1 Einleitung -- 2 Die Multimodalität von Diskursen -- 3 Die dispositive Konstruktion multimodaler Wirklichkeit -- 4 Zur theorie-empirischen Rekonstruktion dispositiver Konstruktionen von Wirklichkeit -- 5 Drogentests als Prä-Mediatoren -- 6 Drogentests als scripted technology -- 7 Drogentests als Agenten mechanischer Objektivität -- 8 Drogentests als Skopische Mediatoren -- 9 Über die Schließung epistemischer Lücken: Drogentesten als security chain -- 10 Zwei Schlussfolgerungen: Materialitätssensible Diskursanalytik und Soziologie des Testens.
In diesem Open-Access-Buch wird unter Rückgriff auf einen multimodalen Diskursbegriff das Vorgehen für eine soziotechnisch fundierte Dispositivanalyse entwickelt, die auf die produktive Rolle von Materialität in Diskursen fokussiert. Mit der Frage nach der Stellung von Artefakten in Diskursen werden grundlegende Aspekte der Diskurstheorie und -analytik adressiert, die sich vor allem auf die Bestimmung der Ränder von Diskursen sowie der diskursiven Wirkmächtigkeit von Dingen beziehen. Auf diesem Wege wird eine Diskussion um die passenden konzeptuellen, begrifflichen und methodischen Instrumente diskursanalytischer Studien herausgefordert, zu der dieses Buch einen theoretischen und empirischen Beitrag leistet. Die entwickelte multimodale Dispositivanalyse wird im Rahmen einer qualitativ-empirischen Studie zu Drogentestpraktiken am Arbeitsplatz und im Straßenverkehr exemplarisch umgesetzt. Drogentests werden im Zuge dessen als Diskursaktanten verstanden, die im soziotechnischen Zusammenspiel mit den menschlichen Anwender*innen an der dispositiven Konstruktion von Wirklichkeit wirkmächtig beteiligt sind.
In numerous police departments in German-speaking countries, algorithmic-supported prediction technologies are being used to enable predictive policing. Currently, mostly predictions about the probability of future domestic burglaries are generated for certain spatiotemporal constellations, primarily using police crime data. In this article, this use of prediction software by the police is analysed as a potential extra-legal innovation; an innovation, which contains onsiderable potential for legislative and judicial adaptations. Above all, this is due to its substantial reconfiguration of the temporality of police knowledge but also because of its algorithmic underpinning. The existing police, criminal justice and data protection regulations tend to reach their limits when confronted with these new, algorithmic police practices. With recourse to qualitative data on the execution of predictive policing in the German-speaking area, this argument is made plausible empirically, contouring predictive policing as a driver of legal innovation. As background to these considerations serves the conviction that new technologies have intended as well as unintended effects, which are particularly effective on a practical everyday level and, by doing so, are likely to animate legal creation from below. ; In zahlreichen Polizeibehörden im deutschsprachigen Raum werden algorithmengestützte Prognosetechnologien angewendet, die vorhersagebasierte Polizeiarbeit (Predictive Policing) ermöglichen sollen. Gegenwärtig werden dabei vor allem auf Basis von polizeilichen Kriminalitätsdaten Vorhersagen über die Wahrscheinlichkeit zukünftiger Wohnungseinbruchdiebstähle für bestimmte raumzeitliche Konstellationen generiert. Diese polizeiliche Nutzung von Prognosesoftware wird in diesem Beitrag als mögliche rechtsexterne Innovation analysiert, die auf Grund ihrer temporalen Neukonfiguration polizeilichen Wissens und ihrer algorithmischen Fundierung erhebliches Potential für legislative und judikative Adaptionen enthält, da die existierenden polizei- und strafrechtlichen Regelungen mit diesen neuen, algorithmengestützten Polizeipraktiken an ihre Grenzen stoßen. Unter Rückgriff auf qualitative Daten über die Durchführung von Predictive Policing im deutschsprachigen Raum wird diese These empirisch fundiert plausibilisiert und mithin Predictive Policing als Treiber rechtlicher Innovationen konturiert. Den Hintergrund dieser Überlegungen bildet die Überzeugung, dass neue Technologien intendierte wie auch nicht-intendierte Folgeeffekte haben, die gerade auf praktischer Alltagsebene wirksam werden und auf diese Weise Rechtskreationen from below animieren können.
