Much has been written about recidivist punishments, particularly within the area of criminology. However there is a notorious lack of penal philosophical reflection on this issue. This book attempts to fill that gap by presenting the philosopher’s view on this matter as a way of furthering the debate on recidivist punishments.

Much has been written about recidivist punishments, particularly within the area of criminology. However there is a notorious lack of penal philosophical reflection on this issue. This book attempts to fill that gap by presenting the philosopher’s view on this matter as a way of furthering the debate on recidivist punishments.

Recent scholarship in philosophy of science and technology has shown that scientific and technological decision making are laden with values, including values of a social, political, and/or ethical character. This paper examines the role of value judgments in the design of machine-learning systems generally and in recidivism-prediction algorithms specifically. Drawing on work on inductive and epistemic risk, the paper argues that ML systems are value laden in ways similar to human decision making, because the development and design of ML (...) systems requires human decisions that involve tradeoffs that reflect values. In many cases, these decisions have significant—and, in some cases, disparate—downstream impacts on human lives. After examining an influential court decision regarding the use of proprietary recidivism-prediction algorithms in criminal sentencing, Wisconsin v. Loomis, the paper provides three recommendations for the use of ML in penal systems. (shrink)

Prior research on corporate misconduct pays extensive attention to single misconduct behaviors. However, little research has addressed recidivism – the repeated behaviors of corporate misconduct. Based on institutional theory and using the context of emerging economies where recidivism plays a considerable role, we propose the path dependency of corporate recidivism and suggest that three influential factors exist: internal preconditioning, inter-organizational imitation, and the prevailing external evaluation. Our event history analysis of 1,036 listed companies in China over the (...) period 2001–2008 statistically confirms our hypotheses. We conclude the paper by outlining the implications for both theory and practice. (shrink)

Recent studies have shown that recidivism scoring algorithms like COMPAS have significant racial bias: Black defendants are roughly twice as likely as white defendants to be mistakenly classified as medium- or high-risk. This has led some to call for abolishing COMPAS. But many others have argued that algorithms should instead be given access to a defendant's race, which, perhaps counterintuitively, is likely to improve outcomes. This approach can involve either establishing race-sensitive risk thresholds, or distinct racial ‘tracks’. Is there (...) a moral difference between these two approaches? We first consider Deborah Hellman's view that the use of distinct racial tracks (but not distinct thresholds) does not constitute disparate treatment since the effects on individuals are indirect and does not rely on a racial generalization. We argue that this is mistaken: the use of different racial tracks seems both to have direct effects on and to rely on a racial generalization. We then offer an alternative understanding of the distinction between these two approaches—namely, that the use of different cut points is to the counterfactual comparative disadvantage, ex ante, of all white defendants, while the use of different racial tracks can in principle be to the advantage of all groups, though some defendants in both groups will fare worse. Does this mean that the use of cut points is impermissible? Ultimately, we argue, while there are reasons to be skeptical of the use of distinct cut points, it is an open question whether these reasons suffice to make a difference to their moral permissibility. (shrink)

About 80 % of all convicted have had a prior record of conviction. But how should the state punish repeat offenders (with a prior conviction) as compared with first-time offenders who are convicted? The law in all jurisdictions, a large swathe of public opinion, and the general trend within criminal justice ethics all seem to accept what we may call: -/- Asymmetry A The punishment of repeat offenders should be harsher than the punishment of first-time offenders. -/- This asymmetry is (...) obviously just a rough structure. It leaves a lot of room for interpretation. Several retributivists have argued for progressive loss of mitigation (PLM). On this view, a first-time offender receives a discount on punishment that is gradually lost if he re-offends. When the discount is lost the offender receives the full punishment, and re-offending from that point on will be punished equally. However, recently some retributivists have argued in favour of a cumulative principle (CP) according to which an offender will progressively be punished more severely the more convictions he has accumulated. In sum, in the theoretical literature on the subject, Asymmetry A has been the mantra for several prominent retributivists. The aim of this paper is to point to an all but overlooked logical point in the discussion of punishment and recidivism. This is the point that it follows, from retributivism, that there is a reason - at least in some situations, as we shall see - to support what we may call: -/- Asymmetry B The punishment of repeat offenders should be more lenient than the punishment of first-time offenders. (shrink)

Criminologists have long acknowledged the link between a number of cognitive deficits, including low intelligence and impulsivity, and crime. A new wave of research has demonstrated that pharmacological intervention can restore or improve cognitive function, particularly executive function, and restore neural plasticity. Such restoration and improvement can allow for easier acquisition of new skills and as a result, presents significant possibilities for the criminal justice system. For example, studies have shown that supplements of Omega-3, a fatty acid commonly found in (...) food such as tuna, can decrease frequency of violent incidents in an incarcerated population. Research has also begun to explore the use of selective serotonin reuptake inhibitors to reduce impulsivity in some violent offenders. However, there are significant legal and ethical implications when moving from dietary supplements to prescription pharmaceuticals and medical devices for cognitive intervention. This paper will explore the legal and ethical issues surrounding the use of pharmacological intervention on prisoners as an effort to reduce crime and recidivism. (shrink)

Base rates are vital in predicting violent criminal recidivism. However, both lay people given simulated prediction tasks and professionals milking real life predictions appear insensitive to variations in the base rate of violent recidivism. Although there are techniques to help decision makers attend to base rates, increased decision accuracy is better sought in improved actuarial models as opposed to improved clinicians.

