Constitutive Priors for Machine Intelligence: A Legitimacy Theory of the Artificial Physical World

Authors:Jiang Jiang (1), Yifu Sun (1), Qi Shen (1) ((1) Persagy Science and Technology Co., Beijing, China)

Abstract:Machine intelligence has conquered the symbolic world but stalled at the physical one. The stall is structural: physical AI faces a cold-start deadlock -- no intelligence without data, no data without deployed intelligence. Our thesis: the deadlock is real but unevenly distributed, and the exception has a name: the artificial physical world. Buildings, industrial facilities, and infrastructure are intentionally constituted and documented: designed artifacts ship with readable archives that precede and constitute their instances; here, norms are promulgated before instances, not averaged from them. Four contributions. (i) From a four-world ontology we derive a legitimacy criterion for constitutive prior frameworks: prior extraction is legitimate if and only if the object domain is intentionally constituted and has left a readable archive; the criterion is testable through direction of fit -- deviation from a constitutive norm is a violation in the world, not a revision of the model. (ii) We establish a layering lower bound: any such framework has at least four layers -- syntax, concept, knowledge, instance -- because four construction goals pair into mutually incompatible carriers. (iii) We register deployment claims across five industrial domains and a 32-class failure-mode vocabulary. (iv) We stake the framework on five falsifiable predictions, the central one checkable on the public engineering record: if it fails, the framework fails. Semi-formal arguments back these claims (Appendix A): a Gold-type boundary on rule coverage in archiveless worlds, a decidability result for failure reduction over closed concept layers, and a boundary theorem for certificate-anchored calculi. Large language models find an honored place here -- as readers of the archive, not as the archive. First of three companion works; the companions take up the questions deliberately left open.

55 pages, 3 figures, 75 references. Appendix A contains the semi-formal statements. First of three companion works; the two companions are in preparation

Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)

arXiv:2608.15147 [cs.AI]

(or arXiv:2608.15147v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.15147 arXiv-issued DOI via DataCite (pending registration)