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What Has Wellbeing Got to Do With It? Artificial Intelligence, the Hybrid Tipping Zone, and the Crisis of Human Flourishing

Aug 2026 · Journal of Wellbeing Economics · Vol 1, pp. 43 - 53 · 0 citations · 33 references

TL;DR

The article argues that wellbeing economics offers the conceptual and measurement tools needed to evaluate AI as an innovation whose value cannot be inferred from market capitalization, productivity, or benchmark performance alone, and proposes three extensions for the field: hybrid eudaimonia, capabilities under algorithmic mediation, and aspirational algorithmic adaptation.

Abstract

Wellbeing economics has spent decades challenging the assumption that income, output, and human flourishing move together automatically. Artificial intelligence brings this familiar economic question into a new setting. AI can raise task-level efficiency, improve access to knowledge, support care, and reduce barriers for people who face cognitive, linguistic, or physical constraints. Its welfare effect remains conditional. Productivity gains become wellbeing gains when they expand real freedoms, strengthen human capacities, improve relationships, distribute benefits fairly, and respect ecological limits. They become wellbeing losses when efficiency is purchased through human deskilling, relational substitution, environmental externalities, or unequal exposure to algorithmic power. This viewpoint defines the hybrid era as the period in which human decisions, relationships, learning, work, and public institutions are increasingly co-produced with AI systems. It then uses the Hybrid Tipping Zone framework to organize four mechanisms with direct relevance for wellbeing economics: agency asymmetry, bond blur, concrete environmental costs, and distorted society. The article argues that wellbeing economics offers the conceptual and measurement tools needed to evaluate AI as an innovation whose value cannot be inferred from market capitalization, productivity, or benchmark performance alone. It proposes three extensions for the field: hybrid eudaimonia, capabilities under algorithmic mediation, and aspirational algorithmic adaptation. It closes with an institutional agenda that links WELLBY-style appraisal, capability assessment, Double Literacy, and ProSocial AI metrics to AI governance. The central claim is direct: institutions should assess AI’s technical power against its contribution to human and planetary flourishing.

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