In this paper, we study the effects of using an algorithm-based risk assessment instrument (RAI) to support the prediction of risk of violent recidivism upon release. The instrument we used is a machine learning version of RiskCanvi used by the Justice Department of Catalonia, Spain. It was hypothesized that people can improve their performance on defining the risk of recidivism when assisted with a RAI. Also, that professionals can perform better than non-experts on the domain. Participants had to (...) predict whether a person who has been released from prison will commit a new crime leading to re-incarceration, within the next two years. This user study is done with (1) general participants from diverse backgrounds recruited through a crowdsourcing platform, (2) targeted participants who are students and practitioners of data science, criminology, or social work and professionals who work with RisCanvi. We also run focus groups with participants of the targeted study, including people who use RisCanvi in a professional capacity, to interpret the quantitative results. Among other findings, we observe that algorithmic support systematically leads to more accurate predictions from all participants, but that statistically significant gains are only seen in the performance of targeted participants with respect to that of crowdsourced participants. Among other comments, professional participants indicate that they would not foresee using a fully-automated system in criminal risk assessment, but do consider it valuable for training, standardization, and to fine-tune or double-check their predictions on particularly difficult cases. We found that the revised prediction by using a RAI increases the performance of all groups, while professionals show a better performance in general. And, a RAI can be considered for extending professional capacities and skills along their careers. (shrink)

Judges in multiple US states, such as New York, Pennsylvania, Wisconsin, California, and Florida, receive a prediction of defendants’ recidivism risk, generated by the COMPAS algorithm. If judges act on these predictions, they implicitly delegate normative decisions to proprietary software, even beyond the previously documented race and age biases. Using the ProPublica dataset, we demonstrate that COMPAS predictions favor jailing over release. COMPAS is biased against defendants. We show that this bias can largely be removed. Our proposed correction increases (...) overall accuracy, and attenuates anti-black and anti-young bias. However, it also slightly increases the risk that defendants are released who commit a new crime before tried. We argue that this normative decision should not be buried in the code. The tradeoff between the interests of innocent defendants and of future victims should not only be made transparent. The algorithm should be changed such that the legislator and the courts do make this choice. (shrink)

In this paper we investigate risk prediction of criminal re-offense among juvenile defendants using general-purpose machine learning algorithms. We show that in our dataset, containing hundreds of cases, ML models achieve better predictive power than a structured professional risk assessment tool, the Structured Assessment of Violence Risk in Youth, at the expense of not satisfying relevant group fairness metrics that SAVRY does satisfy. We explore in more detail two possible causes of this algorithmic bias that are related to biases in (...) the data with respect to two protected groups, foreigners and women. In particular, we look at the differences in the prevalence of re-offense between protected groups and the influence of protected group or correlated features in the prediction. Our experiments show that both can lead to disparity between groups on the considered group fairness metrics. We observe that methods to mitigate the influence of either cause do not guarantee fair outcomes. An analysis of feature importance using LIME, a machine learning interpretability method, shows that some mitigation methods can shift the set of features that ML techniques rely on away from demographics and criminal history which are highly correlated with sensitive features. (shrink)

La division du travail physiologique est un concept tombé en désuétude en biologie. Quand l’expression est employée, c’est sans égard pour sa fonction nomologique importante dans la biologie du second xixe. Nous analyserons l’importation de la division du travail de l’économie à la biologie, malgré les difficultés de validation que posait son transfert d’une science à l’autre. La notion a ainsi continué sa carrière dans une biologie gagnée à la théorie cellulaire, cependant que ses déterminations économiques perdaient leur pertinence. Nous (...) terminerons en interrogeant sa disparition au début du xxe. La division du travail physiologique, une fois purifiée de son économicité primitive, ne pouvait sans doute que retourner à un stade métaphorique. (shrink)

This article argues that it is far from trivial to convert social science concepts into accurate categories on which algorithms work best. The literature raises this concern in a general way; for example, Deeks notes that legal concepts, such as proportionality, cannot be easily converted into code noting that ‘The meaning and application of these concepts is hotly debated, even among lawyers who share common vocabularies and experiences’ (Deeks in Va Law Rev 104, pp. 1529–1593, 2018). The example discussed here (...) is recidivism prediction, where the factors that are of interest are difficult to capture adequately through questionnaires because survey responses do not necessarily indicate whether the behaviour that is of interest is present. There is room for improvement in how questions are phrased, in the selection of variables, and by encouraging practitioners to consider whether a particular variable is the sort of thing that can be measured by questionnaires at all. (shrink)

In this paper we explore whether or not the use of risk assessment tools in criminal sentencing can be made compatible with a retributivist justification of punishment. While there has been considerable discussion of the accuracy and fairness of these tools, such discussion assumes that one’s recidivism risk is relevant to the severity of punishment that one should receive. But this assumption only holds on certain accounts of punishment, and seems to conflict with retributivist justifications of punishment. Drawing on (...) the broader desert literature, we explain the source of this conflict, and suggest that a retributivist approach on which the severity of punishment partly depends on one’s character in addition to their acts offers some hope of reconciling retributivism with the use of risk assessment tools in considerations of sentencing reduction in particular. Ultimately, however, even this limited attempt at reconciliation fails, so long as risk assessment tools fail to distinguish between risk that one is responsible for, and risk that one is not responsible for. (shrink)

