positivistic epistemology, which refuses to assume any precision in the extra-conscious world that may not be captured by observation and measurement. I therefore propose this view as the preferred interpretation of the Talmudic notion of impossible reduction. Attributing a fuzzy world view to the Talmudic authorities is meant not only to increase our understanding of the Talmud but, in so doing, also to demonstrate that fuzzy notions are entrenched in our practical reasoning. If Talmudic sages did indeed conceive the results of measurements in terms of fuzzy numbers, then equality between the results of measurements had to be more complicated than crisp equations. The problem of impossible reduction could lie in fuzzy sets with an empty core or whose membership functions were only partly congruent. Reduction is impossible may thus be reconstructed as there is no core to the intersection of two measures. I describe Dirichlet maps for fuzzy measurements of distance as a rough partition of the universe, where for any region A there may be a non-empty set of - _A, where the problem of impossible reduction applies. This model may easily be combined with probabilistic extention. The possibility of adopting practical decision standards based on -cuts is discussed in this context. I propose to characterize the uncertainty that was presumably capped by the old sages as U- uncertainty, defined, for a non-empty fuzzy set A on the set of real numbers, whose -cuts are intervals of real numbers, as U = 1/h 0 h log [1+]d, where h is the largest membership value obtained by any element of A and is the measure of the -cut of A defined by the Lebesge integral of its characteristic function. (shrink)

Many who think that naked statistical evidence alone is inadequate for a trial verdict think that use of probability is the problem, and something other than probability – knowledge, full belief, causal relations – is the solution. I argue that the issue of whether naked statistical evidence is weak can be formulated within the probabilistic idiom, as the question whether likelihoods or only posterior probabilities should be taken into account in our judgment of a case. This question also identifies a (...) major difference between the Process Reliabilist and Probabilistic Tracking views of knowledge and other concepts. Though both are externalist, and probabilistic, epistemic theories, Tracking does and Process Reliabilism does not put conditions on likelihoods. So Tracking implies that a naked statistic is not adequate evidence about an individual, and does not yield knowledge, whereas the Reliabilist thinks it gives justified belief and knowledge. Not only does the Tracking view imply that naked statistical evidence is insufficient for a verdict, but it gives us resources to explain why, in terms of risk and the special conditions of a trial. (shrink)

The rapidly increasing role of automation throughout the economy, culture and our personal lives has generated a large literature on the risks of algorithmic decision-making, particularly in high-stakes legal settings. Algorithmic tools are charged with bias, shrouded in secrecy, and frequently difficult to interpret. However, these criticisms have tended to focus on particular implementations, specific predictive techniques, and the idiosyncrasies of the American legal-regulatory regime. They do not address the more fundamental unease about the prospect that we might (...) one day replace judges with algorithms, no matter how fair, transparent, and intelligible they become. The aim of this paper is to propose an account of the source of that unease, and to evaluate its plausibility. I trace foundational unease with algorithmic decision-making in the law to the powerful intuition that there is a basic moral and legal difference between showing that something is true of many people just like you and showing that it is true of you. Human judgment attends to the exception; automation insists on blindly applying the rule. I show how this intuitive thought is connected to both epistemological arguments about the value of statistical evidence, as well as to court-centered conceptions of the rule of law. Unease with algorithmic decision-making in the law thus draws on an intuitive principle that underpins a disparate range of views in legal philosophy. This suggests the principle is deeply ingrained. Nonetheless, I argue that the powerful intuition is not as decisive as it may seem, and indeed runs into significant epistemological and normative challenges. At an epistemological level, I show how concerns about statistical evidence's ability to track the truth can be resolved by adopting a probabilistic, rather than modal, conception of truth-tracking. At a normative level, commitment to highly individualized decision-making co-exists with equally ingrained and competing principles, such as consistent application of law. This suggests that the “rule of law” may not identify a discrete set of institutional arrangements, as proponents of a court-centric conception would have it, but rather a more loosely defined set of values that could potentially be operationalized in multiple ways, including through some level of algorithmic adjudication. Although the prospect of replacing judges with algorithms is indeed unsettling, it does not necessarily entail unreasonable verdicts or an attack on the rule of law. (shrink)

How does a Muslim jurist think the law and how, accordingly, he judges a fact? Using Alice in Wonderland as hermeneutical device to explore the logic of fiqh, this article identifies a divergence between Western and Islamic legal thinking in the application of abduction as key form of inference in the law of Islam. In particular, looking at the fact/law relation in symbolic terms, the article highlights how, while a dichotomy between fact and law characterizes Western legal thinking, (...) fiqh upholds a connection between the “real” and the “right”, where the effort in understanding sharī‘ah postulates the actualization of the “rule” in God’s creation. Thus, if sharī‘ahpre-scribes the Law, not only is the rule discovered through the sources, but the right has to be justified through a verdict de-scribing the fact, for the law to be validly stated for the given situation. In this sense, abduction as explanatory “hypothesis” and “inference to the best explanation” of sharī‘ah provides an account for the probabilistic nature of fiqh, its ramification through verdicts, as well as for the epistemic and narrative function of the tradition as core aspects of the logic of Islamic law. At the same time, doubts can be raised about the compatibility between this logic and the deductive logic of modern state law, as a sub-product of Western legal thinking. (shrink)

