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The research led by Kanika examines the growing use of algorithmic surveillance technologies among law enforcement agencies to try to predict areas and individuals with a higher propensity of crime. Although hailed by some police services as an efficient mechanism to aid in their decisions to deploy resources, critics argue that the data used to predict crime can be flawed and racially biased. As an increasing number of civil liberties associations, researchers and community members call for the government to implement policies that counteract systemic racism in policing, there are many calls to regulate predictive policing technologies given their potential risk of exacerbating observed racial biases in law enforcement practices.
The research project will document and analyse how policing agencies approach the decision to use predictive analytics in light of stated concerns. Through a comparative analysis of jurisdictions in Australia and Canada, the study explores the following questions:
- In what ways do predictive policing technologies affect how police engage in crime control?
- Has the implementation of predictive policing technologies affected police stop and search procedures, particularly in predominately Black, Indigenous, and immigrant communities?
- How do communities that experience forms of marginalisation perceive the use of predictive policing technologies?
The study will bring together insights from nodal governance and critical race theory to capture the dynamic nature of contemporary policing alongside enduring concerns of inequitable law enforcement practices.
The SSHRC is the Canadian federal research funding agency that promotes and supports research and research training in the humanities and social sciences.