Legal Gaps in India’s Unregulated AI surveillance

Use AI Surveillance in India

• In 2019, the Indian government announced plans to create the world’s largest facial recognition system for policing.
• AI-powered surveillance systems are in use at railway stations.
• The Delhi Police is preparing to use AI for crime patrols.
• Plans include launching 50 AI-powered satellites to enhance India’s surveillance infrastructure.

What are the issues associated with AI Surveillance In India?

• Privacy Infringement: AI surveillance systems can lead to dragnet surveillance, a term that refers to indiscriminate data collection beyond just suspects or criminals, infringing on citizens’ right to privacy (Article 21).
  • Example: Hyderabad police accessed the databases from social welfare schemes like “Samagra Vedika.”
• Lack of Proportional Safeguards: Existing safeguards are insufficient to prevent misuse of AI-driven surveillance.
  • The promised Digital India Act (for regulating AI) has yet to materialize.
• Exemptions in the Digital Personal Data Protection Act (DPDPA), 2023: Section 7(g) waives consent requirements for processing medical data during epidemics, while Section 7(i) exempts government from consent for employment-related data processing.
  • These exemptions raise concerns about misuse, especially regarding AI surveillance technologies that rely on vast amounts of personal data.
  • Citizens face increased scrutiny under DPDPA provisions like Section 15(c), which mandates that individuals must not suppress any material information when submitting personal data.
• Lack of Transparency and Accountability: Absence of publicly available guidelines on how data is collected, processed, stored, and protected by law enforcement agencies.
  • No independent oversight to prevent potential misuse of AI technologies.
• Risk of Discrimination and Bias: AI surveillance systems can perpetuate algorithmic biases and lead to unfair targeting of certain communities.
  • These biases can violate the principles of equality and non-discrimination.
• Data Security Concerns: High risk of data breaches and misuse due to inadequate cybersecurity infrastructure.
  • Example: The Telangana Police data breach exposed vulnerabilities in law enforcement data management.
• Civil Liberties Erosion: Unchecked surveillance threatens fundamental rights such as freedom of expression, association, and movement.
  • Excessive surveillance may create a chilling effect on democratic participation.

Proposed Reforms for AI Surveillance in India

• Comprehensive Regulatory Framework: Enact a robust legal framework to regulate AI-driven surveillance with clear guidelines on data collection, processing, storage, and deletion.
  • Ensure alignment with the principles of necessity, legitimacy, and proportionality.
• Transparency and Oversight Mechanisms: Mandate public disclosure of:
  • What data is being collected.
  • The purpose of collection.
  • Duration of data retention.
• Establish independent judicial oversight to review and approve surveillance activities.

• Strict Consent Requirements: Narrow and specific exemptions for consent under the DPDPA, ensuring they are not overly broad or ambiguous.
  • Implement transparent consent-gathering practices with proper safeguards.
• Risk-Based Regulation: Adopt a risk-based approach to categorize AI activities (similar to the EU model)
• Data Protection and Security: Strengthen cybersecurity infrastructure to prevent data breaches.
  • Introduce penalties for unauthorized access or misuse of personal data by law enforcement agencies.
• Algorithmic Fairness and Bias Mitigation: Conduct regular audits of AI systems to identify and mitigate biases.
  • Ensure AI algorithms used in surveillance are transparent and explainable.
• Judicial Oversight and Redressal Mechanisms: Implement judicial review for AI surveillance operations.
  • Create mechanisms for citizens to challenge surveillance practices and seek redressal for violations.

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