6 papers · 1 filter
Insuring the Fallback: Capital, Monitoring, and the Certification of Preserved Human Capability under Improving AI
Andreas Bauer
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 l…
Doctrine as a Fixed Point: A Formal Model of the Enforceable Penalty Ceiling when Human Oversight of AI Must Remain Effective
Andreas Bauer
Article 14 of the EU AI Act requires that a high-risk system be overseen by natural persons who understand its limits, remain alert to automation bias, and can disregard or overrid…
The Last Costly Signal: How Generative AI Collapses Competence Signaling and Why Liability Sustains Markets for Expert Services
Andreas Bauer
Generative artificial intelligence has reduced the cost of producing convincing artifacts of expertise-reports, analyses, proposals-to nearly zero. Signaling theory predicts that s…
The Fallback as Signal: Preserved Human Skill, Liability, and Competence Signaling in Credence-Good Markets under Improving AI
Andreas Bauer
Providers deploying imperfect AI must decide how much to keep humans engaged: engagement costs output but builds the fallback skill needed when it fails. A liability pledge whose e…
Three Ceilings: Model Monoculture, Solvency, and the Penalty Doctrine in Markets for Expert Services
Andreas Bauer
When generative AI drives the marginal cost of a persuasive expert artefact toward zero, production-cost signals of competence collapse and outcome-contingent liability commitments…
The Institutional Window: Occupation- and Jurisdiction-Specific Calibration of Liability Signaling for Preserved Human Fallback Capability
Andreas Bauer
Generative AI makes expert output uninformative about the human fallback capability its provider keeps in reserve. A liability commitment can signal that capability: a provider who…