This paper examines racial discrimination and algorithmic bias in predictive policing algorithms (PPAs), an emerging technology designed to predict threats and suggest solutions in law enforcement. We first describe what discrimination is in a case study of Chicago’s PPA. We then explain their causes with Broadbent’s contrastive model of causation and causal diagrams. Based on the cognitive science literature, we also explain why fairness is not an objective truth discoverable in laboratories but has context-sensitive social meanings that need (...) to be negotiated through democratic processes. With the above analysis, we next predict why some recommendations given in the bias reduction literature are not as effective as expected. Unlike the cliché highlighting equal participation for all stakeholders in predictive policing, we emphasize power structures to avoid hermeneutical lacunae. Finally, we aim to control PPA discrimination by proposing a governance solution—a framework of a social safety net. (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 policing has become a new panacea for crime prevention. However, we still know too little about the performance of computational methods in the context of predictive policing. The paper provides a detailed analysis of existing approaches to algorithmic crime forecasting. First, it is explained how predictive policing makes use of predictive models to generate crime forecasts. Afterwards, three epistemologies of predictive policing are distinguished: mathematical social science, social physics and machine (...) learning. Finally, it is shown that these epistemologies have significant implications for the constitution of predictive knowledge in terms of its genesis, scope, intelligibility and accessibility. It is the different ways future crimes are rendered knowledgeable in order to act upon them that reaffirm or reconfigure the status of criminological knowledge within the criminal justice system, direct the attention of law enforcement agencies to particular types of crimes and criminals and blank out others, satisfy the claim for the meaningfulness of predictions or break with it and allow professionals to understand the algorithmic systems they shall rely on or turn them into a black box. By distinguishing epistemologies and analysing their implications, this analysis provides insight into the techno-scientific foundations of predictive policing and enables us to critically engage with the socio-technical practices of algorithmic crime forecasting. (shrink)

Should you be targeted by police for a crime that AI predicts you will commit? In this paper, we analyse when, and to what extent, the person-based predictive policing (PP) — using AI technology to identify and handle individuals who are likely to breach the law — could be justifiably employed. We first examine PP’s epistemological limits, and then argue that these defects by no means refrain from its usage; they are worse in humans. Next, based on major (...) AI ethics guidelines (IEEE, EU, and RIKEN, etc.), we refine three basic moral principles specific to person-based PP. We also derive further requirements from case studies, including debates in Chicago, New Orleans, San Francisco, Tokyo, and cities in China. Instead of rejecting PP programs, we analyse what necessary conditions should be met for using the tool to achieve social good. While acknowledging its risks, we conclude that the person-based PP could be beneficial in community policing, especially when merging into a larger governance framework of the social safety net. (shrink)

Whereas using artificial intelligence (AI) to predict natural hazards is promising, applying a predictive policing algorithm (PPA) to predict human threats to others continues to be debated. Whereas PPAs were reported to be initially successful in Germany and Japan, the killing of Black Americans by police in the US has sparked a call to dismantle AI in law enforcement. However, although PPAs may statistically associate suspects with economically disadvantaged classes and ethnic minorities, the targeted groups they aim to (...) protect are often vulnerable populations as well (e.g., victims of human trafficking, kidnapping, domestic violence, or drug abuse). Thus, determining how to enhance the benefits of PPA while reducing bias through better management is important. In this paper, we propose a policy schema to address this issue. First, after clarifying relevant concepts, we examine major criticisms of PPAs and argue that some of them should be addressed. If banning AI or making it taboo is an unrealistic solution, we must learn from our errors to improve AI. We next identify additional challenges of PPAs and offer recommendations from a policy viewpoint. We conclude that the employment of PPAs should be merged into broader governance of the social safety net and audited publicly by parliament and civic society so that the unjust social structure that breeds bias can be revised. (shrink)

In light of the recent emergence of predictive techniques in law enforcement to forecast crimes before they occur, this paper examines the temporal operation of power exercised by predictive policing algorithms. I argue that predictive policing exercises power through a paranoid style that constitutes a form of temporal governmentality. Temporality is especially pertinent to understanding what is ethically at stake in predictive policing as it is continuous with a historical racialized practice of organizing, (...) managing, controlling, and stealing time. After first clarifying the concept of temporal governmentality, I apply this lens to Chicago Police Department’s Strategic Subject List. This predictive algorithm operates, I argue, through a paranoid logic that aims to preempt future possibilities of crime on the basis of a criminal past codified in historical crime data. (shrink)

This article offers a detailed examination of the content of predictive policing applications. Crime prediction machines are used by governments to shape the moral behavior of police. They serve not only to predict when and where crime is likely to occur, but also to regulate police work. They calculate equivalence ratios, distributing security across the territory based on multiple cost and social justice criteria. Tracing the origins of predictive policing in the Compstat system, this article studies (...) the shift from machines to explore intuitions to applications removing the reflexive dimension of proactivity, thus turning prediction into the medium for “dosage” metrics of police work quantities. Finally, the article discusses how, driven by a critical movement denouncing the discriminatory biases of predictive machines, developers seek to develop techniques to audit training dataset and ways to calculate the reasonable amount of stop and frisk over the population. (shrink)