In the US context, critics of court use of algorithmic risk prediction algorithms have argued that COMPAS involves unfair machine bias because it generates higher false positive rates of predicted recidivism for black offenders than for white offenders. In response, some have argued that algorithmic fairness concerns, either also or only, calibration across groups–roughly, that a score assigned to different individuals by the algorithm involves the same probability of the individual having the target property across different groups of individuals–and (...) that, for mathematical reasons, it is virtually impossible to equalize false positive rates without impairing the calibration. I argue that in standard non-algorithmic contexts, such as hirings, we do not think that lack of calibration entails unfair bias, and that it is difficult to see why algorithmic contexts, as it were, should differ fairness-wise from non-algorithmic ones in this respect. Hence, we should reject the view that calibration is necessary for fairness in an algorithmic context. (shrink)

Abstract The accumulated case studies in the Sociology of Scientific Knowledge have been taken to establish the Strong Programme's thesis that beliefs have social causes in contradistinction to psychological ones. This externalism is essentially a commitment to the stimulus control of behaviour which was the principal tenet of orthodox Skinnerian Behaviorism. Offered as ?straight forward scientific hypotheses? these claims of social determination are asserted to be ?beyond dispute?. However, the causes of beliefs and especially their contents has also been the (...) subject of intense study in the quite different domain of cognitive science where internal states, images, rules, representations and schemas are postulated as explanatory constructs. Such explanations which postulate mental states are described by Bloor as infected by the ?disease? of ?psychologism? and Bloor has defined his Strong Programme in terms of its diametrical opposition to mentalistic theories. For example, Bloor has explicitly endorsed the Behaviourist rejection of mental representations such as images. Accordingly, a direct comparison of these radically divergent approaches to a common subject matter is of considerable interest. The paper attempts to reveal the unnoticed enormity and recidivism of the sociological programme, and how its vulnerability is betrayed in Bloor's response to criticism on central issues. (shrink)

Psychopathy is a disorder involving personality and behavioral features associated with a high rate of violent aggression and recidivism. This paper explores potential psychopharmacological therapies to modulate dysfunctional neural pathways in psychopaths and reduce the incidence of their harmful behavior, as well as the ethical and legal implications of offering these therapies as an alternative to incarceration. It also considers whether forced psychopharmacological intervention in adults and children with psychopathic traits manifesting in violent behavior can be justified. More generally, (...) the paper addresses the question of how to weigh the psychopath’s presumptive right to non-interference in his brain and mind against the public interest in avoiding harm. (shrink)

A central tenet of medical ethics holds that it is permissible to perform a medical intervention on a competent individual only if that individual has given informed consent to the intervention. However, in some circumstances it is tempting to say that the moral reason to obtain informed consent prior to administering a medical intervention is outweighed. For example, if an individual’s refusal to undergo a medical intervention would lead to the transmission of a dangerous infectious disease to other members of (...) the community, one might claim that it would be morally permissible to administer the intervention even in the absence of consent. Indeed, as we shall discuss below, there are a number of examples of public health authorities implementing compulsory or coercive measures for the purposes of infectious disease control (IDC). The plausibility of the thought that non-consensual medical interventions might be justified when performed for the purpose of IDC raises the question of whether such interventions might permissibly be used to realize other public goods. In this article we focus on one possibility: whether it could be permissible to non-consensually impose certain interventions that alter brain states or processes through chemical or physical means on serious criminal offenders. We shall suggest that some such interventions might be permissible if they safely and effectively serve to facilitate the offender’s rehabilitation and thereby prevent criminal recidivism. (shrink)

Predictive algorithms are playing an increasingly prominent role in society, being used to predict recidivism, loan repayment, job performance, and so on. With this increasing influence has come an increasing concern with the ways in which they might be unfair or biased against individuals in virtue of their race, gender, or, more generally, their group membership. Many purported criteria of algorithmic fairness concern statistical relationships between the algorithm’s predictions and the actual outcomes, for instance requiring that the rate of (...) false positives be equal across the relevant groups. We might seek to ensure that algorithms satisfy all of these purported fairness criteria. But a series of impossibility results shows that this is impossible, unless base rates are equal across the relevant groups. What are we to make of these pessimistic results? I argue that none of the purported criteria, except for a calibration criterion, are necessary conditions for fairness, on the grounds that they can all be simultaneously violated by a manifestly fair and uniquely optimal predictive algorithm, even when base rates are equal. I conclude with some general reflections on algorithmic fairness. (shrink)

Moral agential neuroenhancement can transform us into better people. However, critics of MB raise four central objections to MANEs use: It destroys moral freedom; it kills one moral agent and replaces them with another, better agent; it carries significant risk of infection and illness; it benefits society but not the enhanced person; and it’s wrong to experiment on nonconsenting persons. Herein, I defend MANE’s use for prisoners of war fighting unjustly. First, the permissibility of killing unjust combatants entails that, in (...) cases where MANE is equally or more likely as termination to reduce moral recidivism in unjust combatants, then MANE is morally justified. Second, the relevant infections and illnesses caused by MANE are less bad than death, so MANE leaves unjust POWs better off than the alternative. Third, just as incarceration is often permissible despite benefitting society but not the incarcerated, the same holds for unjust POWs. Fourth, we should accept a broader construal of “benefit” that includes moral benefits. Thus, 3 and 4 are false when applied to unjust POWs. Fifth, medical experimentation likely to help nonconsenting persons is sometimes permissible. Because MANE is likely to help unjust POWs irrespective of their consent or lack thereof, its use is permissible. Sixth, basic principles of proper medical care support the use of MANE on unjust POWs as pro tanto morally obligatory. I conclude that militaries should therefore begin to employ MANE for unjust POWs. (shrink)

