Q. Ravi is a senior police officer with vast experience in riot control and cyber-policing. Since one year, he has been the Superintendent of Police (SP) of a district with a history of frequent rioting.
Last year, Ravi had sought installation of an AI enabled software for predictive policing. This system has been operational for approximately six months. This new system employs advanced algorithms for capturing the biometric data of persons in a crowd and swiftly relating it to a data library. This has enabled the police to identify the persons involved in various crimes.
The system has identified an immigrant and low-income neighbourhood as a centre for gang violence and drug trafficking. Aided by this AI analysis, the local police has focused its patrolling, preventive detentions and establishing checkpoints. Consequently, public order and law enforcement has visibly improved.
Last week, some community leaders, civil rights lawyers and human rights activists visited Ravi’s office. They submitted a memorandum that the new system is faulty as it is based on incorrect historical data caused by social biases and discriminatory policing. The memorandum also alleges that the increased surveillance has created a climate of tension amongst residents. This feeling is aggravated by the fact that the residents are not aware of the data noted against their names.
(a) What are the ethical issues including biases involved in the use of AI in data-driven policing?
(b) Place yourself in Ravi’s role and discuss the alternatives available. Justify the action that optimises compliance with ethics.
Question from UPSC Mains 2026 GS4 Paper
Model Answer:
The dilemma pits technological efficiency in crime control against algorithmic discrimination, civil liberties (Art. 14, 21), and the erosion of police-community trust.
1. Ethical Issues & Biases in AI-Driven Policing
- Reinforcement of Historical Bias: AI models trained on skewed arrest records institutionalize systemic discrimination against marginalized groups (e.g., US COMPAS bias).
- Feedback Loop of Over-Policing: Disproportionate patrol allocation in target zones creates higher arrests, artificially validating flawed algorithmic predictions.
- Infringement of Privacy & Due Process: Mass biometric harvesting without informed consent breaches procedural fairness and data privacy (K.S. Puttaswamy; DPDP Act, 2023).
- “Black-Box” Opacity & Non-Accountability: Lack of algorithmic explainability prevents citizens from knowing, verifying, or challenging criminal tagging against their names.
- Chilling Effect & Collective Criminalization: Pervasive surveillance breeds psychological fear, stigmatizes entire neighbourhoods, and damages community-police relations.
2. Evaluation of Alternatives & Justified Action Plan
| Alternative | Merits | Demerits |
|---|---|---|
| 1. Unchanged AI Deployment | Maintains deterrence and low crime rates. | Deepens alienation; risks legal challenge under Art. 14 & 21. |
| 2. Complete Scrapping of AI | Restores community trust; eliminates algorithmic bias. | Sacrifices technological efficiency in riot-prone terrain. |
| 3. Calibrated Ethical Governance | Balances public order with constitutional morality. | Requires administrative restructuring and resources. |
Justified Course of Action (Alternative 3)
- Third-Party Algorithmic Audit: Temporarily halt automated predictive profiling to audit training datasets for socio-economic biases with independent technical experts.
- “Human-in-the-Loop” Protocol: Mandate that AI outputs serve only as secondary advisory inputs; prohibit automatic preventive detentions without independent evidentiary corroboration.
- Data Transparency & Redressal: Establish a standard operating procedure for data transparency, allowing citizens to contest incorrect records (Principles of Natural Justice).
- Community-Centric Policing: Re-channel police presence from hostile checkpoints to participatory community outreach (e.g., Janamaithri model) to heal civic trust.
Ethical policing demands that technological tools align with constitutional morality, ensuring crime prevention does not compromise human dignity, equity, and the rule of law.
