A predictive State? Sri Lankan context of predictive policing

Despite being slow in digital adaption, SLP has recognised that data analytics is a vital part of modern policing, and to assist in that CRD has setup local infrastructure, as well as a web server hosted in a managed data centre to host raw criminal data stats for analytics. Right now, it may be in its infancy, but many law enforcement agencies globally are pivoting towards predictive policing – Pic by Shehan Gunasekara

The Sri Lankan State sector has shown a gradual warming up to digitalisation and digital transformation. 

Taking a lead from President Gotabaya Rajapaksa’s Digital Sri Lanka initiatives, there are ambitious plans to give the Sri Lankan State sector a much-needed digital makeover. However, there is one area of the State that has been sluggish to implement digital transformations, it is perhaps the most vital State institution, as it deals with the critical function of maintenance of law and order. If you haven’t guessed already, it’s the Sri Lanka Police. 

The digitalisation of Sri Lanka Police (SLP) has been a slow journey. SLP has 496 police stations; out of which 492 are on a VPN network (four Police stations are unable to be connected to VPN due to technical issues with broadband connectivity). 

SLP digital use cases are limited in application: they only use their email system to share Daily Police messages (bulletins, notices by IGP or senior officers, etc.) but due to COVID situation the email system has now been expended to be used for divisional communications. 

There is an Admin/HR system that contains details of all 88,000 police officers, which includes their personnel records, leave information, etc. and finally individual police stations’ criminal data and traffic offence data is manually entered via web forms and updated to Police CRD (Criminal Records Division) for trend analysis.  

Aha! Trend analysis! Despite being slow in digital adaption, SLP has recognised that data analytics is a vital part of modern policing, and to assist in that CRD has setup local infrastructure, as well as a web server hosted in a managed data centre to host raw criminal data stats for analytics. Right now, it may be in its infancy, but many law enforcement agencies globally are pivoting towards predictive policing. 

Predictive policing? 

Predictive policing uses computer systems to analyse large data sets, including historical and present crime data, to help decide where to deploy police or to identify individuals who are purportedly more likely to commit or be a victim of a crime. 

Place-based predictive policing, the most widely practiced method, typically uses preexisting crime data to identify places and times that have a high risk of crime (E.g., hypothetically, Kotahena at 6 p.m.).

Person-based predictive policing, on the other hand, attempts to identify persons or groups who are likely to commit a crime — or to be victim of one — by analysing for risk factors such as past arrests or victimisation patterns.

Good idea or bad idea? 

Advocates argue that algorithms can predict future crimes more accurately and objectively than human police officers relying on their instincts alone. Also, predictive policing can provide significant cost savings for police departments by improving the efficiency of resource deployment to their crime-reduction efforts.

Opponents warn about a lack of transparency from law enforcement agencies that administer predictive policing programs. They also point to a number of civil rights and civil liberties concerns, including the instances that algorithms could reinforce racial biases in the criminal justice system. These concerns, combined with independent audits, have led some police departments in the United States, including in Los Angeles and Chicago, to phase out or significantly reduce the use of their predictive policing programs after auditing them.

Notable examples of predictive policing projects

One of the earliest adopters of predictive policing was the Los Angeles Police Department (LAPD). They began working with federal agencies in 2008 to study different prediction algorithm approaches. Since then, the LAPD has implemented a variety of predictive policing programs (https://www.wired.com/story/los-angeles-police-department-predictive-policing/), including LASER, which identifies areas where gun violence is thought likely to occur, and PredPol, which calculates “hot spots” with a high likelihood of property-related crimes: 

“..about past offenders over a two-year period, using technology developed by the shadowy data analysis firm Palantir, and scores individuals based on their rap sheets. If you’ve ever been in a gang, that’s five points. If you’re on parole or probation? Another five. Every time you’re stopped by police, every time they come knocking on your door, that could land you more points. The higher the points, the more likely you are to end up on something called the Chronic Offender Bulletin, a list of people the data says are most at risk of reoffending and ought to be kept on close watch…” [https://www.wired.com/story/los-angeles-police-department-predictive-policing/]

