Mingdong He has posted Floors and Ceilings: A Hohfeldian Analysis of Artificial Intelligence Governance on SSRN. Here is the abstract:
Debate over artificial intelligence governance is organised along a single axis running from permissive to restrictive. This article argues that the axis obscures a distinction of jural type. Using Hohfeld’s analysis of fundamental legal conceptions, I show that instruments imposing determinate obligations (floors) and instruments licensing persons (ceilings) operate at different orders of legal relation: the first imposes a duty correlative to a right; the second confers a power on an administrative body, correlative to a liability in the researcher — a susceptibility to having one’s legal position altered without having done anything wrong. The second-order character of ceilings explains four otherwise puzzling features: their resistance to textual constraint, their attractiveness to capture, the monotonicity of their incidence in firm size, and their resistance to downward revision. I derive a six-part test classifying a proposed instrument from the face of its text — distinguishing floors, defective floors, and ceilings — and apply it to four near-simultaneous interventions of 2025–2026, clause by clause to the EU Artificial Intelligence Act — which contains both forms — and to the Chinese position, whose pairing of domestic permission with state-encouraged diffusion both instantiates the framework’s predictions and disciplines its addressees elsewhere. The claim that ceilings redistribute participation toward incumbents is evidenced from the GDPR natural experiment and the occupational-licensing record. Comparative analysis of recombinant DNA governance, pharmaceutical authorisation, and aviation incident reporting identifies when a ceiling is warranted; eight floor-compatible instruments are set out, with a candid feasibility note on mandatory insurance. I conclude with the conditions on which the framework’s fate depends, including the one that would defeat it on the point that matters most.
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