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Policy·P Space·Evidence-backed problem·Published 2026-08-05

Artificial intelligence, work, and structural inequality: Why human-centric AI requires institutional architecture, not just ethics

Abstract: BackgroundThe rapid integration of artificial intelligence (AI) into labour markets, migration governance, and social protection systems is increasingly reshaping how institutional decisions are produced, delegated, and enforced. While human-centric and ethics-based AI frameworks have established important normative principles, concerns regarding inequality, opacity, and accountability in AI-mediated decision-making continue to persist across labour-related environments.ObjectiveThis article examines why ethical…

TRV-2026-0648Peer-reviewedPermanent record — cite & verify
Artificial intelligence, work, and structural inequality: Why human-centric AI requires institutional architecture, not just ethics

The ethics of Aristotle by D. P. Chase. Public domain

The quick read

Published August 4 2026 in WORK, this peer-reviewed analysis examines AI integration into labour markets, migration governance and social protection systems. It argues AI functions as institutional infrastructure and shows how continuous classification, automated risk assessment and worker scoring can amplify structural inequalities when deployed at scale.

The piece matters because it reframes AI governance challenges in work from ethical principles to institutional architecture, arguing oversight becomes procedural rather than substantive under administrative complexity. What remains uncertain is how specific governance architectures and contestability mechanisms would perform empirically, as the article relies on literature synthesis and illustrative examples rather than measured interventions.

Main points
  • Article frames AI as operational infrastructure organizing institutional visibility, discretion, prioritisation, and authority, not just a technical tool.
  • Labour markets and migration governance are presented as stress-test domains where classification and automated risk assessment operate at scale.
  • Authors argue ethics-based frameworks are insufficient and call for institutionally grounded governance architectures and enforceable operational oversight.
Problem

When AI is embedded in labour market and migration governance infrastructure, continuous classification, worker scoring and automated risk assessment can amplify structural inequalities while human oversight becomes procedural under scale and speed.

The rundown

The article conceptualises AI as part of the operational infrastructure through which institutional visibility, discretion, prioritisation, and authority are organised, drawing on institutional and policy analysis and labour and migration governance literature.

It uses labour markets and migration governance as stress-test domains to show how fragmented data environments and automated systems reshape delegation and enforcement, concluding that fairness requires contestability mechanisms and enforceable operational oversight beyond ethics-first compliance.

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