Theoretical proposal models human capability conversion dynamics in rapidly automating societies, highlighting the urgency of preventing technological lock-in.
Status. K0 theory proposal and empirical research agenda; v1.1 is the glosa-checked edition of the 6 September 2026 v1.0 (citation lineage repaired to deposited DOIs and versions; priority wording removed; a companion-paper attribution softened from "shows formally" to "proposes"; no content change). Part of the series When AI Expands Human Potential (index DOI 10.5281/zenodo.22308201). Companion papers: After Labour and How Humans Should Converse with AI. Central thesis. The central problem of an AI-rich society is not whether machines become capable but whether machine capability is converted into durable human capability and broadly distributed systemic standing fast enough to prevent dependency, deskilling, gate concentration and lock-in. The paper defines a nine-dimensional Human Conversion Vector, conversion elasticities, a Bad-Mode state space, a Reversibility Window and an Urgency Vector, six minimum safeguard invariants, five rival models and explicit removal conditions. Current 2024–2026 evidence motivates but does not validate the model. An AI assistant assisted under the author's direction; no AI system is an author or contributor.
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Yaoharee Lahtee (2026) studied this question.
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