Agenda Relevance is the first volume in the authors' omnibus investigation of the logic of practical reasoning, under the collective title, A Practical Logic of Cognitive Systems. In this highly original approach, practical reasoning is identified as reasoning performed with comparatively few cognitive assets, including resources such as information, time and computational capacity. Unlike what is proposed in optimization models of human cognition, a practical reasoner lacks perfect information, boundless time and unconstrained access to computational complexity. The practical reasoner is (...) therefore obliged to be a cognitive economizer and to achieve his cognitive ends with considerable efficiency. Accordingly, the practical reasoner avails himself of various scarce-resource compensation strategies. He also possesses neurocognitive traits that abet him in his reasoning tasks. Prominent among these is the practical agent's striking (though not perfect) adeptness at evading irrelevant information and staying on task. On the approach taken here, irrelevancies are impediments to the attainment of cognitive ends. Thus, in its most basic sense, relevant information is cognitively helpful information. Information can then be said to be relevant for a practical reasoner to the extent that it advances or closes some cognitive agenda of his. The book explores this idea with a conceptual detail and nuance not seen the standard semantic, probabilistic and pragmatic approaches to relevance; but wherever possible, the authors seek to integrate alternative conceptions rather than reject them outright. A further attraction of the agenda-relevance approach is the extent to which its principal conceptual findings lend themselves to technically sophisticated re-expression in formal models that marshal the resources of time and action logics and label led deductive systems. Agenda Relevance is necessary reading for researchers in logic, belief dynamics, computer science, AI, psychology and neuroscience, linguistics, argumentation theory, and legal reasoning and forensic science, and will repay study by graduate students and senior undergraduates in these same fields. Key features: relevance action and agendas practical reasoning belief dynamics non-classical logics labelled deductive systems. (shrink)

In the Principles of the Penal Code, Jeremy Bentham described offences that he labelled presumed or evidentiary. The conduct penalized under such offences is punished not because it is intrinsically wrong, but because it probabilistically indicates the presence of an intrinsic wrong. Bentham was sceptical of the need to create offences, but grudgingly accepted their value in light of deficiencies in procedure and the judiciary. These days the scepticism is even greater, with courts and commentators in the United States, Canada, (...) the United Kingdom and elsewhere believing that such offences deny a defendant the right to establish that he did not engage in the conduct that the presumed offence probabilistically but not necessarily indicates. On closer analysis, however, such scepticism appears unjustified. Almost all offences, and indeed almost all legal rules, are premised on a probabilistic relationship between the behaviour the rule encompasses and the behaviour that is the rule-maker's real concern. Presumed offences may make this relationship especially obvious, but it is a relationship that exists whenever the law operates by the use of rules. (shrink)

The paper addresses charges of risk and loss aversion as well as of irrationality directed against the precautionary principle, by providing an epistemic analysis of its specific role in the safety law system. In particular, I contend that: 1) risk aversion is not a form of irrational or biased behaviour; 2) both risk and loss aversion regard the form of the utility function, whereas PP rather regards the information on which to base the decision; 3) thus PP has formally nothing (...) to do with risk or loss aversion but rather with risk awareness; 4) PP removes a fictional construct in the legal system, according to which any hazard should be ignored and denied until it is scientifically proven; 5) the quandary originates in the tension between current methods of evidence evaluation, and the logic underlying PP which demands for a probabilistic epistemology. (shrink)

In this article it is argued that the standard theoretical account of risk in the contemporary literature, which is cast along probabilistic lines, is flawed, in that it is unable to account for a particular kind of risk. In its place a modal account of risk is offered. Two applications of the modal account of risk are then explored. First, to epistemology, via the defence of an anti-risk condition on knowledge in place of the normal anti-luck condition. Second, to (...) class='Hi'>legal theory, where it is shown that this account of risk can cast light on the debate regarding the extent to which a criminal justice system can countenance the possibility of wrongful convictions. (shrink)

The first reference on rationality that integrates accounts from psychology and philosophy, covering descriptive and normative theories from both disciplines. Both analytic philosophy and cognitive psychology have made dramatic advances in understanding rationality, but there has been little interaction between the disciplines. This volume offers the first integrated overview of the state of the art in the psychology and philosophy of rationality. Written by leading experts from both disciplines, The Handbook of Rationality covers the main normative and descriptive theories of (...) rationality—how people ought to think, how they actually think, and why we often deviate from what we can call rational. It also offers insights from other fields such as artificial intelligence, economics, the social sciences, and cognitive neuroscience. The Handbook proposes a novel classification system for researchers in human rationality, and it creates new connections between rationality research in philosophy, psychology, and other disciplines. Following the basic distinction between theoretical and practical rationality, the book first considers the theoretical side, including normative and descriptive theories of logical, probabilistic, causal, and defeasible reasoning. It then turns to the practical side, discussing topics such as decision making, bounded rationality, game theory, deontic and legal reasoning, and the relation between rationality and morality. Finally, it covers topics that arise in both theoretical and practical rationality, including visual and spatial thinking, scientific rationality, how children learn to reason rationally, and the connection between intelligence and rationality. (shrink)