Machine Learning has become a popular tool in a variety of applications in criminal justice, including sentencing and policing. Media has brought attention to the possibility of predictive policing systems causing disparate impacts and exacerbating social injustices. However, there is little academic research on the importance of fairness in machine learning applications in policing. Although prior research has shown that machine learning models can handle some tasks efficiently, they are susceptible to replicating systemic bias of previous (...) human decision-makers. While there is much research on fair machine learning in general, there is a need to investigate fair machine learning techniques as they pertain to the predictive policing. Therefore, we evaluate the existing publications in the field of fairness in machine learning and predictive policing to arrive at a set of standards for fair predictive policing. We also review the evaluations of ML applications in the area of criminal justice and potential techniques to improve these technologies going forward. We urge that the growing literature on fairness in ML be brought into conversation with the legal and social science concerns being raised about predictive policing. Lastly, in any area, including predictive policing, the pros and cons of the technology need to be evaluated holistically to determine whether and how the technology should be used in policing. (shrink)

This article links three rarely considered dimensions related to the implementation of artificial intelligence (AI)-based technologies in the form of predictive policing and discusses them in relation to liberal democratic societies. The three dimensions are the theoretical embedding and the workings of AI within anomic conditions (1), potential normative disorders emerging from them in the form of thinking errors and discriminatory practices (2) as well as the consequences of these disorders on the psychosocial, and emotional level (3). Against (...) this background, AI-induced anomie is conceptualized as a field of tension that refers to a systematic deterioration of democratic norms that are supposed to create ‘normative orders’, but which, when implemented through AI-supported measures, can reproduce existing discriminations, and establish new kinds of discriminatory relations. In future, these AI-based measures have the potential to lead to opposing normative disorders by emerging in the form of false social norms to an equally false Second Nature. They deprive persons involved of the possibility of individual appropriation of social norms and the specific emotional development associated with it. (shrink)

Fighting crime has historically been a field that drives technological innovation, and it can serve as an example of different governance styles in societies. Predictive policing is one of the recent innovations that covers technical trends such as machine learning, preventive crime fighting strategies, and actual policing in cities. However, it seems that a combination of exaggerated hopes produced by technology evangelists, media hype, and ignorance of the actual problems of the technology may have boosted sales of (...) software that supports policing by predicting offenders and crime areas. In this paper we analyse currently used predictive policing software packages with respect to common problems of data mining, and describe challenges that arise in the context of their socio-technical application. (shrink)

In this chapter I defend the construction of inclusive, tightly governed DNA databases, as long as police can access them only for the prosecution of the most serious crimes or less serious but very high-volume offences. I deny that that the ethics of collecting and using these data sets the pattern for other kinds of policing by big data, notably predictive policing. DNA databases are primarily used for matching newly gathered biometric data with stored data. After considering (...) and disputing a number of objections to this practice, I conclude that DNA databases used in this way are ethically acceptable, if not valuable, contributions to legitimate policing. (shrink)

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

We examine when and how police officers may avoid costly errors under stress by leveraging theoretical and empirical work on the biopsychosocial (BPS) model of challenge and threat. According to the BPS model, in motivated performance contexts (e.g., test taking, athletics), the evaluation of situational and task demands in relation to one’s perceived resources available to cope with those demands engenders distinct patterns of peripheral physiological responding. Individuals experience more challenge-like states in which blood circulates more efficiently in the periphery (...) when they evaluate their coping resources as meeting or exceeding the task demands. Conversely, individuals experience more threat-like states in which blood circulates less efficiently in the periphery when they view the situation or task demands as exceeding their coping resources. Patterns of response consistent with challenge and threat states have been shown to predict important performance and decision-making outcomes in stressful contexts, and repeated experiences of threat-like patterns of physiological activity are thought to have detrimental effects on long-term cardiovascular health. To date, however, research has not used the biopsychosocial model to understand police decision-making under stress. Here, we review relevant empirical work from the perspective of the BPS model concerning how minority status and power can shape challenge and threat responding and contribute to decision making under stress. We then detail a research agenda aimed at improving the translational value of research being conducted within the BPS model for understanding complex performance and decision making in the real world, including among law enforcement personnel. (shrink)

Predictive policing, the practice of using of algorithmic systems to forecast crime, is heralded by police departments as the new frontier of crime analysis. At the same time, it is opposed by civil rights groups, academics, and media outlets for being ‘biased’ and therefore discriminatory against communities of color. This paper argues that the prevailing focus on racial bias has overshadowed two normative factors that are essential to a full assessment of the moral permissibility of predictive (...) class='Hi'>policing: fairness in the social distribution of the benefits and burdens of policing as well as the distinctive role of consent in determining fair distribution. When these normative factors are given their due attention, several requirements emerge for the fair implementation of predictive policing. Among these requirements are that police departments inform and solicit buy-in from affected communities about strategic decision-making and that departments favor non-enforcement-oriented interventions. (shrink)

This book provides a comprehensive examination of the police role from within a broader philosophical context. Contending that the police are in the midst of an identity crisis that exacerbates unjustified law enforcement tactics, Luke William Hunt examines various major conceptions of the police—those seeing them as heroes, warriors, and guardians. The book looks at the police role considering the overarching societal goal of justice and seeks to present a synthetic theory that draws upon history, law, society, psychology, and philosophy. (...) Each major conception of the police role is examined in light of how it affects the pursuit of justice, and how it may be contrary to seeking justice holistically and collectively. The book sets forth a conception of the police role that is consistent with the basic values of a constitutional democracy in the liberal tradition. Hunt’s intent is that clarifying the police role will likewise elucidate any constraints upon policing strategies, including algorithmic strategies such as predictive policing. This book is essential reading for thoughtful policing and legal scholars as well as those interested in political philosophy, political theory, psychology, and related areas. Now more than ever, the nature of the police role is a philosophical topic that is relevant not just to police officials and social scientists, but to everyone. (shrink)

