60 GovernanceNow | March 16-31, 2015

people politics policy performancePublic Safety

Hong-Eng Koh

Social-enabled policing is a con-cept which police and law en-forcement agencies should adopt in this age of social net-

working and crowdsourcing. In 20th century, community policing seemed to give way to problem-oriented polic-ing, with a focus on effective methods to solve problems of crime and disor-der, including methodology, tools and data; but not on community relation-ship, let alone on prevention. In the early 21st century, problem-oriented policing evolved into intelligence-led policing. The focus was on integrated crime and criminal analysis, profiling of serious offenders, supported by an informed police command structure.

With the advancement of analytical tools, intelligence-led policing soon led to today’s predictive policing (PredPol). This allows police to mobilise and de-ploy necessary resources to mitigate threats. PredPol relies on past crime and criminal data, and thus assumes that the cause and reason of crime and disorder do not change. Does this re-ally prevent a crime and disorder or merely suppress its symptom?

Individuals, organised criminals and even terrorists are ‘crime-sourc-ing’ to help each other, though they may not know each other. Likewise, the social community is contributing to big data by sharing information and media that are of high value to police.

The right mixData analysis is not new. It has been

used widely in intelligence-led polic-ing – to identify a suspect for example – and for predictive policing that is aimed to prevent a crime through pro-active patrolling. We understand that the difference between success and failure in predictive policing lies in the relevant data model. Predictive polic-ing mainly relies on historical data and crime pattern, and knowledge from experienced police and intelligence of-ficers. It is clear that traditional data analysis based on past incidents, crime records, intelligence, call detail re-cords, video surveillance and automat-

ic number plate recognition (ANPR) are not sufficient. It’s about fusion of variety of data: traditional, social and open-source intelligence (OSINT), usu-ally at high velocity with high volume.

Organisations need to evolve their data management architecture into a big data management system that en-ables seamless integration of all types of data from a variety of sources, in-cluding Hadoop, relational and NoSQL. While simplifying access to all data, a big data management system can also enable organisations to leverage ex-isting skills and maintain enterprise-grade data security and governance for sensitive or regulated information.

Police and the government have to protect the privacy of their constitu-ents. For example, the UK has a Na-tional ANPR Data Centre. Law enforce-ment and intelligence agencies follow strict guidelines on the use of such data. It is important to point out that

a cornerstone of social-enabled polic-ing is its ability to analyse public senti-ments through such OSINT.

Social-enabled policing supports prevention, detection and solving of crime and disorder. It is about com-munity policing, intelligence-led polic-ing and predictive policing. It is made possible through social networking and crowdsourcing, and the effects brought about by them, complementing tradi-tional policing. Mere engagement of the community through physical police presence is insufficient, we need a ho-listic social strategy and social presence to listen, analyse, understand, engage and communicate with the community.

Social-enabled policing is not just about adoption of social network-ing technologies and collecting open source intelligence. It is still about traditional community policing, intel-ligence-led policing and predictive po-licing, complemented by social media and social networking. It allows the

social-savvy generation to report in-cidents and be engaged 24x7 through multiple channels. It is also about re-moval of barriers and stovepipes, facil-itating a 360-degree view of the victim, witness, suspect and incident.

Criminals and terrorists adopt tech-nologies at a faster rate than govern-ment agencies. Technologies are both tools and threats to police. The younger generation is dependent on technolo-gies, social networking, big data, cloud, mobility and even Internet of Things. Police and law enforcement agencies have to stay ahead of this curve.

Also, one should remember that good old policing and detective skills are still essential; technologies are only tools to mitigate this world of big data.n

Koh is the global lead for justice and pub-lic safety with Oracle Corporation and VP (corporate) of the Society for Policing of Cyberspace (POLCYB).

Gov NEXT A Click Into Digital Governance

Effective policing through social mediaAdopting next-generation technologies for better policing

Social-enabled policing is about removal of barriers and stovepipes, facilitating a 360-degree view of the victim, witness, suspect and incident.