The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers must provide their decision-subjects with justifications for their automated system’s outputs, but what kinds of broader principles should we expect such justifications to appeal to? Drawing from political philosophy, I present an account of algorithmic accountability in terms of the democratic ideal of ‘public reason’. I argue that situating demands for algorithmic accountability within this justificatory framework enables us to (...) better articulate their purpose and assess the adequacy of efforts toward them. (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)

Due to the ongoing advancements in technology, socio-technical collaboration has become increasingly prevalent. This poses challenges in terms of governance and accountability, as well as issues in various other fields. Therefore, it is crucial to familiarize decision-makers and researchers with the core of human–machine collaboration. This study introduces a taxonomy that enables identification of the very nature of human–machine interaction. A literature review has revealed that automation and technical autonomy are main parameters for describing and understanding such interaction. Both aspects (...) must be carefully evaluated, as their increase has potentially far-reaching consequences. Hence, these two concepts comprise the taxonomy’s axes. Five levels of automation and five levels of technical autonomy are introduced below, based on the assumption that both automation and autonomy are gradual. The levels of automation were developed from existing approaches; those of autonomy were carefully derived from a review of the literature. The taxonomy’s use is also explained, as are its limitations and avenues for further research. (shrink)

Through a theoretical examination of the preventive turn in criminal law and justice which has gained momentum in Anglo-American criminal justice systems since the late-twentieth century, The Preventive Turn in Criminal Law demonstrates how recent transformations in criminal law and justiceare intrinsically related to and embedded in the way liberal society and liberal law have been imagined, developed, and conditioned by its social, political, and historical context. Henrique Carvalho identifies a tension between the idea of punishment as an expression of (...) individual justice, andprevention as a manifestation of the need for security and the promotion of welfare. Tracing this tension back to an intrinsic ambivalence within the modern conception of individual liberty, which is both repressed and preserved by liberal conceptions of responsibility and punishment, Carvalhoproves that as long as this ambivalence remains unexamined, liberal law has the potential to both promote and undermine individual justice.Engaging with the dominant contemporary literature on criminal law, prevention, risk, security, and criminalisation, this volume deploys a theoretical perspective developed through a critical analysis of both classical and contemporary works of social and political theory. The book reveals that thepervasiveness of prevention in 21st century criminal justice systems represents not only the consequence of new and unprecedented features of contemporary politics and society, but also the manifestation of essential aspects of the liberal legal and political tradition. (shrink)

In a 1955 lecture the physicist Richard Feynman reflected on the place of doubt within scientific practice. ‘Permit us to question, to doubt, to not be sure’, proposed Feynman, ‘it is possible to live and not to know’. In our contemporary world, the science of machine learning algorithms appears to transform the relations between science, knowledge and doubt, to make even the most doubtful event amenable to action. What might it mean to ‘leave room for doubt’ or ‘to live and (...) not to know’ in our contemporary culture, where the algorithm plays a major role in the calculability of doubts? I propose a posthuman mode of doubt that decentres the liberal humanist subject. In the science of machine learning algorithms the doubts of human and technological beings nonetheless dwell together, opening onto a future that is never fully reduced to the single output signal, to the optimised target. (shrink)