Policing in many parts of the world—the United States in particular—has embraced an archetypal model: a conception of the police based on the tenets of individuated archetypes, such as the heroic police “warrior” or “guardian.” Such policing has in part motivated moves to (1) a reallocative model: reallocating societal resources such that the police are no longer needed in society (defunding and abolishing) because reform strategies cannot fix the way societal problems become manifest in (archetypal) policing; and (...) (2) an algorithmic model: subsuming policing into technocratic judgements encoded in algorithms through strategies such as predictive policing (mitigating archetypal bias). This paper begins by considering the normative basis of the relationship between political community and policing. It then examines the justification of reallocative and algorithmic models in light of the relationship between political community and police. Given commitments to the depth and distribution of security—and proscriptions against dehumanizing strategies—the paper concludes that a nonideal-theory priority rule promoting respect for personhood (manifest in community and dignity-promoting policing strategies) is a necessary condition for the justification of the above models. (shrink)

From ‘connecting the dots’ and finding ‘the needle in the haystack’ to predictive policing and data mining for counterinsurgency, security professionals have increasingly adopted the language and methods of computing for the purposes of prediction. Digital devices and big data appear to offer answers to a wide array of problems of (in)security by promising insights into unknown futures. This article investigates the transformation of prediction today by placing it within governmental apparatuses of discipline, biopower and big data. Unlike (...) disciplinary and biopolitical governmentality, we argue that prediction with big data is underpinned by the production of a different time/space of ‘between-ness’. The digital mode of prediction with big data reconfigures how we are governed today, which we illustrate through an analysis of how predictive policing actualizes between-ness as hotspots and near-real-time decisions. (shrink)

This article sketches a case for the importance of allowing and protecting civil disobedience in a democratic society. There are weighty reasons for non-enforcement of certain laws under certain circumstances, which undermines the legalistic claim that justice requires police to faithfully (try to) enforce all laws at all times. Furthermore, questions about how the police should respond to disobedient demonstrations are not settled by popular theoretical treatments of civil disobedience. Police responses to disobedient demonstrations should be guided by a principle (...) of proportionality. This proportionality requirement is more stringent in cases of self-generated needs for self-defense. Common police tactics like “skirmish lines” predictably escalate interactions and create a need for further defensive force, thereby violating the proportionality requirement. (shrink)

This essay argues that Huey Newton’s philosophical explanation of US empire fills an epistemological gap in our thinking that provides us with a basis for understanding the emergence and operational application of predictive policing, Big Data, cutting-edge surveillance programs, and semi-autonomous weapons by US military and policing apparati to maintain control over racialized populations historically and in the (still ongoing) Global War on Terror today – a phenomenon that Black Studies scholars and Black philosophers alike have yet (...) to demonstrate the conceptual acumen to explain. Newton’s ability to explain the conceptual foundation of US empire alongside his prediction of the emergence and application of AI and other Big Data technologies towards the repression of dissidents, criminals, terrorists, and other racialized groups abroad gives intercommunalism the explanatory power to lay the basis for a genealogical account of Black repression that also advances our understanding of how the US as a liberal democratic regime engages in enemy target acquisition (the construction of racialized groups as threats internally and externally) to rationalize the brutal repression of these populations by military-police agencies whose operational application of new AI and computing-surveillance technologies and semi-autonomous weapons are conditioned by the intensity of their racialized dehumanization of the enemy. (shrink)

Steve Fuller's Social Epistemology offers a constructive program for integrating philosophy and sociology of science as normative knowledge policy, constrained by the linguistic, psychological, social, and political embodiment of knowledge. I endorse and elaborate upon Fuller's insistence that science studies should take seriously the embodiment of knowledge, but criticize his conception of knowledge policy on three grounds. Knowledge policy as Fuller conceives it seems committed to an untenable conception of a value?free or politically neutral social science. Knowledge policy studies are (...) also self?defeating, since they provide good reasons to ignore the recommendations of the knowledge?policy expert, and to prevent the successful development of a predictively adequate policy science. Finally, knowledge?policy studies cannot adequately respond to political conflict over knowledge production and dissemination. (shrink)

From George Floyd to Breonna Taylor, the brutal deaths of Black citizens at the hands of law enforcement have brought race and policing to the forefront of national debate in the United States. In The Ethics of Policing, Ben Jones and Eduardo Mendieta bring together an interdisciplinary group of scholars across the social sciences and humanities to reevaluate the role of the police and the ethical principles that guide their work. With contributors such as Tracey Meares, Michael Walzer, (...) and Franklin Zimring, this volume covers timely topics including race and policing, the use of aggressive tactics and deadly force, police abolitionism, and the use of new technologies like drones, body cameras, and predictive analytics, providing different perspectives on the past, present, and future of policing, with particular attention to discriminatory practices that have historically targeted Black and Brown communities. This volume offers cutting-edge insight into the ethical challenges facing the police and the institutions that oversee them. As high-profile cases of police brutality spark protests around the country, The Ethics of Policing raises questions about the proper role of law enforcement in a democratic society. (shrink)

Two uses of the modal verb would in police interrogation are examined. First, suspects use it to claim a disposition to act in ways inconsistent with whatever offence they are accused of. Second, police officers use it in challenging the suspect’s testimony, asking why a witness would lie. Both uses deploy a form of practical inferential reasoning from norms to facts, in the face of disputed testimony. The value of would is that its semantics provide for a sense of back-dated (...) predictability with regard to the actions in question. Further, although police officers provide minimal acknowledgement of suspects’ uses of the term, suspects tend to provide a response when police officers use it. This difference is explained by the different actions being done in each case - normative self assessments by suspects, and challenges by police officers - and their interactional and institutional relevance in and for police pursuit of factual testimony. (shrink)

