Section Article

The Impact of Algorithmic Bias in Artificial Intelligence on Social Stratification
Author(s): Vikash Aggarwal

Abstract
The rapid evolution of artificial intelligence (AI) has transformed decision-making processes across diverse sectors such as employment finance and criminal justice. However these technological advancements have also introduced significant challenges most notably the issue of algorithmic bias. This paper examines how inherent biases in AI systems—often originating from historical data imbued with social prejudices—both reflect and reinforce social stratification. By analyzing a range of empirical case studies and synthesizing insights from sociology computer science and ethics this study reveals that biased algorithms not only mirror pre-existing societal inequalities but also create self-perpetuating cycles that restrict socioeconomic mobility for marginalized groups. The research underscores the urgent need for ethical frameworks greater transparency and regular auditing in AI development. Ultimately this paper calls for an interdisciplinary collaboration among policymakers technologists and social scientists to transform AI into an instrument for social equity rather than division.