67. Intelligence-led policing: investigating the Dystopia
Vasilis Galis; Helene Oppen Ingebrigtsen Gundhus, University of Oslo; Vasilis Vlassis, IT University of Copenhagen; Anu Masso, Tallinn University of Technology; Anda Adamsone-Fiskovica, Baltic Studies Centre
Posted: February 28, 2022 Accepted Languages: English/Inglés/Inglês
Given the political, social, and economic instability that arose during the latest financial crisis, the negative prognosis for the coming years (World Bank 2019), as well as the issuing of stay-at-home orders/shelter-in-place orders as a response to the COVID19 pandemic, the police have gained increasing attention for their role and militarized tactics to absorb socio-legal turbulences and to maintain order (rua Wall 2018; 2020). In this context of a fragile and instable financial and sociopolitical landscape, law enforcement lies at the fore front of digitalization both in Europe and globally and constitutes perhaps one of the most emblematic public sector institutions going through a significant transformation in the age of Big Data. We know very little about how big data, humans and software co-constitute crime, crime solving and/or prediction. There is a conceptual and empirical need for research that simultaneously examines how police officers are using data driven technologies and focuses on how their varied usage affects not only crime solving/prevention but also the technologies themselves. The rapid evolution of machine learning, data mining and data analysis, have advanced crime analysis and constituted data technologies an imperative for police work (Ferguson 2017). A number of software packages for data analytics are used by police officers for identifying patterns that indicate future spatial and temporal distributions of crime (Kaufmann et al. 2018). This transformation refers to all police decision-making processes that are driven by data technologies aiming to prioritize specific crimes, hotspots and offender groups (Kaufmann 2018). Predictive policing is by definition aimed at anticipating the future. What does law enforcement mean after digitalization? What values are embedded in digital policing technologies, and how are these negotiated and transformed before and after implementation? How can STS inspired methodologies and conceptual frameworks contribute to studying intelligence-led policing, considering the often non-transparent development and implementation of digital police technologies? In this panel, we aim to include a diverse set of ideas, approaches, and methods to problematize how social and cultural values, bias, and legal adjustments are conceived and embedded in data-driven police innovations, as well as experienced, negotiated and practiced by citizens, law makers, police officers and developers.