The paper sets out the challenges facing the Police in respect of the detection and prevention of the volume crime of burglary. A discussion of data mining and decision support technologies that have the potential to address these issues is undertaken and illustrated with reference the authors’ work with three Police Services. The focus is upon the use of “soft” forensic evidence which refers to modus operandi and the temporal and geographical features of the crime, rather than “hard” evidence such (...) as DNA or fingerprint evidence. Three objectives underpin this paper. First, given the continuing expansion of forensic computing and its role in the emergent discipline of Crime Science, it is timely to present a review of existing methodologies and research. Second, it is important to extract some practical lessons concerning the application of computer science within this forensic domain. Finally, from the lessons to date, a set of conclusions will be advanced, including the need for multidisciplinary input to guide further developments in the design of such systems. The objectives are achieved by first considering the task performed by the intended systems users. The discussion proceeds by identifying the portions of these tasks for which automation would be both beneficial and feasible. The knowledge discovery from databases process is then described, starting with an examination of the data that police collect and the reasons for storing it. The discussion progresses to the development of crime matching and predictive knowledge which are operationalised in decision support software. The paper concludes by arguing that computer science technologies which can support criminal investigations are wide ranging and include geographical information systems displays, clustering and link analysis algorithms and the more complex use of data mining technology for profiling crimes or offenders and matching and predicting crimes. We also argue that knowledge from disciplines such as forensic psychology, criminology and statistics are essential to the efficient design of operationally valid systems. (shrink)

This article explores the relevance of the Theory of Planned Behavior to whistleblowing research, and considers whether its widely tested validity as a model of the link between attitudes, intention, and behavior might make it an appropriate candidate for a general theory to account for whistleblowing. This proposition is developed through an empirical test of the theory's predictive validity for whistleblowing intentions. Using a sample of 296 Korean police officers, the analysis showed that attitude, subjective norm, and perceived behavioral (...) control all had significantly positive main effects on internal whistleblowing intentions, but for external whistleblowing intentions only subjective norm was significant. The implications of these findings for applying the Theory of Planned Behavior to whistleblowing research are discussed. (shrink)

This paper explores recent vigilance attending pedophilia in the UK context. It examines governmental and popular responses to the perceived threat posed by child sex offenders, exhibited respectively in provisions for sex offender orders within the Crime and Disorder Act 1998, and in press and public campaigns for the “naming and shaming” of paedophiles. These two responses cohabit in current contexts of concern about childhood as innocence and vulnerability, and are worked out against the figure of the paedophile as a (...) “dangerous individual”; nevertheless, they invoke different visions of political community. Developing Foucault's observation that contemporary political rationalities combine two distinct models of political community, that of the juridically constituted polity and that of the society rendered calculable and organized through normalizing models of risk, the paper argues that both of these models are evident in governmental and popular responses to paedophilia. However, where the former, a technical and administrative response to a problem of social order, aims to achieve public safety through the professional prediction and management of risk, the latter is premised on the elimination of danger,demanding the public outing of paedophiles and their exorcism from the community. While these responses contest whether danger can be turned into risk through professional management, they are mutually enhancing in fostering governmental and popular concern with public and community safety. (shrink)

Reputation monitoring and the punishment of cheats are thought to be crucial to the viability and maintenance of human cooperation in large groups of non-kin. However, since the cost of policing moral norms must fall to those in the group, policing is itself a public good subject to exploitation by free riders. Recently, it has been suggested that belief in supernatural monitoring and punishment may discourage individuals from violating established moral norms and so facilitate human cooperation. Here we (...) use cross-cultural survey data from a global sample of 87 countries to show that beliefs about two related sources of supernatural monitoring and punishment — God and the afterlife —independently predict respondents' assessment of the justifiability of a range of moral transgressions. This relationship holds even after controlling for frequency of religious participation, country of origin, religious denomination and level of education. As well as corroborating experimental work, our findings suggest that, across cultural and religious backgrounds, beliefs about the permissibility of moral transgressions are tied to beliefs about supernatural monitoring and punishment, supporting arguments that these beliefs may be important promoters of cooperation in human groups. (shrink)

Executive functions represent higher order top-down mechanisms regulating information processing. While suboptimal EF have been studied in various patient groups, their impact on successful behavior is still not well described. Previously, it has been suggested that design fluency —a test including several simultaneous EF components mainly related to fluency, cognitive flexibility, and creativity—predicts successful behavior in a quickly changing environment where fast and dynamic adaptions are required, such as ball sports. We hypothesized that similar behaviors are of importance in the (...) selection process of elite police force applicants. To test this hypothesis, we compared elite police force applicants with a control group of police officer trainees. Although both groups were better than the norm, the elite police force applicants had a significantly better performance in DF total correct when adjusting for sex and age [F = 18.98, p < 0.001]. To understand how this capacity was altered by stress and tiredness, we re-tested the elite police force applicants several days during an extreme field assessment lasting 10 days. The results suggested that there was a lower than expected improvement in DF total correct and a decline in the DF3-subtest that includes a larger component of cognitive flexibility than the other subtests. Although there was a positive correlation between the baseline session and the re-test in DF3 [r = 0.49, p = 0.001], the applicants having the highest scores in the baseline test also displayed the largest percentage decline in the re-test [r = −0.46, p = 0.003]. In conclusion, our result suggests that higher order EF that include cognitive flexibility and creativity are of importance in the application for becoming an elite police officer but relatively compromised in a stressful situation. Moreover, as the decline is different between the individuals, the results suggest that applicants should be tested during baseline conditions and during stressful conditions to describe their cognitive capacity fully. (shrink)

