ARCHIVES
VOL. 11, ISSUE 2 (2025)
AI for preventing & reducing traditional crimes
Authors
Dr. Ujwala Bendale, Dr. Anuradha Girme, Utpal Gharde
Abstract
As law enforcement agencies increasingly turn
to Artificial Intelligence (AI) for preventing traditional crimes, it is
crucial to understand the associated risks and identify strategies to mitigate
them. This article gives an overview of the various applications of AI in
prevention of traditional crimes, such as predictive analytics, video
surveillance, and pattern recognition. It, then, examines the potential risks
inherent in the use of AI, including biases in data and algorithms, threats to
privacy, and unintended consequences for marginalized communities. Drawing from
scholarly literature and real-world examples, the article offers a
comprehensive analysis of these risks and proposes mitigation strategies. These
strategies encompass measures to enhance transparency, accountability, and fairness
in AI systems, as well as mechanisms for community engagement. By highlighting
the risks associated with AI in preventing traditional crimes and providing
actionable mitigation strategies, this article aims to support informed
decision-making and responsible deployment of AI technologies in law
enforcement.
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Pages:20-24
How to cite this article:
Dr. Ujwala Bendale, Dr. Anuradha Girme, Utpal Gharde "AI for preventing & reducing traditional crimes". International Journal of Law, Vol 11, Issue 2, 2025, Pages 20-24
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