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Algorithmic Status Inequality: An Integrative Perspective on AI-Driven Social Stratification

Citation. Wu, J. (2026). Algorithmic status inequality: An integrative perspective on AI-driven social stratification. Journal of Management Studies. https://doi.org/10.1111/joms.70134

Summary. This conceptual journal article introduces algorithmic status inequality as durable differences in social position, influence, and resource access that AI systems can reinforce. It argues that computational beliefs embedded in design and unequal computational capabilities interact through feedback loops to institutionalize status hierarchies, so neither technical debiasing nor market dynamics alone is sufficient.

Key claims

• Algorithmic status inequality is a sociotechnical form of stratification in which AI systems can reinforce enduring differences in legitimacy, authority, influence, and resource access.
• Computational beliefs, or cultural assumptions encoded in AI design, and computational inequalities, or unequal technical capabilities and resources, mutually amplify rather than independently add to status disparities.
• Recruitment, healthcare, and legal-assistance cases illustrate three proposed patterns: schisms within minority-serving systems, tensions between dominant and specialized algorithms, and disparities between algorithmic systems and human experts.
• Interventions must jointly address encoded cultural assumptions and material inequalities because isolated technical fixes or market mechanisms can leave reinforcing feedback loops intact.

Evidence & limitations

• This is a conceptual “Point” article that integrates prior literature and illustrative cases; it does not report a new empirical study or estimate effect sizes.
• The framework is useful for diagnosing sociotechnical mechanisms across institutional domains, but its proposed patterns and interventions require direct empirical testing in specific organizational settings.

Feeds

• responsible-ai-deployment
• Proposed new topic: algorithmic-status-inequality — a distinct framework for AI-mediated status stratification that is broader than technical fairness or deployment governance alone.