Eyewitnesses to crimes sometimes search for a culprit on social media before viewing a police lineup, but it is not known whether this affects subsequent lineup identification accuracy. The present online study was conducted to address this. Two hundred and eighty-five participants viewed a mock crime video, and after a 15–20 min delay either viewed a mock social media site including the culprit, viewed a mock social media site including a lookalike, or completed a filler task. A week later, participants (...) made an identification from a photo lineup. It was predicted that searching for a culprit on social media containing the lookalike would reduce lineup identification accuracy. There was a significant association between social media exposure and lineup accuracy for the Target Present lineup, but for the Target Absent lineup there was no significant association with lineup identification accuracy. The results suggest that if an eyewitness sees a lookalike when conducting a self-directed search on social media, they are less likely to subsequently identify the culprit in the formal ID procedure. (shrink)

Racial capitalism depends on the reproduction of an existing racialized economic order. In this article, I argue that the disavowal of past injustice is a central way in which this reproduction is ensured and that market-based forms of knowledge production, such as for-profit predictive practices, play a crucial role in facilitating this disavowal. Recent debates about the fairness of algorithms, data justice, and predictive policing have intensified long-standing controversies, both popular and academic, about the way in which (...) statistical and financial modes of accounting and predicting articulate, represent and produce ascriptive categories of hierarchically ordered social difference, and reproduce unjust social hierarchies and inequalities. These debates have productively problematized the racial lives of seemingly apolitical predictive technologies and demanded the re-politicization of predictive practices. What has been missing from these debates so far, however, is a more explicit engagement with ways in which anti-racist movements and activists themselves have contested the entanglements of prediction and race making. I turn to a recent prominent example, namely the contestation over racial discrepancies in subprime lending to examine how fair lending activists have conceptualized and troubled the reproduction of a racialized economic order through for-profit predictive practices in the decade before the Great Financial Crisis. I situate this particular example in the broader historical and political context of politicizing prediction that first emerged with the ascendancy of a liberal, individualist-proprietary conception of risk, and the political problem space to which this has given rise. My analysis shows that actuarial conceptions of fairness continue to reverberate in anti-racist contestations of for-profit predictive practices, and that they tend to marginalize and undercut more radical strands of critique of the racialization of financial markets. Insofar as these modalities of contestation implicitly reproduce a liberal, proprietary-individualist conception of risk, I argue, they fail to effectively challenge the quasi-alchemical transformation of injustice into personal responsibility, and thus contribute to the disavowal of past injustice. (shrink)

Bernard Harcourt, Against Prediction: Profiling, Policing, and Punishing in an Actuarial Age Chicago: University of Chicago Press, 2006, 336pp.

Objective: Based on the theory of perceived organizational support (POS), conservation of resource (COR) and job demands-resources (JD-R) model, this study establishes a moderated mediation model to test the role of job satisfaction in mediating the relationship between perceived organizational support and job burnout, as well as the role of regulatory emotional self-efficacy in moderating the above mediating process. Method: A total of 784 police officers were surveyed with the Perceived Organizational Support Scale, the Job Burnout Questionnaire, the Regulatory Emotional (...) Self-Efficacy Scale, and the Minnesota Job Satisfaction Questionnaire. Results: (1) After controlling for gender, seniority, age, police classification, education, and marital status, regression analysis showed a significant negative correlation between perceived organizational support and burnout (r = -0.42, p < 0.01), and the former had a significant negative predictive effect on job burnout (β = -0.42, p < 0.001). (2) The mediating effect test shows that job satisfaction plays a partial role in mediating the relationship between perceived organizational support and job burnout. (3) Through the analysis of the moderated mediation model test, regulatory emotional self-efficacy moderates the first half of the path of “perceived organizational support → job satisfaction → job burnout". Conclusion: Perceived organizational support not only directly affects police job burnout but also indirectly affects police job burnout through job satisfaction. Regulatory emotional self-efficacy enhances the influence of organizational support on job satisfaction. This study indicates the combined effect of perceived organizational support, job satisfaction and regulatory emotional self-efficacy on job burnout and has certain guiding significance for alleviating police job burnout. Keywords: Perceived organizational support, Job burnout, Job satisfaction, Regulatory emotional self-efficacy, Moderated mediation. (shrink)

This article focuses on the question of whether the task of the security authorities to protect public safety can justify unlawful encroachments on fundamental rights committed by them. First, the concept of security is analysed and criticised. This is followed by an analysis of the normative compatibility of the concept of security with the legal system. In particular, the legal principles and the concepts of possibility, probability and risk as standards of assessment for the justification of encroachments on fundamental rights (...) by security authorities as well as predictive policing as measures for determining the concepts are discussed. It is shown that the task of the security authorities to protect public safety cannot justify unlawful encroachments on fundamental rights in any way. (shrink)

Affective realism, roughly the hypothesis that you “perceive what you feel”, has recently been put forward as a novel, empirically-backed explanation of police shooting errors. The affective states involved in policing in high-pressure situations result in police officers literally seeing guns even when none are present. The aim of this paper is to (i) unpack the implications of this explanation for assessing police culpability and (ii) determine whether we should take these implications at face value. I argue that while (...) affective realism stands to diminish, if not eliminate, the moral and legal responsibilities of officers who have made shooting errors, the empirical data itself does not directly support such a radical rethink of police culpability. (shrink)

