Matthieu Queloz

In the AI Story

Queloz's 2025 analysis identifies three asymmetries that AI advisory systems produce between builders and users: epistemic, structural, and temporal. The epistemic asymmetry is the information differential between those who understand the system and those who interact with it. The structural asymmetry is the institutional differential between those who design the system and those whose lives the system shapes. The temporal asymmetry is the differential between the time available to the builder to assess consequences and the time available to the affected to respond to them. Each asymmetry, Queloz argues, is a form of power in Shklar's precise sense, and power without accountability is the precondition for cruelty.

The analysis extends Shklar's framework in a direction she did not specifically address but which her framework anticipates. Personalization, Queloz argues, risks translating structural injustices into individualized challenges. The structural forces that produce overwork — competitive pressure, the institutional absence of rest, the cultural equation of productivity with worth — are experienced by the individual as personal challenges to be overcome through better time management, better self-care, better optimization. The structural is individualized. The political is psychologized. The domination disappears into the vocabulary of self-improvement. This diagnosis connects directly to Shklar's core argument that the reclassification of injustice as misfortune is the oldest instrument of political domination.

Queloz's pragmatist methodology — his emphasis on what political concepts do rather than what they metaphysically are — makes his analysis particularly compatible with Shklar's own. Shklar was suspicious of metaphysical foundations for political theory. Queloz shares this suspicion and applies it to AI ethics, resisting attempts to ground AI regulation in abstract rights claims and focusing instead on the specific institutional arrangements that make particular outcomes more or less likely. This approach produces recommendations that are often more modest than those emerging from rights-based frameworks but also more specifically implementable and more likely to survive political contestation.

His broader scholarly project on the history of liberal political philosophy — including work on Williams, on normative genealogy, and on the Oxford moral philosophy tradition — situates AI ethics within a longer conversation about how political theory responds to novel forms of institutional power. The AI case, on Queloz's analysis, is not categorically different from earlier cases of emergent technological and institutional power that political theory has analyzed for centuries. The framework Shklar developed to address those earlier cases applies to AI with specific adjustments rather than requiring replacement. This continuity is the foundation on which this volume builds.

Origin

Queloz received his DPhil in Philosophy from the University of Oxford in 2019 and has held positions at Basel, Bern, and Oxford. His 2025 paper applying Shklar to AI advisory systems has been widely discussed within both political philosophy and AI ethics communities.

Key Ideas

Three asymmetries structure AI-user relations. Epistemic, structural, and temporal differentials constitute forms of power requiring accountability.

Personalization individualizes the structural. AI systems convert political conditions into personal challenges, eliminating the political demand for structural remedy.

Pragmatist methodology is productive. Focusing on what political concepts do rather than what they metaphysically are produces specifically implementable recommendations.

AI continuity with prior cases. The framework Shklar developed for earlier institutional power applies to AI with adjustments rather than requiring replacement.

The reclassification move persists. Shklar's core insight about misfortune-injustice reclassification operates with renewed force in AI's individualization of structural conditions.