The Algorithmic Victim: Facial Recognition Technology, False Positives, And The Absence Of A Victim-Centered Legal Framework In India
- IJLLR Journal
- 2 hours ago
- 1 min read
Vanshaj Sharma, The National Law University of Meghalaya
ABSTRACT
Facial recognition technology has become a routine instrument of law enforcement across India, deployed by state police forces and proposed for integration into a National Automated Facial Recognition System. Yet the legal architecture governing these deployments remains profoundly underdeveloped. This article advances a specific and original argument: persons who suffer wrongful arrest, detention, or reputational injury as a consequence of a false algorithmic identification are not merely victims of administrative error. They constitute a distinct legal category, the algorithmic victim, whose harms are systematically invisible under existing Indian law.
Drawing on victimological theory, constitutional jurisprudence, and comparative law, the article demonstrates that the absence of recognition produces a remedial vacuum. No statutory provision requires notice before deployment, mandates human verification, or confers compensation rights upon the misidentified. Constitutional remedies, while theoretically available under Articles 14 and 21, are practically inaccessible to those who cannot identify the algorithmic cause of their arrest. The article examines how the European Union's AI Act, the United Kingdom's Bridges litigation, and documented American wrongful arrests have begun to forge accountability frameworks, and concludes by proposing a victim-centered statutory model for India, one grounded in the right to algorithmic due process and in the state's positive obligation to prevent foreseeable harm.
Keywords: Facial Recognition Technology; Algorithmic Victim; False Positives; Article 21; Algorithmic Due Process; NAFRS; Victimology
