Working paper introduces a framework for connecting human capabilities in AI systems, highlighting implications for governance.
This working paper introduces Transition Architecture for Human Capability as a conceptual framework for AI-mediated systems transformation. It develops the concepts of the Human Capability Layer, Recognition Latency, and Transition Integrity to describe how learning, lived experience, informal competence, institutional recognition, participation, and governance can be connected responsibly across systems. The paper argues that AI adoption is not arrival. Organizational and societal transformation depends on whether systems can translate human capability into recognized, governed, and participatory forms of action. Version 1.2 is a full working-paper draft prepared for open preprint publication and subsequent iteration. It is not peer reviewed.
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Stefanie Haslauer (2026) studied this question.
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