AI-Driven Policing in Pakistan: Potential Pitfalls, and Privacy Concerns

Authors

  • Saeed Ahmed Soomro Post Graduate Scholar, Department of Criminology, University of Sindh, Jamshoro, Sindh, Pakistan
  • Hadi Bakhsh Kalhor PhD Scholar, Department of Criminology, University of Sindh, Jamshoro, Sindh, Pakistan
  • Mahwish Gujjar LLM Scholar, Institute of Law, University of Sindh, Jamshoro, Sindh, Pakistan

DOI:

https://doi.org/10.35484/pssr.2025(9-III)28

Keywords:

Artificial Intelligence (AI), Smart Policing, Predictive Policing, Privacy Rights, Algorithmic Bias, Data Protection, Law Enforcement, Digital Governance, AI Ethics

Abstract

This study aims to assess the perceived and actual benefits of AI-driven policing and to examine the legal, ethical, and operational challenges in Pakistan, focusing specifically on urban centers. AI technologies such as facial recognition, predictive analytics, and automated surveillance are being increasingly deployed in Pakistani law enforcement. However, this technological expansion has occurred in the absence of robust regulatory frameworks and public accountability mechanisms, raising concerns about civil liberties and democratic oversight. This is a qualitative secondary research study based on thematic analysis of academic literature, official reports, legal documents, and civil society publications. The findings indicate uneven implementation across cities, a lack of algorithmic transparency, and significant institutional capacity deficits. While AI offers improvements in surveillance and crime detection, its unregulated use poses risks to privacy and social equity. The study calls for a national legal framework, independent oversight bodies, and inclusive governance to ensure ethical and rights-based AI policing.

Downloads

Published

2025-07-30

Details

    Abstract Views: 527
    PDF Downloads: 473

How to Cite

Soomro, S. A., Kalhoro, H. B., & Gujjar, M. (2025). AI-Driven Policing in Pakistan: Potential Pitfalls, and Privacy Concerns. Pakistan Social Sciences Review, 9(3), 338–350. https://doi.org/10.35484/pssr.2025(9-III)28