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March 16, 2026JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH0 citationsOpen Access

Artificial Intelligence and Social Inequalities: Disadvantages, Advantages and Inclusive Pathways

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SSSupriya SinghDDDr.Ram Das

Key Points

  • The aim is to examine how AI can both increase and decrease social inequalities across various sectors.
  • Literature review on AI applications in healthcare, education, labor markets, and governance.
  • Analysis of algorithmic bias and its effects on different social groups.
  • Discussion of ethical frameworks and policy strategies for inclusive AI development.
  • AI can improve efficiency and decision-making but also widen social inequalities.
  • Disparities in access to technology are influenced by race, class, and geographic location.
  • The article calls for responsible governance and equitable design to foster social justice.

Abstract

Artificial Intelligence (AI) has become a transformative technology that shape modern societies. Its covered wide range such as healthcare, education, long-term care, public governance, and labor markets. AI offers significant benefits such as improved efficiency, data-driven decision-making, and innovative service but it also raises important concerns about social inequality. The impacts of AI are not distributed equally across populations. Social groups such as race, class, gender gap, disability, and geographic location may experience different outcomes due to unequal access to technology, biased datasets, and structural inequalities embedded in algorithmic systems. This paper explores how AI can both widen and decrease social inequalities. It examines algorithmic bias, the digital gap, and the unequal distribution of technological advantages across key social sectors including healthcare, education, labor markets, and long-term care. Study also discusses ethical frameworks and policy strategies that can increase inclusive AI development. By exploring both the disadvantages and disadvantages of AI systems, the article highlights that responsible governance, equitable technological design, and inclusive data practices are important to ensure that AI promote social justice rather than reinforcing existing inequalities.

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Cite This Study

Singh et al. (2026) studied this question.

synapsesocial.com/papers/69b79e398166e15b153ab39fhttps://doi.org/10.56975/jetnr.v4i3.232983
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