ABSTRACTIn the United States, constitutional and statutory law reinforce the right of all children to receive an education, regardless of their citizenship or immigration status. In a time of heightened anti-immigrant sentiment and law enforcement, however, partnerships among school districts, local law enforcement, and the U.S. Departments of Justice and Homeland Security subject undocumented and unaccompanied minor students to indefensible levels of risk for detention and deportation. We identify three stances that U.S. schools may take in the face of a (...) potential ‘school-to-deportation pipeline.’ Schools that engage in intentional collaboration actively increase detention and deportation by referring students to immigration officials for criminal, non-criminal, and even non-disciplinary activity. Schools that engage in predictable complicity may not intend to subject their undocumented and unaccompanied minor students to detention or deportation, but still put students at risk by involving police in school policies. We argue that U.S. schools should instead engage in proactive protection of immigrant students and families, including actively resisting federal policies when necessary. (shrink)

The literature studying the characteristics associated with revictimization in Intimate Partner Violence is heterogeneous and inconclusive. The absence of studies on the role of the emotional variables of the victims and the failure to distinguish revictimization by the same or different aggressors are two of the main limitations in this area of research. The aim of this work was to study the relative contribution of the material, social, and emotional resources available to IPV victims in predicting revictimization by the same (...) or different perpetrators. The sample consisted of 290 women registered in the city of Madrid who had filed at least one police report for intimate partner violence. The material resources of the victims were evaluated through their level of monthly income and employability status, the social resources through perceived social support, and the emotional resources through emotional regulation and coping strategies. Hierarchical multinomial logistic regression models were estimated to predict single-offender victimization, same-offender revictimization, and multiple-offender revictimization. The results revealed that: differentiating between revictimization by the same and different aggressors improved the fit of the model by 50.8% compared to when only differentiating between victimized and revictimized women; material resources had no significant weight in the prediction of any type of revictimization; SRV women had more social support than VSRDA women ;, those victims who had made several reports to the authorities of violence by different aggressors, had worse emotional regulation than those victims who had made a single report to the authorities ; and VSRDA obtained the worst mental health indexes and they used more coping strategies based on positive reappraisal than the VSR women and those victims with several reports by the same aggressor. These results show that being a victim of several episodes of intimate partner violence by different aggressors should be understood as a form of revictimization of great severity associated with worse emotional regulation and less social support. (shrink)

Incels (involuntary celibates) are part of a broader misogynistic culture known as the manosphere. Some communities within the manosphere, including incels, promote gender-based violence through misogynistic rhetoric and ideology. Incels are men who struggle to form romantic relationships and thus seek solace in online forums to find a sense of purpose and community. The community is organised around an ideology and a hierarchical classification of members. This paper presents a computational linguistic analysis of the utterances made within the community. We (...) analyse the linguistic patterns of six different ranks of users: paragons, high-rank users, low-rank users, greycels, banned users, and self-banned/deleted users. We conducted an analysis of the sentiments expressed between ranks and of the affective attitude of posters when discussing a variety of topics. We then we analysed linguistic features, also conditioned on the rank of the poster. These analyses reveal qualitative differences between users of different ranks in how they express themselves and their sentiments. Finally, we trained models based on the linguistic features of users’ posts and show that already based on this information it is possible to predict the rank of users. Overall, our results indicate that the incel community has developed distinctive linguistic patterns to disseminate their ideology and that these linguistic patterns vary according to the rank of an incel within the community. This methodology offers a robust framework for studying similar echo chamber-like communities. (shrink)

ABSTRACT: So far in this book, we have examined algorithmic decision systems from three autonomy-based perspectives: in terms of what we owe autonomous agents (chapters 3 and 4), in terms of the conditions required for people to act autonomously (chapters 5 and 6), and in terms of the responsibilities of agents (chapter 7). -/- In this chapter we turn to the ways in which autonomy underwrites democratic governance. Political authority, which is to say the ability of a government to exercise (...) power, may be justifiable or not. Whether it is justified and how it can come to be justified is a question of political legitimacy. Political legitimacy is another way in which autonomy and responsibility are linked. This relationship is the basis of the current chapter, and it is important in understanding the moral salience of algorithmic systems. We will draw the connection as follows. We begin, in section 8.1, by describing two uses of technology: crime predicting technology used to drive policing practices and social media technology used to influence elections (including by Cambridge Analytica and by the Internet Research Agency). In section 8.2 we consider several views of legitimacy and argue for a hybrid version of normative legitimacy based on one recently offered by Fabienne Peter. In section 8.3 we will explain that the connection between political legitimacy and autonomy is that legitimacy is grounded in legitimating processes, which are in turn based on autonomy. Algorithmic systems—among them PredPol and the Cambridge Analytica-Facebook-Internet Research Agency amalgam—can hinder that legitimation process and conflict with democratic legitimacy, as we argue in section 8.4. We will conclude by returning to several cases that serve as through-lines to the book: Loomis, Wagner, and Houston Schools. -/- The link below is to an open-access copy of the chapter. (shrink)

This article examines the “aesthetic” and “prescient” turn in the surveillant assemblage and the various ways in which risk technologies in local law enforcement are reshaping the post hoc traditions of the criminal justice system. The rise of predictive policing and crime prevention software illustrate not only how the world of risk management solutions for public security is shifting from sovereign borders to inner-city streets but also how the practices of authorization are allowing software systems to become proxy (...) forms of sovereign power. The article also examines how corporate strategies and law enforcement initiatives align themselves through media, connectivity, and consumer-oriented opt-in strategies that endeavor to “mold” and “deputize” ordinary individuals into obedient and patriotic citizens. (shrink)

