Presented at
32C3 (2015),
Dec. 28, 2015, 4 p.m.
(30 minutes)
This talk will focus on the potential ability of data disaggregated by race and ethnicity to reduce discriminatory policing in Germany. In the UK, data has been collected during police procedures, allowing for a monitoring and evaluation of discriminatory policing practices. Unfortunately, such an empirically driven policy approach is not currently possible in Germany. This talk will argue that, as a first step, a policy based off the UK approach towards data collection be implemented in Germany to incorporate, rather than ignore, Germany’s diverse identities, and to allow for empirically driven and more effective policing.
As social exclusion and racial discrimination are highly tied to policing practices, it is essential that a reduction of discriminatory policing be part of the larger discussion on addressing social inequalities in developed nations. In Germany, the lack of data disaggregated by race and ethnicity means that there are no figures on the extent of racially or ethnically based discrimination. Germany presents a unique case for examining the collection of disaggregated data due largely to the term race, or Rasse, having negative connotations due to the misuse of such data during the Nazi era.
This talk will focus on the potential ability of data disaggregated by race and ethnicity to reduce discriminatory policing in Germany, with a particular focus on ‘stop and search.’ Stop and search is a crime-prevention practice existing in both Germany and the UK which allows police officers to stop individuals they suspect of committing a crime, carrying a weapon, possessing stolen property, or carrying drugs. In Germany, federal police have the added power to stop a person suspected of committing an immigration violation.
In the UK – due to pressure from civil society organisations, academics, and government officials – data has been collected during police procedures, allowing for a monitoring and evaluation of discriminatory policing practices. Unfortunately, such an empirically driven policy approach is not currently possible in Germany. This talk will argue that, as a first step, a policy based off the UK approach towards data collection be implemented in Germany to incorporate, rather than ignore, Germany’s diverse identities, and to allow for empirically driven and more effective policing.
Presenters:
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Jeff Deutch
Jeff Deutch is an applied researcher with a community organising
background who has worked extensively on issues of data and discrimination.
Jeff Deutch is an applied researcher with a community organising background who has worked extensively on issues of data and discrimination. He has a BA in Critical Social Inquiry from Hampshire College in Amherst, Massachusetts, and a Masters in Public Policy from the Hertie School of Governance, Berlin, Germany. He has worked as a research consultant with Tactical Tech and is a co-founder of Artists Without A Cause.
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