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)

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)

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an in- hibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N =96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding (...) constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior. (shrink)

This review is unashamedly from the perspective of English law because busy United Kingdom criminal law solicitors and barristers mostly wish to know what the law states, which case is a precedent case and whether the author has provided up-to-date legal information. This is because legal practitioners deal with real and urgent cases. The English Income Tax Act gained Royal Assent in 1799 the first government attempt to stop early tax avoidance. Later, tax avoidance schemes (which in English Law were (...) deemed a legitimate method of minimising one payment of taxation) became de rigueur all over the world and often involved creation of Deeds of Covenant and Trusts, notably Discretionary Trusts under civil law. Man’s ingenuity knows no bounds and this applies to man’s characteristic of criminality as it does to scholarship, enterprise and innovation. Despite protestations by some countries police agencies, contrary to the rise of crime, the fact is that that crime is increasing exponentially worldwide, but the number of people committing crime is not increasing because many crimes are repeated crimes committed by persons with habitual criminal behaviour, ie hard-core criminals. (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)

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)

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 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)

It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, (...) ensuring that the resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (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)

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)

Many criminal offenders come from disadvantaged backgrounds, which punishment entrenches. Criminal culpability explains some disadvantageous treatment in state-offender interactions; yet offenders remain people, and ‘some mother’s child’, in Eva Kittay’s terms. Offending behaviour neither erases needs, nor fully excuses our responsibility for offenders’ needs. Caring is demanded in principle, recognising the offender’s personhood. Supporting offenders may amplify welfare resources: equipping offenders to provide self-care; to meet caring responsibilities; and enabling offenders’ contribution to shared social life, by providing support and furthering (...) the choices of others seeking to engage with them. The desistance paradigm (viewing desistance from offending as a process, following from an offender’s active choice in the context of stabilising social structures and personal circumstances), implies that a supportive environment may facilitate reduced recidivism. While decisions about criminal culpability need justice, we may use state resources most effectively by also including care ethics in our thinking about punishment. (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)

It is often said that the institutions of criminal justice ought or—perhaps more often—ought not to rehabilitate criminal offenders. But the term ‘criminal rehabilitation’ is often used without being explicitly defined, and in ways that are consistent with widely divergent conceptions. In this paper, we present a taxonomy that distinguishes, and explains the relationships between, different conceptions of criminal rehabilitation. Our taxonomy distinguishes conceptions of criminal rehabilitation on the basis of (i) the aims or ends of the putatively rehabilitative measure, (...) and (ii) the means that may be used to achieve the intended end. We also explore some of the implications of each conception, some of the payoffs of a taxonomy of the kind we offer, and some areas for future work. (shrink)

Human rights and restorative justice are rarely brought under the same spotlight despite their normative similarities. In fact, this gap becomes even more apparent when put in the context of policy and practice internationally. Firstly, there is a developing gap between public perception and evidence-based depiction of crime. Secondly, scholarly debates are rarely reflected in criminal justice policy and legislation. This failure has an impact on recidivism, the spiralling costs of penal interventions, but most importantly on how we view (...) our interpersonal and inter-communal relationships. -/- This unique collection of papers brings together international leading experts in human rights and restorative justice to address a gap in the literature. From reconstructing and restorative human rights for restorative justice to addressing issues such as the standardisation of restorative justice, this edited volume is a must read for researchers, practitioners and campaigners. (shrink)

Psychopathy is a personality disorder characterized by callous antisocial behavior and criminal recidivism. Here we examine whether psychopathy is associated with alterations in functional connectivity in three large-scale cortical networks. Using fMRI in 142 adult male prison inmates, we computed resting-state functional connectivity using seeds from the default mode network, frontoparietal network, and cingulo-opercular network. To determine the specificity of our findings to these cortical networks, we also calculated functional connectivity using seeds from two comparison primary sensory networks: visual (...) and auditory networks. Regression analyses related network connectivity to overall psychopathy scores and to subscores for the “factors” and “facets” of psychopathy: Factor 1, interpersonal/affective traits; Factor 2, lifestyle/antisocial traits; Facet 1, interpersonal; Facet 2, affective; Facet 3, lifestyle; Facet 4, antisocial. Overall psychopathy severity was associated with reduced functional connectivity between lateral parietal cortex and dorsal anterior cingulate cortex. The two factor scores exhibited contrasting relationships with functional connectivity: Factor 1 scores were associated with reduced functional connectivity in the three cortical networks, whereas Factor 2 scores were associated with heightened connectivity in the same networks. This dissociation was evident particularly in the functional connectivity between anterior insula and dorsal anterior cingulate cortex. The facet scores also demonstrated distinct patterns of connectivity. We found no associations between psychopathy scores and functional connectivity within visual or auditory networks. These findings provide novel evidence on the neural correlates of psychopathy and suggest that connectivity between cortical association hubs, such as the dorsal anterior cingulate cortex, may be a neurobiological marker of the disorder. (shrink)