[2605.07671] The Endogeneity of Miscalibration: Impossibility and Escape in Scored Reporting

Computer Science > Computer Science and Game Theory arXiv:2605.07671 (cs) [Submitted on 8 May 2026] Title:The Endogeneity of Miscalibration: Impossibility and Escape in Scored Reporting Authors:Lauri Lovén, Sasu Tarkoma View a PDF of the paper titled The Endogeneity of Miscalibration: Impossibility and Escape in Scored Reporting, by Lauri Lov\'en and Sasu Tarkoma View PDF HTML (experimental) Abstract:Eliciting truthful reports from autonomous agents is a core problem in scalable AI oversight: a principal scores the agent's report using a strictly proper scoring rule, but the agent also benefits from the report through a non-accuracy channel (approval for autonomous action, allocation share, downstream control). The same structure appears in classical mechanism-design settings such as marketplace operation. Our main result is an endogeneity: the principal's optimal oversight necessarily uses a non-affine approval function to screen types, yet any non-affine approval makes truthful reporting suboptimal under the combined objective whenever deviation is undetectable. The principal cannot avoid the perturbation that undermines calibration. This impossibility holds for all strictly proper scoring rules, with a closed-form perturbation formula. A constructive escape exists: a step-function approval threshold achieves first-best screening for every strictly proper scoring rule, because the agent's binary inflate-or-not choice creates a type-space threshold regardless of the gener...