This book explores how predictive policing transforms police work. Police departments around the world have started to use data-driven applications to produce crime forecasts and intervene into the future through targeted prevention measures. Based on three years of field research in Germany and Switzerland, this book provides a theoretically sophisticated and empirically detailed account of how the police produce and act upon criminal futures as part of their everyday work practices. The authors argue that predictive policing must not be analyzed as an isolated technological artifact, but as part of a larger sociotechnical system that is embedded in organizational structures and occupational cultures. The book highlights how, for crime prediction software to come to matter and play a role in more efficient and targeted police work, several translation processes are needed to align human and nonhuman actors across different divisions of police work. Police work is a key function for the production and maintenance of public order, but it can also discriminate, exclude, and violate civil liberties and human rights. When criminal futures come into being in the form of algorithmically produced risk estimates, this can have wide-ranging consequences. Building on empirical findings, the book presents a number of practical recommendations for the prudent use of algorithmic analysis tools in police work that will speak to the protection of civil liberties and human rights as much as they will speak to the professional needs of police organizations. An accessible and compelling read, this book will appeal to students and scholars of criminology, sociology, and cultural studies as well as to police practitioners and civil liberties advocates, in addition to all those who are interested in how to implement reasonable forms of data-driven policing.
This book explores how predictive policing transforms police work. Police departments around the world have started to use data-driven applications to produce crime forecasts and intervene into the future through targeted prevention measures. Based on three years of field research in Germany and Switzerland, this book provides a theoretically sophisticated and empirically detailed account of how the police produce and act upon criminal futures as part of their everyday work practices. The authors argue that predictive policing must not be analyzed as an isolated technological artifact, but as part of a larger sociotechnical system that is embedded in organizational structures and occupational cultures. The book highlights how, for crime prediction software to come to matter and play a role in more efficient and targeted police work, several translation processes are needed to align human and nonhuman actors across different divisions of police work. Police work is a key function for the production and maintenance of public order, but it can also discriminate, exclude, and violate civil liberties and human rights. When criminal futures come into being in the form of algorithmically produced risk estimates, this can have wide-ranging consequences. Building on empirical findings, the book presents a number of practical recommendations for the prudent use of algorithmic analysis tools in police work that will speak to the protection of civil liberties and human rights as much as they will speak to the professional needs of police organizations. An accessible and compelling read, this book will appeal to students and scholars of criminology, sociology, and cultural studies as well as to police practitioners and civil liberties advocates, in addition to all those who are interested in how to implement reasonable forms of data-driven policing.
In this book, Simon Egbert and CSS' Matthias Leese explore how predictive policing transforms police work. Police departments around the world have started to use data-driven applications to produce crime forecasts and intervene into the future through targeted prevention measures. The authors argue that predictive policing must not be analyzed as an isolated technological artifact, but as part of a larger sociotechnical system that is embedded in organizational structures and occupational cultures. Building on empirical findings from three years of field research in Germany and Switzerland, the book presents a number of practical recommendations for the prudent use of algorithmic analysis tools in police work that will speak to the protection of civil liberties and human rights as much as they will speak to the professional needs of police organizations. ; Simon Egbert und CSS Forscher Matthias Leese untersuchen, wie Predictive Policing die Polizeiarbeit verändert. Polizeidienststellen auf der ganzen Welt haben damit begonnen, datengesteuerte Anwendungen zu nutzen, um Kriminalitätsprognosen zu erstellen und präventive Massnahmen besser zu steuern. Die Autoren argumentieren, dass Predictive Policing nicht als isoliertes technologisches Artefakt analysiert werden darf, sondern als Teil eines grösseren soziotechnischen Systems, das in Organisationsstrukturen und Berufskulturen eingebettet ist. Aufbauend auf empirischen Erkenntnissen aus drei Jahren Feldforschung in Deutschland und der Schweiz präsentiert das Buch eine Reihe praktischer Empfehlungen für den umsichtigen Einsatz algorithmischer Analysewerkzeuge in der Polizeiarbeit, die sowohl dem Schutz von Bürger- und Menschenrechten als auch den professionellen Bedürfnissen von Polizeiorganisationen gerecht werden.
For several years now, crime prediction software operating on the basis of data analysis and algorithmic pattern detection has been employed by police departments throughout the world. As these technologies aim at forestalling criminal events, they may aptly be understood as elements of preventive strategies. Do they also initiate a logic of preemptive policing, as several authors have suggested? Using the example of crime prediction software that is used in German-speaking countries, the article shows how current forms of predictive policing echo classical modes of risk calculation: usually employed in connection with domestic burglary, they help police to identify potential high-risk areas by extrapolating past crime patterns into the future. However, preemptive elements also emerge, to the extent that the software fosters 'possibilistic' thinking in police operations. Moreover, current advances in crime prediction technologies give us a quite different picture of a probable future of preemptive policing. Following a general trend of data-driven government that draws on self-learning algorithms and heterogeneous data sources, crime prediction software will likely be integrated into assemblages of predictive technologies where criminal events are indeed foreclosed before they can unfold and emerge, implying preemptive police action.
