Jonida Milaj and Gerard Jan Ritsema van Eck ‘Capturing licence plates: police-citizen interaction apps from an EU data protection perspective’ (2019) International Review of Law, Computers & Technology, doi: 10.1080/13600869.2019.1600335
A Pokémon Go-like smartphone app called ‘Automon’ was unveiled in October 2017 as one of several new initiatives to increase the public’s contribution and engagement in police investigations in the Netherlands. Automon is designed in the form of a game that instigates participants to photograph license plates to find out if a vehicle is stolen. The participants in the game score points for each license plate photographed, and may also qualify for a financial reward if a vehicle is actually stolen. In addition, when someone reports that a vehicle has been recently stolen, game participants that are in the vicinity receive a push notification and are tasked with searching for that particular vehicle and license plate. This paper studies the example of the Automon app and contributes to the existing debate on crowdsourced surveillance and the involvement of individuals in law enforcement activities from an EU law perspective. It analyses the lawfulness of initiatives that proactively require individuals to be involved in law enforcement activities and confronts them for the first time with European Union (EU) data protection standards. It is concluded that the Automon app design does not meet the new legal standards.
Available open access here.
Gerard Jan Ritsema van Eck, ‘Emergency Calls with a Photo Attached: The Effects of Urging Citizens to Use Their Smartphones for Surveillance’ in Bruce Clayton Newell, Tjerk Timan and Bert-Jaap Koops (eds), Surveillance, Privacy, and Public Space (Routledge 2018).
Various kinds of media and metadata, such as pictures, videos, and geo-location, can be attached to emergency reports to the police using dedicated platforms, social networking sites, or general communication apps such as WhatsApp. Although potentially a very useful source of information for law enforcement agencies, this also raises considerable concerns regarding surveillance and privacy in public spaces: It exhorts citizens to establish a supervisory gaze over anyone, at any time, and anywhere.
This chapter analyses these concerns using theories from surveillance studies. It considers the (surprisingly high) applicability of panoptical theories by Foucault and others to the effects of increased visibility of citizens in public spaces. This analysis importantly reveals how discriminatory tendencies might be introduced and exacerbated. Attention is then paid to Deleuze’s ‘societies of control’ and related notions such as database surveillance, surveillance assemblages, and predictive policing. This analysis shows that the enrichment of emergency reports with media and metadata from smartphones can pressurize people into conformity, erode the presumption of innocence, and diminish societal trust. Furthermore, this process will disproportionality affect already disadvantaged groups and individuals. Policy makers are advised to implement enriched emergency reports carefully.
Get the hardcopy book at Routledge, get access to the digital edition, or ask your favourite librarian and/or local bookshop. Alternatively, download the accepted manuscript here.
Oskar Josef Gstrein and Gerard Ritsema van Eck ‘Mobile devices as stigmatizing security sensors: The GDPR and a future of crowd-sourced ‘broken windows” (2018) 8(1) International Data Privacy Law 69-85, doi: 10.1093/idpl/ipx024.
Various smartphone apps and services are available which encourage users to report where and when they feel they are in an unsafe or threatening environment. This user generated content may be used to build datasets, which can show areas that are considered ‘bad,’ and to map out ‘safe’ routes through such neighbourhoods. Despite certain advantages, this data inherently carries the danger that streets or neighbourhoods become stigmatized and already existing prejudices might be reinforced. Such stigmas might also result in negative consequences for property values and businesses, causing irreversible damage to certain parts of a municipality. Overcoming such an “evidence-based stigma” — even if based on biased, unreviewed, outdated, or inaccurate data — becomes nearly impossible and raises the question how such data should be managed.
Published version freely available at Oxford Academic.
Accepted manuscript (‘post-print’) freely available here.