Evidential reasoning is hard, and errors can lead to miscarriages of justice with serious consequences. Analytic methods for the correct handling of evidence come in different styles, typically focusing on one of three tools: arguments, scenarios or probabilities. Recent research used Bayesian networks for connecting arguments, scenarios, and probabilities. Well-known issues with Bayesian networks were encountered: More numbers are needed than are available, and there is a risk of misinterpretation of the graph underlying the Bayesian network, for instance as a (...) causal model. The formalism presented here models presumptive arguments about coherent hypotheses that are compared in terms of their strength. No choice is needed between qualitative or quantitative analytic styles, since the formalism can be interpreted with and without numbers. The formalism is applied to key concepts in argumentative, scenario and probabilistic analyses of evidential reasoning, and is illustrated with a fictional crime investigation example based on Alfred Hitchcock’s film ‘To Catch A Thief’. (shrink)

How were reliable predictions made before Pascal and Fermat's discovery of the mathematics of probability in 1654? What methods in law, science, commerce, philosophy, and logic helped us to get at the truth in cases where certainty was not attainable? The book examines how judges, witch inquisitors, and juries evaluated evidence; how scientists weighed reasons for and against scientific theories; and how merchants counted shipwrecks to determine insurance rates. Also included are the problem of induction before Hume, design arguments for (...) the existence of God, and theories on how to evaluate scientific and historical hypotheses. It is explained how Pascal and Fermat's work on chance arose out of legal thought on aleatory contracts. The book interprets pre-Pascalian unquantified probability in a generally objective Bayesian or logical probabilist sense. (shrink)

Society is facing uncertainty on a multitude of domains and levels: usually, reasoning and decisions about political, economic, or health issues must be made under uncertainty. Among various approaches to probability, this chapter presents the coherence approach to probability as a method for uncertainty management. The authors explain the role of uncertainty in the context of important societal issues like legal reasoning and vaccination hesitancy. Finally, the chapter presents selected psychological factors which impact probabilistic representation and reasoning and discusses (...) what society can and cannot learn from the coherence approach from theoretical and practical perspectives. (shrink)

1. Comparing the weight of different evils is highly problematic; neither a positivist, interpretive account nor an exclusively aspirational account is satisfactory. 2. Alexander is correct that choosing a lesser evil is sometimes a mandate, not a mere permission, but the point has wider application than he indicates. 3. Is a choice of lesser but not least evil justifiable? Alexander’s affirmative answer is only partially convincing. 4. Alexander endorses a striking claim: the very notion of a reckless belief or reckless (...) mistake (as to the factual grounds for a justification) is incoherent. This claim is insupportable, but the flaws in his argument demonstrate the complexity of the concept of reckless belief, especially in the context of justification defenses, where the probabilistic aspect of the distinction between permissible and impermissible risk-taking is especially salient. 5. Alexander aptly notes that the legislatively preclusion doctrine (which denies application of the lesser evils defense) creates a fundamental tension between legal actors’ power to articulate the content of the defense and the democratic pedigree of the criminal law. I conclude that genuinely democratic principles can be served by permitting juries considerable latitude to recognize a defense when the legislature has not yet had occasion to formulate an exception, or even, in some cases, by authorizing de facto civil disobedience. (shrink)

Trial by jury is a fundamental feature of democratic governance. But what form should jury decision-making take? I argue against the status quo system in which juries are encouraged and even required to engage in group deliberation as a means to reaching a decision. Jury deliberation is problematic for both theoretical and empirical reasons. On the theoretical front, deliberation destroys the independence of jurors’ judgments that is needed for certain attractive theoretical results. On the empirical front, we have evidence from (...) both legal and non-legal contexts that group deliberation often leads to group judgments that are worse in a number of respects than judgments generated by non-interactional methods of judgment aggregation. Finally, I examine some possible alternatives to free-wheeling jury deliberation, including the constrained and structured deliberation embodied in the DELPHI method, voting, and averaging of probabilistic judgments. (shrink)

The paper addresses charges of risk and loss aversion as well as of irrationality directed against the precautionary principle (PP), by providing an epistemic analysis of its specific role in the safety law system. In particular, I contend that: 1) risk aversion is not a form of irrational or biased behaviour; 2) both risk and loss aversion regard the form of the utility function, whereas PP rather regards the information on which to base the decision; 3) thus PP has formally (...) nothing to do with risk or loss aversion but rather with risk awareness; 4) PP removes a fictional construct in the legal system, according to which any hazard should be ignored and denied until it is scientifically proven; 5) the quandary originates in the tension between current methods of evidence evaluation, and the logic underlying PP which demands for a probabilistic epistemology. (shrink)