The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and (...) academics have begun to raise critical questions about the use of these tools in policing contexts. In this chapter, I review the emerging critical literature on predictive policing and contribute to it by raising ethical questions about the use of predictive analytics tools to identify potential offenders. Drawing from work on the ethics of profiling, I argue that the much-lauded move from reactive to preemptive policing can mean wrongfully generalizing about individuals, making harmful assumptions about them, instrumentalizing them, and failing to respect them as full ethical persons. I suggest that these problems stem both from the nature of predictive policing tools and from the sociotechnical contexts in which they are implemented... (shrink)

This volume provides discussions of both the concept of responsibility and of punishment, and of both individual and collective responsibility. It provides in-depth Socratic and Kantian bases for a new version of retributivism, and defends that version against the main criticisms that have been raised against retributivism in general. It includes chapters on criminal recidivism and capital punishment, as well as one on forgiveness, apology and punishment that is congruent with the basic precepts of the new retributivism defended therein. (...) Finally, chapters on corporate responsibility and punishment are included, with a closing chapter on holding the U.S. accountable for its most recent invasion and occupation of Iraq. The book is well-focused but also presents the widest ranging set of topics of any book of its kind as it demonstrates how the concepts of responsibility and punishment apply to some of the most important problems of our time. “This is one of the best books on punishment, and the Fourth Edition continues its tradition of excellence. The book connects punishment importantly to moral responsibility and desert, and it is comprehensive in its scope, both addressing abstract, theoretical issues and applied issues as well. The topics treated include collective responsibility, apology, forgiveness, capital punishment, and war crimes. Highly recommended.”—John Martin Fischer, Distinguished Professor of Philosophy, University of California, Riverside. (shrink)

Measures of algorithmic bias can be roughly classified into four categories, distinguished by the conditional probabilistic dependencies to which they are sensitive. First, measures of "procedural bias" diagnose bias when the score returned by an algorithm is probabilistically dependent on a sensitive class variable (e.g. race or sex). Second, measures of "outcome bias" capture probabilistic dependence between class variables and the outcome for each subject (e.g. parole granted or loan denied). Third, measures of "behavior-relative error bias" capture probabilistic dependence between (...) class variables and the algorithmic score, conditional on target behaviors (e.g. recidivism or loan default). Fourth, measures of "score-relative error bias" capture probabilistic dependence between class variables and behavior, conditional on score. Several recent discussions have demonstrated a tradeoff between these different measures of algorithmic bias, and at least one recent paper has suggested conditions under which tradeoffs may be minimized. -/- In this paper we use the machinery of causal graphical models to show that, under standard assumptions, the underlying causal relations among variables forces some tradeoffs. We delineate a number of normative considerations that are encoded in different measures of bias, with reference to the philosophical literature on the wrongfulness of disparate treatment and disparate impact. While both kinds of error bias are nominally motivated by concern to avoid disparate impact, we argue that consideration of causal structures shows that these measures are better understood as complicated and unreliable measures of procedural biases (i.e. disparate treatment). Moreover, while procedural bias is indicative of disparate treatment, we show that the measure of procedural bias one ought to adopt is dependent on the account of the wrongfulness of disparate treatment one endorses. Finally, given that neither score-relative nor behavior-relative measures of error bias capture the relevant normative considerations, we suggest that error bias proper is best measured by score-based measures of accuracy, such as the Brier score. (shrink)

Repeat offenders receive longer sentences than first offenders in virtually every modern jurisdiction. Such prior-record enhancements are politically popular. Scholars are more divided, especially regarding severe enhancements. Retributivists have long disagreed about which enhancements, if any, are morally justifiable and on what basis. This article advances the debate, offering lessons for retributivists on all sides. I address an intuitive argument that justifies enhancements in terms of character. This argument has been caricatured and dismissed, with defenders of enhancements preferring character-independent arguments. (...) I reconstruct an argument for enhancements that assumes recidivism constitutes evidence of culpability-aggravating character traits. The argument seems at least coherent, inferentially valid, and intuitively plausible. I then raise what I see as the real threats to the argument, which are neither conceptual nor normative, but empirical. I identify some formal features that the character argument requires of culpability-aggravating traits. To support enhancements, such traits must also correlate properly with criminal records. One place to look for characterizations of such traits, and evidence of correlation, is criminology, in theories of criminogenesis and criminality. I conclude that character arguments for prior-record enhancements cannot be dismissed, although their thorough evaluation awaits answers to complex empirical questions. (shrink)

Can the evidence provided by software systems meet the standard of proof for civil or criminal cases, and is it individualized evidence? Or, to the contrary, do software systems exclusively provide bare statistical evidence? In this paper, we argue that there are cases in which evidence in the form of probabilities computed by software systems is not bare statistical evidence, and is thus able to meet the standard of proof. First, based on the case of State v. Loomis, we investigate (...) recidivism predictions provided by software systems used in the courtroom. Here, we raise problems for software systems that provide predictions that are based on bare statistical evidence. Second, by examining the case of People v. Chubbs, we argue that the statistical evidence provided by software systems in cold hit DNA cases may in some cases suffice for individualized evidence, on a view on which individualized evidence is evidence that normically supports the relevant proposition (Smith, in Mind 127:1193–1218, 2018). (shrink)

