ALGORITHMIC DISCRIMINATION AND SOCIAL INEQUALITY: EMERGING CHALLENGES FOR INDIAN LAW

The rapid expansion of Artificial Intelligence (AI), automated decision-making systems and algorithmic technologies is transforming the manner in which individuals interact with institutions, markets and the State. While algorithms are often perceived as objective and technologically neutral, their design, training data and deployment may reproduce or amplify existing patterns of social inequality. In a socially diverse country such as India, where inequalities based on caste, gender, class, language, region, disability and economic status continue to influence access to opportunities and resources, algorithmic decision-making presents emerging sociological and legal challenges. This research paper examines algorithmic discrimination as a contemporary form of structural inequality and analyses how automated systems may perpetuate historical and institutional biases while making discriminatory outcomes less visible and more difficult to challenge. The paper adopts a socio-legal and interdisciplinary approach to examine the relationship between algorithmic systems and constitutional principles of equality, non-discrimination, dignity and privacy. It analyses the relevance of Articles 14, 15, 16 and 21 of the Constitution of India, judicial developments concerning privacy and informational autonomy, and the emerging framework governing digital personal data and artificial intelligence in India. Particular attention is given to algorithmic applications in employment, financial services, welfare delivery, education, public administration and other areas where automated decisions may significantly affect individuals' social and economic opportunities. The study also examines the problems of algorithmic opacity, lack of explainability, unequal access to technology, accountability gaps and difficulties in establishing discriminatory intent or causation. From a sociological perspective, the paper argues that technological systems operate within existing social structures and therefore cannot be examined independently of the inequalities embedded in the societies in which they are developed and deployed. The study concludes by exploring possible legal and institutional responses, including algorithmic impact assessments, transparency requirements, human oversight, independent auditing, effective grievance mechanisms and stronger anti-discrimination safeguards. It seeks to contribute to the emerging Indian discourse on responsible AI by examining how law can respond to technological systems without losing sight of the underlying social structures that produce inequality.