The New York Police Department (NYPD) created predictive algorithms for several crime categories, including shootings, burglaries, assaults, breaking and entering, motor vehicles thefts, and armed robberies. Those algorithms are used to help assign officers to monitor specific areas. (https://www.thedailybeast.com/red-flags-as-new-documents-point-to-blind-spots-of-nypd-predictive-policing)

The predictive case for Sri Lanka 

One could argue that this tech seems a bit far off as a use case in Sri Lanka, nonetheless the building blocks are in place. The CRD already has database in digital format hosted in the data centre, as well as the Police CCTV division (https://www.police.lk/index.php/item/16-cctv-division) which has been in operation since 2010 (incidentally this unit was created in 2010 as brainchild of current President Gotabaya Rajapaksa). In August 2019 it was decided to upgrade the police CCTV system with advanced optics which would allow Police to identify the vehicle’s number plate clearly and get a clear view of the driver’s face. (i.e., enabling facial recognition) (https://www.news.lk/news/political-current-affairs/item/26909-police-cctv-system-to-get-upgraded)

The Police with the assistance of the military’s Drone regiment

(https://www.newsfirst.lk/2020/11/12/15th-drone-regiment-of-sri-lanka-artillery-inaugurated/) has already started using advanced drones equipped with Zenmuse H20 optics with thermal and night vision capabilities with to enforce COVID-19 lockdown in isolated areas (https://www.newsfirst.lk/2020/11/12/police-to-use-drones-to-monitor-lock-down-areas/) 

The missing piece of this predictive policing puzzle is the facial recognition tech which can’t be deemed as inaccessible, as evident by Russian Apps like FindFace: A NtechLab App Launched in the mid-2010s, where the app allowed users to take a picture of someone and match their face to their social media profiles on Russian site Vkontakte (VK). Although NtechLab since shut down the consumer app, the company pivoted its tech to the lucrative surveillance market. In January 2020 the company disclosed that it’s being paid at least $3.2 million for deploying its tools across the Russian capital. NtechLab CEO Alex Minin claimed, in an interview with Forbes, that it’s the biggest “live” facial recognition project in the world. (https://www.forbes.com/sites/thomasbrewster/2020/01/29/findface-rolls-out-huge-facial-recognition-surveillance-in-moscow-russia/?sh=33919e08463b)   

Comedian John Oliver in an episode of ‘Last Week Tonight’ on Facial Recognition (https://www.youtube.com/watch?v=jZjmlJPJgug&ab_channel=LastWeekTonight) painted a target on another tech company ClearView AI (https://clearview.ai/) which was offering law enforcement agencies face recognition tech by mining online user data to build a vast facial recognition database. (https://youtu.be/cc0dqW2HCRc) Although under a slew of lawsuits, the company has shifted to COVID- 19 related contract tracing efforts using its platforms in order to gain legitimacy. (https://www.vox.com/recode/2020/2/11/21131991/clearview-ai-facial-recognition-database-law-enforcement)

Finally.

Thus, the implementation plan is clear, scale up SLP Data analytics unit (CRD), upgrade the CCTV division with latest facial recognition tech, tap into the presumptive eNIC (https://www.readme.lk/enic-sri-lanka/) Project for location/demographic related data, and the recipe is ready for a Sri Lankan predictive policing program. 

So, what does this mean to regular Citizen Perera? Is it Orwellian? Perhaps. Would it be effective? Overwhelmingly. Is there a chance of abuse? Yes, without the necessary legal provisions, regulatory oversight and privacy councils it would be. But... if used well and true to its purpose, it would transform the Sri Lankan law enforcement to an agile, digital first, effective, efficient entity. But then, for whom will its bells toll?   

(The writer has been a prominent personality in the sphere of cyber-security, with over a decade of experience in progressive technology and digital strategy. Garnering extensive qualifications in both the legal and technical arenas, Asela is a pioneer trailblazer and avant-garde in the information security marketplace.)