Insuring the Fallback: Capital, Monitoring, and the Certification of Preserved Human Capability under Improving AI

Abstract

When generative AI makes the deliverable uninformative, a professional-services provider can still certify the preserved human capability to catch the machine's errors, through a liability pledge whose expected cost falls in that capability. The pledge is credible only up to what can be collected, and that ceiling is set by an underwriter, which bears part of the pledge and audits the insured. The range of client stakes over which one certificate separates has a width bounded by the provider's own capital plus the audited share of the underwriter's capacity, so unmonitored capacity adds nothing to it. Blind capital instead relocates that range upward, through a cross-subsidy that exists only under class rating. Monitoring converts capital into width, removes the cross-subsidy, raises the return to preserving skill, and, because audit information leaks, makes the certificate redundant beyond an interior precision.

arXiv comment43 pages, 10 figures. v2 replaces the equilibrium construction of v1 (see Appendix B) and carries a new title. Builds on four companion papers by the author (arXiv:2607.26327, published in Games 17(5):49; arXiv:2608.04276; arXiv:2608.05969; arXiv:2609.26141). Replication package: doi:10.6084/m9.figshare.33193704. JEL: D82, D86, G22, K13, L15