Crime-preventing neurointerventions (CPNs) are increasingly being used or advocated for crime prevention. There is increasing use of testosterone-lowering agents to prevent recidivism in sexual offenders, and strong political and scientific interest in developing pharmaceutical treatments for psychopathy and anti-social behaviour. Recent developments suggest that we may ultimately have at our disposal a range of drugs capable of suppressing violent aggression, and it is not difficult to imagine possible applications of such drugs in crime prevention. But should neurointerventions be used (...) in crime prevention, and may the state ever permissibly impose CPNs as part of the criminal justice process? It is widely thought that preventing recidivism is one of the aims of criminal justice, yet existing means of pursuing this aim are often poorly effective, restrictive of basic freedoms, and harmful. Incarceration, for example, tends to be disruptive of personal relationships and careers, detrimental to physical and mental health, highly restrictive of freedom of movement and association, and rarely more than modestly effective at preventing recidivism. Neurointerventions hold the promise of preventing recidivism in ways that are more effective and more humane, but the use of CPNs in criminal justice raises several ethical concerns. CPNs could be highly intrusive and may threaten fundamental human values, such as bodily integrity and freedom of thought, and humanity has a track record of misguided, harmful, and unwarrantedly coercive use of neurotechnological ‘solutions’ to criminality. This collection brings together original contributions from emerging scholars and internationally renowned moral and political philosophers to address these issues. (shrink)

There are a number of important links and similarities between public health and safety. In this extended essay, Gregg D. Caruso defends and expands his public health-quarantine model, which is a non-retributive alternative for addressing criminal behavior that draws on the public health framework and prioritizes prevention and social justice. In developing his account, he explores the relationship between public health and safety, focusing on how social inequalities and systemic injustices affect health outcomes and crime rates, how poverty affects brain (...) development, how offenders often have pre-existing medical conditions (especially mental health issues), how involvement in the criminal justice system itself can lead to or worsen health and cognitive problems, how treatment and rehabilitation methods can best be employed to reduce recidivism and reintegrate offenders back into society, and how a public health approach could be successfully applied within the criminal justice system. Caruso's approach draws on research from the health sciences, social sciences, public policy, law, psychiatry, medical ethics, neuroscience, and philosophy, and he delivers a set of ethically defensible and practically workable proposals for implementing the public health-quarantine model. The essay begins by discussing recent empirical findings in psychology, neuroscience, and the social sciences that provide us with an increased understanding of the social and neurological determinants of health and criminal behavior. It then turns to Caruso's public health-quarantine model and argues that the model provides the most justified, humane, and effective approach for addressing criminal behavior. Caruso concludes by proposing a capability approach to social justice grounded in six key features of human well-being. He argues that we cannot successfully address concerns over public health and safety without simultaneously addressing issues of social justice—including the social determinants of health (SDH) and the social determinants of criminal behavior (SDCB)—and he recommends eight general policy proposals consistent with his model. (shrink)

In the past decade there has been renewed interest in the study of mental imagery. Emboldened by new findings from neuroscience, many people have revived the idea that mental imagery involves a special format of thought, one that is pictorial in nature. But the evidence and the arguments that exposed deep conceptual and empirical problems in the picture theory over the past 300 years have not gone away. I argue that the new evidence from neural imaging and clinical neuropsychology does (...) little to justify this recidivism because it does not address the format of mental images. I also discuss some reasons why the picture theory is so resistant to counterarguments and suggest ways in which non-pictorial theories might account for the apparent spatial nature of images. (shrink)

In many assessment problems—aptitude testing, hiring decisions, appraisals of the risk of recidivism, evaluation of the credibility of testimonial sources, and so on—the fair treatment of different groups of individuals is an important goal. But individuals can be legitimately grouped in many different ways. Using a framework and fairness constraints explored in research on algorithmic fairness, I show that eliminating certain forms of bias across groups for one way of classifying individuals can make it impossible to eliminate such bias (...) across groups for another way of dividing people up. And this point generalizes if we require merely that assessments be approximately bias-free. Moreover, even if the fairness constraints are satisfied for some given partitions of the population, the constraints can fail for the coarsest common refinement, that is, the partition generated by taking intersections of the elements of these coarser partitions. This shows that these prominent fairness constraints admit the possibility of forms of intersectional bias. (shrink)

Ethicists have for the past 20 years debated the possibility of using neurointerventions to improve intelligence and even moral capacities, and thereby create a safer society. Contributing to a recent debate concerning neurointerventions in criminal rehabilitation, Nicole Vincent and Elizabeth Shaw have separately discussed the possibility of responsibility enhancement. In their ethical analyses, enhancing a convict’s capacity responsibility may be permissible. Both Vincent and Shaw consider self-control to be one of the constituent mental capacities of capacity responsibility. In this paper, (...) we critically examine the promise of improving convicts’ capacity responsibility by neuroenhancements of self-control to see whether the special characteristics of the inmate population make a difference in the analyses. As improving self-control by means of neurointerventions seems plausible, we then ask whether it is or could be a justified measure in court rulings. We conclude that, even if there are cases in which neurointerventions were warranted in the context of the stated goals of the criminal court, i.e., decreasing recidivism and rehabilitating the offenders to the society, due to the range of individual variability in the constitution of self-control, the prescription of specific neurointerventions of self-control falls outside the scope of legitimate court rulings. (shrink)

