Deputy Chief Peter Sloly believes the Toronto Police Service could reduce it’s force by ‘several hundred’ officers if it leverages technologies associated with ‘Big Data’ (CBC 2016). Sloly claims big changes are needed to restore trust in policing he feels is at a low point not just in Toronto, but also, across North America (Powell 2016). Investigations into the killing of Laquann McDonald by a Chicago police officer and Sammy Yatim by a Toronto police officer have damaged public perception and generated traction for calls for reform. In both cases, human resources management and new information communication technologies have been presented as solutions to the challenges of contemporary policing.
Many technology firms are making claims that advancements in data analytics can shift police forces from a reactive model to a predictive one. Through Big Data, the City of Chicago has produced a list of individuals that algorithms have categorized as high risk for committing serious crime. The Chicago Police Department (CPD) then contacted the individuals with information about the consequences of the criminal acts they were deemed likely to commit in an effort to change their ‘future’. At the IBM Smarter Cities conference in Las Vegas last year it was announced that Watson analytics would mine data provided by Twitter in an attempt to predict crime hot spots.
Chicago, like Toronto, has a body worn camera pilot underway. Manuel launched the body worn camera pilot not long after the death of Laquan McDonald, claiming that the new technology would help restore faith and trust in the police force. Interestingly, the ‘in car camera’, an earlier form of mobile surveillance, was introduced twenty years prior in the State of Illinois with the same objective: restore the loss of faith and trust in local law enforcement. In some ways, these mobile cctv solutions are closer to the reactive policing model cited by Sloly. Although footage of interactions between officers and citizens has proven useful in both the McDonald and Yatim cases, the video is a record of reactive policing in action.
Days after video of a Chicago Police Officer shooting Laquan McDonald sixteen times was released, Chicago Mayor Rahm Emanuel fired superintendent Garry F. McCarthy (Davey 2015). The footage was suppressed for a year after McDonald’s death, which, in conjunction with reports of officers deleting private CCTV footage at a nearby Burger King and threatening witnesses to make them file false accounts, fuelled outrage and protests in the city. In Toronto, just days after a verdict in the Sammy Yatim case was released, Mayor John Tory made a public appearance at the Toronto Police College. Tory observed training that focuses on dealing with people in crisis situations similar to Yatim’s case. Although the mayor was impressed he stated that more needed to be done to improve policing.
Like Tory, Sloly believes there is work to be done in the Toronto Police Force to foster new cultural norms. Sloly claims the practice of carding is reflective of a global crisis in policing. Research has repeatedly shown carding perpetuates systemic racial bias and is a result of inadequate training and supervision (Floyd v. State of New York; R. v. Fountain; Ontario Human Rights Commission 2003; Wortley and Owusu-Bempah 2011). In other words, officers were able to systematically target individuals for criminal investigation based on skin colour.
According to many creators of smart technologies, algorithms are not susceptible to bias (Kitchin 2014). Following this logic, a Big Data approach to policing could offer much to Toronto Police Services. However, scholars have contested the claims that algorithms ‘tell it like it is’ and encourage researchers to challenge claims of objectivity (van Dijck 2014). Transparency in the collection, sharing and analysis of data is an important safeguard against the potential failures of Big Data (Couldry and Powell 2014). These failures are already apparent in smart policing projects in the United States (Ferguson 2015). Thus, inadequate training and supervision of Big Data policing could reproduce the issues that have persisted with carding historically. Unfortunately, discussions about the potential for Big Data to erode democratic freedoms through the intensification of surveillance remain marginalized (Lyon 2014). Deputy Sloly, and those in the Toronto Police Service that favour his position, would do well to encourage researchers to join the table as the seemingly inevitable move to Big Data and smart policing occurs.
CBC. (27012016). Police “trying to dissolve the uniform,” Tory says of crisis training. Retrieved February 3, 2016, from http://www.cbc.ca/news/canada/toronto/john-tory-police-college-1.3422033
Couldry, N., & Powell, A. (2014). Big Data from the bottom up. Big Data & Society, 1(2), 2053951714539277. http://doi.org/10.1177/2053951714539277
Davey, M. (2015, December 1). Chicago police superintendent fired in response to shocking video of black teen being shot 16 times. Retrieved from http://news.nationalpost.com/news/chicago-police-superintendent-fired-in-response-to-shocking-video-of-black-teen-being-shot-16-times
Ferguson, A. G. (2015). Big Data and Predictive Reasonable Suspicion. University of Pennsylvania Law Review, 163(2), 327–410.
Floyd v. State of New York. 82 Fed. R. Serv. 3d (West) 833 (S.D.N.Y. 2012).
Lyon, D. (2014). Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big Data & Society, 1(2). http://doi.org/10.1177/2053951714541861
Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 2053951714528481. http://doi.org/10.1177/2053951714528481
Ontario Human Rights Commission. 2003. “Paying the Price: The Human Cost of Racial
Powell, B. (2016, January 18). Passed over for the top job with Toronto police, Sloly says harnessing technology could allow the service to drop “several hundred police officers.” The Toronto Star. Retrieved from http://www.thestar.com/news/gta/2016/01/18/deputy-chief-peter-sloly-pushes-for-change-amid-low-point-and-looming-crisis.html
R. v. Fountain, 2013 ONCJ 434
van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208.
Wortley, S. and Owusu-Bempah, A. 2011. “The usual suspects: police stop and search practices in
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