Digital Inequality and Social Stratification: A Sociological Analysis of Access, Agency, and Algorithmic Bias in India

Abstract

Digital technologies have transformed social interaction, education, labour, and governance in India. Yet, this transformation is uneven. This paper investigates how digital inequality defined as disparities in access, literacy, and algorithmic fairness—intersects with traditional axes of social stratification such as caste, class, gender, and geography. Drawing on intersectional theory and empirical data from the National Sample Survey Office (NSSO), Pew Research Centre, and Telecom Regulatory Authority of India (TRAI), the study reveals that digital tools often replicate and intensify existing inequalities. The analysis begins with a theoretical framework combining social constructivism and intersectionality, then examines infrastructural gaps in internet access, mobile ownership, and digital literacy. It further explores algorithmic bias in platforms and AI systems, showing how marginalized groups are disproportionately excluded or misrepresented. Case studies—including the impact of the TikTok ban on Dalit creators and gendered access to online education—illustrate the lived consequences of digital stratification.

 The paper concludes with policy recommendations for inclusive digital development, emphasizing ethical AI, participatory design, and targeted literacy programs. By situating digital inequality within broader sociological debates on power and exclusion, this research contributes to understanding how technology can both challenge and reinforce social hierarchies in India.