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Algorithmic-driven Social (in)Injustice in Law Enforcement: A Critical Race Theory Perspective
Marco Marabelli, Joel Rivera Jimenez, Darakshan Nazir, Richa Shankar

Algorithmic decision-making systems (ADMS), especially when embedded in AI systems, have recently been the focus of social injustice research. In the US, law scholarship uses Critical Race Theory (CRT) to explain how and why social injustice still affects marginalized communities. For instance, algorithms perpetuate discrimination and can be supported by the juridical system and law enforcement because of systemic racism, which is embedded in historical racial discrimination. In this paper, after reviewing the extant literature on algorithmic discrimination associated with structural racism, we present vignettes of such types of discrimination (i.e., due to structural racism) in India, Italy, Pakistan, and the US. The vignettes focus on how law enforcement leverages algorithmic-based technologies to exercise power and maintain the status quo. We showcase that structural racism is inherently tied to institutional inertia and contribute to the interdisciplinary debate of the (mis) use of ADMS and the associated consequences for social justice.

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