SAS consultant recommends analytics uses to police

SAS UK Consultant, Police & Intelligence Services Andy Davies has explained how police can depart from “black box” solutions using analytics.

Davies, who has a history of working in the police force before joining the analytics firm, has recommended a number of ways in which the police force can expand their use of data analytics in order to improve crime-fighting and antisocial behaviour prevention methods.

“The world of policing is continually changing as budgets are cut and the nature of crime and civil unrest changes,” he said. “To enable forces to respond to the ever-changing demand placed on them, they need to take a holistic approach to the role of analytics and how it can assist them.

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“This means moving away from the single purpose “black box” predictive policing solutions.”

Innovating using data analytics

The consultant recommended the following methods of data analytics uses that can be applied to police solutions:

• Demand profiling – predicting when/where and with what frequency crime and incidents will occur.
• Resource management – understanding what resources are available and if they are suitable to meet demand.
• Facial recognition – to identify known persons from captured images from CCTV, social media etc
• Body worn video analysis – automated-at-the-scene analysis of video material to support officers involved in violent offences and gang control
• Gang analysis – using network analysis to understand crime syndicates
• Social media analysis – using social media to track stolen goods and develop a better understanding of criminals
• Text and sentiment analytics – to automate intelligence gathering from free text intelligence records or automatically extract key information from telephone calls when used alongside voice-to-text functionality
• Criminal pathway analysis – to understand which people are at risk of entering organised crime
• Automated briefing tools – to provide up-to-date information from a wide range of police data to officers quickly and efficiently.

“None of these techniques or processes are new or revolutionary ideas,” Davies added, “but it’s my view that police forces need to change their approach to using these types of analytical functionalities.

“Forces need to use in-house data scientists who can use emerging technologies and adapt them to the policing environment.

“By using in-house skills forces can tap into the huge amount of experience and knowledge that already exists and use analytics to augment this.”

>See also: In-house vs. outsourced IT: what makes the most business sense?

Facial Recognition

One of many recommended technologies by the SAS consultant, facial recognition, at least within the police force, seems to be far from the finished article yet.

recent report has found that automated facial recognition used by the UK police to identify criminals failed to pick out correct suspects 98% of the time.

Surveillance Camera Commissioner, Tony Porter, responded to the report by insisting that automated facial recognition technology still had potential and that is still being developed.

>See also: Authentication vs identification: Understanding the tech behind face ID

SAS consultant Davies insists, however, that no matter how much analytical and AI technology develops, it will never play as important a role as the experience that human intervention brings.

“Officers and staff will remain the most important tool in policing and the wealth and experience they have built up can never be replaced,” he stated.

“But analytics can help them do their jobs better, so we need to find new and innovative ways to make analytics and resulting insights accessible to them.”

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Aaron Hurst

Aaron Hurst is Information Age's senior reporter, providing news and features around the hottest trends across the tech industry.