Fairness on Autopilot? Regulating Algorithmic Decisions in Indian Governance

Author(s): Shabnam Akbar Pathan, Dr. Rajeshri N. Varhadi and Dr. Sanjay Jadhav

Abstract:

As India fast-tracks its digital transformation, artificial intelligence (AI) is quietly stepping into spaces once governed by human judgment-from welfare distribution and facial recognition to predictive policing and public service delivery. While the tech promises efficiency and scalability, it also raises pressing questions: What happens when an algorithm makes a mistake? Who's accountable? And most importantly-is the process fair? This paper explores the growing use of AI-based decision-making systems in Indian governance and interrogates the legal and ethical frameworks (or the lack thereof) guiding them. Unlike traditional legal mechanisms that prioritize human dignity and due process, AI operates in a black-box model, often with little transparency or room for contestation. These systems largely imported or developed without local socio-legal context, risk reinforcing existing inequalities, especially when deployed in areas affecting marginalized communities.
The research draws upon constitutional principles of fairness, non-discrimination, and procedural justice to examine whether India's current legal landscape is equipped to regulate algorithmic decision-making. It critically evaluates existing policies such as the Personal Data Protection Bill and National AI Strategy, revealing significant regulatory blind spots. By comparing global models of AI governance and accountability (such as the EU’s AI Act), the study highlights the urgent need for an Indian framework that balances innovation with justice. Ultimately, this paper argues that without human-centric laws and ethical oversight, the promise of AI can quietly turn into digital disenfranchisement. We must build systems where the code serves the people-not the other way around.

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Pages: 08-11     |    1 View     |    0 Download