Achieving stronger community policing through the technology and social science interface

 

Design a technology such as INSPEC2T lead to analyse how to conceptualise complex ICT-enabled tools and systems into policing, police work.

Police work can be aligned to the logic of technology developers. Police work is mapped onto a model of information processing, where officers are represented as units, feeding information into the system, or retrieving information, where information is distributed and algorithmic computations are performed on data stored in the system. In the case of INSPEC2T solution which aims to strengthen community policing, citizens are integrated into the system as well.

However, apart from the technical challenges there are other problems to be addressed. Looking at specific real-life scenarios, we may argue that a strict technology focus need to be matched with a social-science focus, opening room for basic research about the interface between these different approaches and for an increased understanding of security as a societal challenge in general.

Taking a closer look at one of the scenarios used by the technology partners in the INSPEC2T project, the nature of these problems can be demonstrated.

 

A-thief-takes-a-bike-scenario

The scenario presented the case of a thief who takes a bike. A kid’s bike no longer is at the location where it was left, when entering a playground. Upon the kid’s return, accompanied by an adult guardian, the bike has disappeared. This constellation now is taken as the input for the demonstration of the supportive software tools designed to improve community policing. The point though is, that it is interpreted in a specific – crime-centred – way: It is assumed that a thief has taken the bike. Operating on this assumption a number of actions are triggered, putting the ICT-enabled communication and information infrastructure to use. The presumed “victim” informs the police, using an INSPEC2T citizen app, forwarding a picture of the “stolen object” stored on her files with photo images. The citizen app entails functionalities to transmit pictures and visual material. The police call-centre, receiving the report from the “victim” after consulting with the community police officer working in the area, shares the information with other members of the community, i.e. lay citizens who downloaded the app and asks for their support: has anyone seen the bike or the bike thief? Feedback is pouring in from citizens and police staff is guided to the area where the thief and the stolen object had been spotted. The story, as designed in the hypothetical scenario culminates in the arrest of the wrong-doer and a happy kid, reunited with its beloved bicycle – all this facilitated by the INSPEC2T ICT-enabled infrastructure of communication and information processing.

Stepping back for a moment and considering the alternatives left out in this A-thief-takes-a-bike-scenario (hereafter referred to as ATTABS) a number of different stories could be developed using the simple description of physical facts provided.

Every competent police practitioner, confronted with ATTABS would most probably search for stories that do not involve a criminal act. Was the bike really left at this location? Could it be that a sibling, friend or acquaintance has taken the bike? Could it be that someone used it for a joyride and then left the bike sitting somewhere in the close neighbourhood? Before having checked the plausibility of these alternative courses of events, no police officer would activate a collective search via citizen app, as suggested in the original interpretation of ATTABS.

Assuming that enough citizens in a community would be willing to join the programme, download the app and actively participate in such collective thief-taking endeavours, the odds of getting the wrong person are still relatively high.

Any person with a kid’s bike may be reported to the police (could happen to fathers, elder siblings, facility managers in schools, etc.). Even when a photo of the missing bike is provided via app, vigilant citizens may report all sorts of unaccompanied bikes to the police. The effect may be an information overload making it difficult for police to select the right leads, although it remains an open question whether a stolen bike creates enough arousal among citizens to begin actively and in great numbers to flood the police with their observations.

Replace the stolen bike with a kidnapper of a child, the dynamic most probably would be different, creating problems of self-reinforcing boot-strapped witch hunts.

 

The technology/social science interface

What often is overlooked when addressing a general public in matters relating to crime, law and order is the subtle but extremely important difference between the status of suspect and (convicted) criminal.

The logic of machine-based algorithmic problem solving, and the logic of hermeneutic understanding of practical human action – are bound together with the machine-based logic taking the lead but represent two epistemologies that are hard to reconcile.

The great advantage of a technology-driven approach is the focus on explicit, and clear rules and processes. When parsing the work of a community police officer into its constituent elements it is hard to identify slots for such expert systems.

Understanding how police officers and citizens engage in mutual reality work in a specific setting, negotiating a shared answer to the question “What happened and what has to be done?” may improve the understanding of police work as situated social practice, but can hardly inform the design of an algorithmic solution, helping police officers to handle everyday encounters.

Acknowledging this predicament, one might start to think about a shift of emphasis in mission-oriented security research from a strict technology focus to a more social-science focus and give room to basic research about the complex interface between these different approaches.

 
Norbert LeonhardmairComment