Restorative justice should have greater weight as a criterion in criminal justice sentencing practice. It permits a realistic recognition of the kinds of harm and damage caused by offences, and encourages individualized non-custodial sentencing options as ways of addressing these harms. Non-custodial sentences have proven more effective than incarceration in securing social reconciliation and preventing recidivism, and they avoid the serious social and personal costs of imprisonment. This paper argues in support of restorative justice as a guiding idea in (...) sentencing. As part of this defence, it considers whether the use of the idea of restorative justice will conflate criminal law with civil law or displace the authority of the criminal courts, and whether the sentences it recommends are best thought of as punishments or alternatives to punishment. (shrink)

Taxometric analyses were applied to the construct of psychopathy (as measured by the Psychopathy Checklist) and to several variables reflecting antisocial childhood, adult criminality, and criminal recidivism. Subjects were 653 serious offenders assessed or treated in a maximum-security institution. Results supported the existence of a taxon underlying psychopathy. Childhood problem behaviors provided convergent evidence for the existence of the taxon. Adult criminal history variables were continuously distributed and were insufficient in themselves to detect the taxon.

As inductive decision-making procedures, the inferences made by machine learning programs are subject to underdetermination by evidence and bear inductive risk. One strategy for overcoming these challenges is guided by a presumption in philosophy of science that inductive inferences can and should be value-free. Applied to machine learning programs, the strategy assumes that the influence of values is restricted to data and decision outcomes, thereby omitting internal value-laden design choice points. In this paper, I apply arguments from feminist philosophy of (...) science to machine learning programs to make the case that the resources required to respond to these inductive challenges render critical aspects of their design constitutively value-laden. I demonstrate these points specifically in the case of recidivism algorithms, arguing that contemporary debates concerning fairness in criminal justice risk-assessment programs are best understood as iterations of traditional arguments from inductive risk and demarcation, and thereby establish the value-laden nature of automated decision-making programs. Finally, in light of these points, I address opportunities for relocating the value-free ideal in machine learning and the limitations that accompany them. (shrink)

As neuroscience progresses, we will not only gain a better understanding of how our brains work, but also a better understanding of how to modify them, and as a result, our mental states. An important question we are faced with is whether the state could be justified in implementing such methods on criminal offenders, without their consent, for the purposes of rehabilitation and reduction of recidivism; a practice that is already legal in some jurisdictions. By focusing on a prominent (...) type of view of free action, which I call bypassing views, this paper evaluates how such interventions may negatively impact the freedom of their subjects. The paper concludes that there will be a tension between the goals of rehabilitation and reduction of recidivism, on the one hand, and the negative impact such interventions may have on free action, on the other. Other things equal, the better that a particular intervention is at achieving the former, the more likely it is to result in the latter. (shrink)

Can humans and artificial intelligences share concepts and communicate? Making AI Intelligible shows that philosophical work on the metaphysics of meaning can help answer these questions. Herman Cappelen and Josh Dever use the externalist tradition in philosophy to create models of how AIs and humans can understand each other. In doing so, they illustrate ways in which that philosophical tradition can be improved. The questions addressed in the book are not only theoretically interesting, but the answers have pressing practical implications. (...) Many important decisions about human life are now influenced by AI. In giving that power to AI, we presuppose that AIs can track features of the world that we care about (for example, creditworthiness, recidivism, cancer, and combatants). If AIs can share our concepts, that will go some way towards justifying this reliance on AI. This ground-breaking study offers insight into how to take some first steps towards achieving Interpretable AI. (shrink)

Machine learning (ML) techniques have become pervasive across a range of different applications, and are now widely used in areas as disparate as recidivism prediction, consumer credit-risk analysis, and insurance pricing. Likewise, in the physical world, ML models are critical components in autonomous agents such as robotic surgeons and self-driving cars. Among the many ethical dimensions that arise in the use of ML technology in such applications, analyzing morally permissible actions is both immediate and profound. For example, there is (...) the potential for learned algorithms to become biased against certain groups. More generally, in so much that the decisions of ML models impact society, both virtually (e.g., denying a loan) and physically (e.g., driving into a pedestrian), notions of accountability, blame and responsibility need to be carefully considered. In this article, we advocate for a two-pronged approach ethical decision-making enabled using rich models of autonomous agency: on the one hand, we need to draw on philosophical notions of such as beliefs, causes, effects and intentions, and look to formalise them, as attempted by the knowledge representation community, but on the other, from a computational perspective, such theories need to also address the problems of tractable reasoning and (probabilistic) knowledge acquisition. As a concrete instance of this tradeoff, we report on a few preliminary results that apply (propositional) tractable probabilistic models to problems in fair ML and automated reasoning of moral principles. Such models are compilation targets for certain types of knowledge representation languages, and can effectively reason in service some computational tasks. They can also be learned from data. Concretely, current evidence suggests that they are attractive structures for jointly addressing three fundamental challenges: reasoning about possible worlds + tractable computation + knowledge acquisition. Thus, these seems like a good starting point for modelling reasoning robots as part of the larger ecosystem where accountability and responsibility is understood more broadly. (shrink)

A central question in the current neurolegal and neuroethical literature is how brain-reading technologies could contribute to criminal justice. Some of these technologies have already been deployed within different criminal justice systems in Europe, including Slovenia, Italy, England and Wales, and the Netherlands, typically to determine guilt, legal responsibility, or recidivism risk. In this regard, the question arises whether brain-reading could permissibly be used against the person's will. To provide adequate legal protection from such non-consensual brain-reading in the European (...) legal context, ethicists have called for the recognition of a novel fundamental legal right to mental privacy. In this paper, we explore whether these ethical calls for recognising a novel legal right to mental privacy are necessary in the European context. We argue that a right to mental privacy could be derived from, or at least developed within in the jurisprudence of the European Court of Human Rights, and that introducing an additional fundamental right to protect against brain-reading is not necessary. What is required, however, is a specification of the implications of existing rights for particular neurotechnologies and purposes. (shrink)

