Impact of facial recognition technology on crime prevention

Abstract

Introduction: Facial recognition is an artificial intelligence technology that allows automated identification of individuals from images or videos of their faces. Its use by police and security agencies to prevent crime has rapidly increased in recent years. However, this application raises significant ethical concerns related to privacy, protection of personal data, freedom of thought, presumption of innocence, and nondiscrimination. Objective: To evaluate the effectiveness and ethical implications of implementing facial recognition technologies in urban environments for crime prevention, providing evidence-based recommendations for responsible application. Methodology: A qualitative systematic review of scientific literature published between 2017 and 2022 on the use of facial recognition in crime prevention was conducted. Sixteen articles meeting predefined eligibility criteria were analyzed, sourced from academic journals in artificial intelligence, law, criminology, and ethics. Results: Reviewed studies suggest that facial recognition is increasingly adopted by security forces in public spaces. While algorithms have achieved high levels of accuracy, evidence of their effectiveness in reducing crime is still limited and mixed. At the same time, significant ethical risks arise, including potential violations of fundamental rights, algorithmic biases, mass surveillance, and erosion of civil liberties. Experts advocate for strict regulations, impact assessments, independent oversight, and public debate to prevent abuses. Conclusion: Facial recognition represents a promising yet controversial tool for crime prevention. Its actual effectiveness remains uncertain, and its ethical risks are significant. A precautionary approach with robust legal and technical safeguards, constant monitoring, and broad social deliberation is required to balance security and freedom. Only responsible and accountable governance will allow harnessing its benefits while respecting human rights. General Study Area: Artificial Intelligence. Specific Study Area: Technology and Crime Prevention. Study Type: Qualitative Systematic Review.