Die Erkenntnis, dass Algorithmen diskriminieren, benachteiligen und ausschließen, ist mittlerweile weit verbreitet und anerkannt. Programme zur Verwendung im predictive policing, zur Berechnung von Rückfälligkeitswahrscheinlichkeiten bei Straftäter:innen oder zur automatischen Gesichtserkennung diskriminieren vor allem gegen nicht-Weiße Menschen. Im Zuge dieser Erkenntnis wird auch vereinzelt die Verbindung zu epistemischer Ungerechtigkeit hergestellt, wobei die meisten Beiträge die Verbindungen zwischen Algorithmen und epistemischer Ungerechtigkeit nicht im Detail analysieren. Dieser Artikel unternimmt einen Versuch, diese Lücke in der Literatur zu verkleinern. Dabei umreiße ich (...) zunächst das Feld der Algorithmen, um so die Entitäten, die epistemisch ungerecht sein könnten, klar zu fassen und zu unterscheiden. Dann erläutere ich eine Auswahl von epistemischen Ungerechtigkeiten, die für die Analyse von ungerechten Algorithmen relevant sind. Schließlich führe ich epistemische Ungerechtigkeiten und Algorithmen zusammen und zeige anhand von drei Beispielen – automatische Geschlechtserkennung, Googles Suchmaschinen-Algorithmus, PredPol – dass Algorithmen an testimonialer Ungerechtigkeit und hermeneutischer Ungerechtigkeit beteiligt sind. Sie tragen so zudem auf verschiedenen Ebenen zur Exklusion von marginalisierten Gruppen bei. (shrink)

As digital labour becomes more widespread across the uneven geographies of race, gender, class and ability, and as histories of colonialism and inequality get drawn into these forms of labour, our imagination of what these worlds contain similarly needs to expand. Beyond the sensationalist images of the ‘brogrammer’ and the call-centre worker lie intersecting labour practices that bring together histories of bodies and materiality in new ways. In the recent past, these entanglements have yielded oppressive results. As scandals over (...) class='Hi'>predictive policing, data mining and algorithmic racism unfold, digital labourers need both to be accounted for in analyses of algorithmic technologies and to be counted among the designers of these platforms. This article attempts to do both of these by highlighting particular cases in which digital labour frames embodied subjects, and to propose ways digital workers might train themselves to recognise ethical problems as they are emerging. I use the idea of attunements as a way to grasp what these forms of care might look like for the digital worker. (shrink)

Today, a major technological trend is the increasing focus on the person: technical systems personalize, customize, and tailor to the person in both beneficial and troubling ways. This trend has moved beyond the realm of commerce and has become a matter of public governance, where systems for citizen risk scoring, predictive policing, and social credit scores proliferate. What these systems have in common is that they may target the person and her ethical and political dispositions, her virtues. Virtue (...) ethics is the most appropriate approach for evaluating the impacts of these new systems, which has translated in a revival of talk about virtue in technology ethics. Yet, the focus on individual dispositions has rightly been criticized for lacking a concern with the political collective and institutional structures. This paper advocates a new direction of research into civic virtue, which is situated in between personal dispositions and structures of governance. First, it surveys the discourse on virtue ethics of technology, emphasizing its neglect of the political dimension of impacts of emerging technologies. Second, it presents a pluralist conception of civic virtue that enables us to scrutinize the impact of technology on civic virtue on three different levels of reciprocal reputation building, the cultivation of internal goods, and excellence in the public sphere. Third, it illustrates the benefits of this conceptions by discussing some paradigmatic examples of emerging technologies that aim to cultivate civic virtue. (shrink)

Traditional notions of crime control often position the police against an individual, known or not yet known, who is responsible for the commission of a crime. However, with increasingly sophisticated technology, policing increasingly prioritizes the prevention of crime, making it necessary to ascertain who, or what class of persons, may be the next likely criminal before a crime can be committed, termed predictive policing. This causes a shift from individualized suspicion toward predictive profiling that may sway (...) the expectations of a police patrol. Classically, where a patrol officer forms reasonable suspicion prior to a stop, it is based upon his/her analysis of the situation taken as a whole in context. However, where a predictive profile is employed, information available to the officer accordingly adjusts his/her perception of context and affects the application of the reasonable suspicion standard. This article addresses the way in which new approaches to forming reasonable suspicion affect the due process protection of individuals’ fundamental rights. It argues that while an officer still operates with good faith discretion, using predictive profiling causes reasonable suspicion to be based on an augmented understanding of reality and as a result, due process guarantees are weakened. The rights to non-discrimination and the presumption of innocence are assessed and argued as illustrative of this weakening and shift in policing standards. The article ultimately argues that while predictive policing cannot be categorically labeled as inconsistent with criminal justice, changes as seemingly moderate as the manner in which discretion operates have larger effects on individuals’ rights. (shrink)

Law-enforcement agencies are increasingly able to leverage crime statistics to make risk predictions for particular individuals, employing a form of inference that some condemn as violating the right to be “treated as an individual.” I suggest that the right encodes agents’ entitlement to a fair distribution of the burdens and benefits of the rule of law. Rather than precluding statistical prediction, it requires that citizens be able to anticipate which variables will be used as predictors and act intentionally to avoid (...) them. Furthermore, it condemns reliance on various indexes of distributive injustice, or unchosen properties, as evidence of law-breaking. (shrink)

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. (...) Using these case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core. (shrink)