Internal misconduct is a universal problem in prisons and affects the maintenance of social order. Consequently, correctional institutions often develop rehabilitation programs to reduce the likelihood of inmates committing internal offenses and criminal recidivism after release. Therefore, it is necessary to identify the profile of each offender, both for the appropriate indication of a rehabilitation program and the level of internal security to which he must be submitted. In this context, this work aims to discover the most significant characteristics (...) in predicting inmate misconduct from ML methods and the SHAP approach. A database produced in 2004 through the Survey of Inmates in State and Federal Correctional Facilities in the United States of America was used, which provides nationally representative data on prisoners from state and federal facilities. The predictive model based on Random Forest performed the best, thus, we applied the SHAP to it. Overall, the results showed that features related to victimization, type of crime committed, age and age at first arrest, history of association with criminal groups, education, and drug and alcohol use are most relevant in predicting internal misconduct. Thus, it is expected to contribute to the prior classification of an inmate on time, to use programs and practices that aim to improve the lives of offenders, their reintegration into society, and consequently, the reduction of criminal recidivism. (shrink)

The proposal that the criminal justice system should focus on rehabilitation – rather than retribution, deterrence, or expressive denunciation – is among the least popular ideas in legal philosophy. Foremost among rehabilitation’s alleged weaknesses is that it views criminals as blameless patients to be treated, rather than culpable moral agents to be held accountable. This article offers a new interpretation of the rehabilitative approach that is immune to this objection and that furnishes the moral foundation that this approach has lacked. (...) The view rests on the principle that moral agents owe it to one another to maintain the dependability of their moral capacities. Agents who culpably commit criminal wrongs, however, betray an unacceptable degree of moral unreliability. Punishment, on this theory, consists in the enforcement of the duties that offenders have to reduce their own likelihood of recidivism. (shrink)

While research has consistently found that general distress and psychopathology are not predictive of sexual recidivism, examination of specific syndromes and their relationship to offending has revealed a potentially more complicated relationship. One proposed mechanism for the mixed findings with respect to major mental illness and sexual offending may be the confound of neurological injury. As identified in Mann et al. work on psychologically meaningful risk factors, mental illness represents an area in need of more study given the indirect (...) influence it may exert on risk. To this end, the current paper summarizes the study of the relationship between neurological injury, psychosis and problematic sexual behavior among two Canadian samples of forensic and civil psychiatric patients. In the first study we observed higher than expected rates of sexually-themed psychotic symptoms and problematic sexual behavior among a combined group of forensic and civil psychiatric patients. Indeed 70 percent of those individuals who engaged in PSB endorsed sexually-themed psychotic symptoms. While comorbidity is common amongst this group, brain injury appeared to represent a specific liability. Compared to those who did not engage in PSB, those who did were almost 4x more likely to have a documented history of brain injury. In the second study we sought to replicate this finding in a larger forensic sample of 1,240. However, the recorded rates of brain injury were significantly less, such that no relationship to PSB was observed. Based on the mixed findings to date, including our own data, questions remain about the nature of a potential shared vulnerability for psychosis and PSB previously postulated. Among psychiatrically complex individuals who engage in PSB, understanding etiology and links to risk are helpful, but perhaps more importantly is attention to the mechanisms through which symptoms confer risk and how best to treat and manage them. (shrink)

Peter McHugh was an internationally known sociologist within the field of anti-positivist social theory. As the only collection of McHugh's sole-authored writings, Redefining the Situation presents a comprehensive yet surprising view of this key theorist's influence in his field. Redefining the Situation is a compendium of McHugh's published and unpublished short-form writings, along with three new essays on McHugh's work, one by his long-time collaborator and friend Alan Blum. The collection contributes to the project of reinventing social theory by providing (...) a new perspective from which to imaginatively rethink the development of sociology over the last fifty years. It locates McHugh's work not only within the modern and postmodern sociological tradition but also within contemporary social theory broadly, including hermeneutics, critical theory, deconstruction, and Hannah Arendt's political theory. The essays in this volume show the development of a method to analyze everyday behaviour in light of fundamental questions, exploring conflicts and connections between socialization and recidivism, fragmentation and ethnic cleansing, justice and affirmative action, teaching and university politics, and intimacy and aesthetics. This book moves beyond contemporary debates about big data/postmodernism, and along the way it identifies convergences in Anglo-American and Continental thought. By tracing the development of Analysis, the tradition of social inquiry, from its beginnings until today, Redefining the Situation re-establishes a prominent sociologist as one of the leading intellectuals in the field of interpretive social theory. (shrink)

