Artificial intelligence is often framed as a neutral technical tool that enhances efficiency and consistency in institutional decision-making. This article challenges that framing by showing that automated systems now operate as social and institutional actors that reshape recognition, opportunity, and public trust in everyday life. Focusing on employment screening, welfare administration, and digital platforms, the study examines how algorithmic systems mediate social relations and reorganise how individuals are evaluated, classified, and legitimised. Drawing on regulatory and policy materials, platform governance documents, technical disclosures, and composite vignettes synthesised from publicly documented evidence, the article analyses how automated judgement acquires institutional authority. It advances three core contributions. First, it develops a sociological framework explaining how delegated authority, automated classification, and procedural opacity transform institutional power and individual standing. Second, it demonstrates a dual logic of inequality: automated systems both reproduce historical disadvantage through patterned data and generate new forms of exclusion through data abstraction and optimisation practices that detach individuals from familiar legal, social, and moral categories. Third, it shows that automation destabilises procedural justice by eroding relational recognition, producing trust deficits that cannot be resolved through technical fairness or explainability alone. The findings reveal that automated systems do not merely support institutional decisions; they redefine how institutions perceive individuals and how individuals interpret institutional legitimacy. The article concludes by outlining governance reforms aimed at restoring intelligibility, accountability, inclusion, and trust in an era where automated judgement increasingly structures social opportunity and public authority.
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Oluwaseyi B. Ayeni
Isabella Musinguzi-Karamukyo
Oluwakemi T. Onibalusi
Societies
Imperial College London
University of Strathclyde
University of Buckingham
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Ayeni et al. (Thu,) studied this question.
www.synapsesocial.com/papers/699011172ccff479cfe57841 — DOI: https://doi.org/10.3390/soc16020059