The relationship between politics and the digital has largely been characterized as one of epochal change. The respective theories understand the digital as external to politics and society, as an autonomous driver for global, unilateral transformation. Rather than supporting such singular accounts of the relationship between politics and the digital, this article argues for its specificity: the digital is best examined in terms of folds within existing socio-technical configurations, and as an artefact with a set of affordances that are shaped (...) and filled with meaning by social practice. In conceptualizing the digital as numeric, countable, computable, material, storable, searchable, transferable, networkable and traceable, fabricated and interpreted, it becomes clear that the digital cannot be divorced from the social. These affordances of the digital are discussed in relation to specific political, digital practices that are further developed in the different contributions in this special issue, such as predictive policing (Aradau and Blanke, this issue), data protection (Bellanova, this issue), extremist recruitment videos (Leander, this issue), political acclamation (Dean, this issue), and pandemic simulations (Opitz, this issue). (shrink)

This paper responds to recent work highlighting the problematic racial politics of predictive policing technologies. Drawing on Michel Foucault’s account of ethics as counter-conduct, I develop a set of ethical techniques for resisting the racial injustice at work in predictive policing. This framework has the advantage, I argue, of not reducing the ethical issues of predictive policing solely to epistemic concerns of transparency. What I suggest is that we think about the ethics of technology (...) less as an epistemic problem than as a problem for action or practice. By thinking of ethics in terms of resistant practices, we can begin to consider a notion of responsibility that holds us and the technologies we bind ourselves to accountable for the harms created by this bond. (shrink)

This article further elaborates on the “pre-crime society” thesis as developed and examined by Arrigo and Sellers. Specifically, the article focuses on the ultramodern era of digital inter-connectivity and argues that productive psychic desire is held clinically captive. Ultra-modernity is populated by cyber-forms of human relating and of economic exchange that nurture hyper-securitization. We discuss how the maintenance of hyper-securitization supports a pre-crime society, and how hyper-securitization’s object of desire consists of sign-optics. We argue that the co-constitutive forces of this (...) desire represent the sign-exchange values of post-criminology. Post-criminology’s signifiers include, among others, “predictive policing”, “crime mapping”, and “actuarial penology.” Post-criminology’s signifieds produce captivity-generating bio-digital “laws” of human relatedness. Among others, these laws sanction the neurosis of de-vitalization and certify the psychosis of finalization. We explain how the unchecked excess neutralizations of de-vitalization and finalization cultivate clinical captivity. Clinical captivity is a social anxiety in which reciprocal consciousness, inter-subjectivity, and mutual power are limited in existence or are denied an existence. (shrink)

What are the challenges of turning data subjects into research participants—and how can we approach this task responsibly? In this paper, we develop a methodology for studying the lived experiences of people who are subject to automated scoring systems. Unlike most media technologies, automated scoring systems are designed to track and rate specific qualities of people without their active participation. Credit scoring, risk assessments, and predictive policing all operate obliquely in the background long before they come to matter. (...) In doing so, they constitute a problem not only for those subject to these systems but also for researchers who try to study their experience. Specifically, we identify three challenges that are distinct to studying experiences of automated scoring: limited awareness, embeddedness, and ongoing inquiry. Starting from the observation that coming to terms with one's position as a data subject constitutes a form of learning in its own right, we propose a research strategy called critical companionship. Originally articulated in the context of nursing research, critical companionship invites us to accompany a data subject over time, paying critical attention to how the participant's and the researcher's inquiries complicate and constitute each other. We illustrate the strengths and limitations of this methodology with materials from a recent study we conducted about people's credit repair practices and sketch a set of sensibilities for studying contemporary scoring systems from the margins. (shrink)

This article explores the trend of increasing automation in law enforcement and criminal justice settings through three use cases: predictive policing, machine evidence and recidivism algorithms. The focus lies on artificial-intelligence-driven tools and technologies employed, whether at pre-investigation stages or within criminal proceedings, in order to decode human behaviour and facilitate decision-making as to whom to investigate, arrest, prosecute, and eventually punish. In this context, this article first underlines the existence of a persistent dilemma between the goal of (...) increasing the operational efficiency of police and judicial authorities and that of safeguarding fundamental rights of the affected individuals. Subsequently, it shifts the focus onto key principles of criminal procedure and the presumption of innocence in particular. Using Article 6 ECHR and the Directive (EU) 2016/343 as a starting point, it discusses challenges relating to the protective scope of presumption of innocence, the burden of proof rule and the _in dubio pro reo_ principle as core elements of it. Given the transformations law enforcement and criminal proceedings go through in the era of algorithms, big data and artificial intelligence, this article advocates the adoption of specific procedural safeguards that will uphold rule of law requirements, and particularly transparency, fairness and explainability. In doing so, it also takes into account EU legislative initiatives, including the reform of the EU data protection _acquis_, the E-evidence Proposal, and the Proposal for an EU AI Act. Additionally, it argues in favour of revisiting the protective scope of key fundamental rights, considering, _inter alia_, the new dimensions suspicion has acquired. (shrink)

The Oxford Handbook of Digital Ethics is a lively and authoritative guide to ethical issues related to digital technologies, with a special emphasis on AI. Philosophers with a wide range of expertise cover thirty-seven topics: from the right to have access to internet, to trolling and online shaming, speech on social media, fake news, sex robots and dating online, persuasive technology, value alignment, algorithmic bias, predictive policing, price discrimination online, medical AI, privacy and surveillance, automating democracy, the future (...) of work, and AI and existential risk, among others. Each chapter gives a rigorous map of the ethical terrain, engaging critically with the most notable work in the area, and pointing directions for future research. (shrink)