Mains Practice Questions

Case Study

As the Deputy Commissioner of Police (DCP) in a metropolitan city, you oversee the implementation of an AI-based Facial Recognition System (FRS) designed to track criminals and prevent crimes. The system, installed across public spaces, has been instrumental in reducing theft, identifying suspects, and solving pending cases. However, concerns have emerged regarding false positives, privacy violations, and potential biases in the AI’s algorithm.

Recently, the system flagged Ravi, a 22-year-old college student, for allegedly being present at a protest that turned violent. Based on the AI-generated report, Ravi was briefly detained for questioning, despite his insistence that he was not involved. His family and civil society groups argue that he was misidentified due to a technical error in the AI system. Investigations reveal that multiple individuals from marginalized backgrounds have been disproportionately flagged, raising concerns about bias in AI-driven policing.

The city’s administration is now divided. Some officials advocate for pausing the AI project for an independent review, citing privacy concerns and wrongful detentions. Others argue that the benefits outweigh the risks and that AI errors can be rectified over time. Meanwhile, public outrage over Ravi’s case is growing, and the police department's credibility is at stake.

Questions:

A. How can law enforcement balance the benefits of AI-driven facial recognition with concerns over false positives, privacy violations, and algorithmic bias?

B. What ethical principles should guide law enforcement in deploying AI tools, particularly in ensuring non-discrimination and protecting marginalized communities?

C. What legal, procedural, and technological safeguards should be implemented to ensure AI-driven policing remains transparent, fair, and accountable?