Biometric Facial Recognition Technology, Law Enforcement Algorithmic Automation, and Data-driven Predictive Policing Systems in Human Rights Protections and Abuses
Biometric Facial Recognition Technology, Law Enforcement Algorithmic Automation, and Data-driven Predictive Policing Systems in Human Rights Protections and Abuses

Summary/Abstract: The aim of this systematic review is to synthesize and analyze facial recognition systems and predictive policing algorithms. With increasing evidence of biometric data processing, digital police surveillance technologies, and automated decision-making systems, there is an essential demand for comprehending whether police surveillance technologies and subjectivities enact regulatory governance. In this research, prior findings were cumulated indicating that digital police surveillance technologies and practices are pivotal in regulatory governance and environments. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout May 2022, with search terms including “human rights pro- tections and abuses” + “biometric facial recognition technology,” “law enforcement algorithmic automation,” and “data-driven predictive policing systems.” As I analyzed research published in 2022, only 142 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, I decided on 25, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

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