Suppose we agree to reject the view that privacy has narrow scope and consequently is irrelevant to the constitutional privacy cases. We then have (at least) these two options: (1) We might further emphasize and draw out similarities between tort and constitutional privacy claims in order to develop a notion of privacy fundamental to informational and Fourth Amendment privacy concerns as well as the constitutional cases. We can cite examples indicating this is a promising position. Consider consenting homosexuality conducted in (...) one's home, for instance. We view it as a private matter, whether the state is seeking to regulate the behavior, or if others are attempting to gain or exploit information about it. I believe basic conceptual similarities between tort and constitutional interests can be identified by showing that there is a range of similar reasons for protecting both tort and constitutional privacy concerns. We might worry, however, that a comprehensive concept of privacy may be too general to be very useful, given that privacy violations can be so diverse, and can arise, for example, from misuse of confidential information, from conduct that is intrusive even if no information is gained or disclosed, from disturbance of an intimate relationship, or from disruption of various other important aspects of one's life.(2) We could concede that whatever “privacy” means in the tort and Fourth Amendment cases, it means something different in the constitutional cases. Nevertheless, we might take that “something else” seriously as a distinct but legitimate use of the term which is not “spurious” but is reflected in our ordinary language. This appears to me to be a fruitful alternative. After all, contrary to Henkin's view that tort privacy is “what most people mean by privacy,” the term is often used in contexts beyond informational privacy and clearly related to the interests at stake in the constitutional cases. Thus, for example, in a pamphlet explaining how to protect children by teaching them how to say “No!” to strangers without making them paranoid or antisocial, parents and teachers are told, Children have a right to privacy. Teach it. Reinforce it. One of the ways to help children prevent sexual assault is to encourage them to develop a sense of physical integrity. A sense that they have a right to their own body space and privacy. Just as we allow them to close the door when they use the bathroom, we must allow them to say no to any unwanted physical affection and touch. Flora Calao and Tamar Hosansky, “The Key to Having Fun is Being Safe: Teaching Personal Safety to Children,” The Safety and Fitness Exchange, 1123 Broadway, N.Y., N.Y. 10010. Unfortunately, the most obvious starting point for identifying the sense of private relevant to the constitutional cases is extremely worrisome. The Court itself has said ... only personal rights that can be deemed “fundamental”...are included in this guarantee of personal privacy...the right has some extension to activities relating to marriage...procreation...contraception...family relationships... and child rearing and education.Roe v. Wade, 410 U.S. 113 (1973).The difficulty, of course, is that little more is offered by way of explanation of which rights are “personal” or “fundamental” or both. Focusing on marriage makes Roe v. Wade difficult to understand given that Ms. Roe was unmarried, and attending only to family issues does not help us make sense of the Stanley case protecting one's right to view pornography in one's home. It is perhaps more problematic that decisions such as what color shoes to wear are reasonably viewed as personal, yet are far from fundamental enough to warrant protection. And regulations governing the draft and employment, for example, are not viewed as privacy invasions although they might be said to interfere with matters of one's life that are both fundamental and personal in the vague sense described.Before we give up in frustration, however, I would urge that we recall that even in tort law the notion of privacy has been evolving through a constellation of judgments. Although there is no fixed way of using the term which we then proceed to analyze, the concept of privacy has not in those cases been taken to be meaningless or empty. Similarly, there is reason to believe that the scope of a “personal and fundamental” notion of privacy relevant to the constitutional cases can be further delineated through a consideration of cases, especially since it seems to me that in many cases application of the term is clear and unproblematic. A decision to have a vasectomy, for example, can uncontroversially be said to be a personal and fundamental one, and it is in that sense private. We fail to acknowledge the personal significance in an individual's life of forcing or refusing him the operation if we deny that this important sense of privacy is relevant to such a decision merely because an interest in determining for oneself what one ought to do is also at risk.Of course, once it is settled that something is a private matter, it is a separate issue to decide whether or not, in some social context, an invasion of it can be justified. Thus, I would claim, a mandatory sterilization program for male recidivists or for those in a country suffering grave poverty and overpopulation does invade privacy, and the social or legal question is whether or not the invasion can, in the particular circumstances, be justified. Although all will agree that both individual and social interests must be balanced by moral philosophers as well as the courts, in conflicts we will not always agree on the weight to be accorded individual claims.I have not provided a constitutional defense for citing privacy as one right at stake in the constitutional privacy cases. Nor have I attempted to enter the debate about how strictly to interpret the Constitution. But if I am correct, then we can agree there is an important interest in privacy at issue in those cases without merely conflating privacy and autonomy or liberty, and can continue the process of marking out its boundaries. If we reach such agreement, we will have made considerable progress. Moreover, the implications of this view are significant. Current constitutional standards, controversial though they may be, require “strict scrutiny” for cases concerning “fundamental values,” and privacy has been judged to be one such value. Thus these privacy claims have a greater chance of being protected when they conflict with other rights or general interests than they would have if only liberty, or freedom from governmental interference, were involved. (shrink)

Most people assume that criminal offenders have only been convicted of a single crime. However, in reality almost half of offenders stand to be sentenced for more than one crime. The high proportion of multiple crime offenders poses a number of practical and theoretical challenges for the criminal justice system. For instance, how should courts punish multiple offenders relative to individuals who have been sentenced for a single crime? How should they be punished relative to each other? Sentencing Multiple Crimes (...) discusses these questions from the perspective of several legal theories. This volume considers questions such as the proportionality of the crimes committed, the temporal span between the crimes, and the relationship between theories about the punitive treatment of recidivists and multiple offenders. Contributors from around the world and in the fields of legal theory, philosophy, and psychology offer their perspectives to the volume. A comprehensive examination of the dynamics involved with sentencing multiple offenders has the potential to be a powerful tool for legal scholars and professionals, particularly given the practical importance of the topic and the relative dearth of research about punishment of multiple offense cases. (shrink)