AI Liability Insurance With an Example in AI-Powered E-diagnosis System

TL;DR

This paper explores AI liability insurance using an AI-powered E-diagnosis system as a case study, proposing a risk assessment model and discussing regulatory and economic implications for AI integration.

Contribution

It introduces a quantitative risk assessment model for AI liability insurance and discusses insurability criteria and premium adjustments specific to AI technologies.

Findings

AI liability insurance can incentivize compliant AI behavior

Proposed premium adjustments reflect AI uncertainty evolution

Insurance acts as a regulatory mechanism for AI quality

Abstract

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 system as an example to study AI liability insurance. We provide a quantitative risk assessment model with evidence-based numerical analysis. We discuss the insurability criteria for AI technologies and suggest necessary adjustments to accommodate the features of AI products. We show that AI liability insurance can act as a regulatory mechanism to incentivize compliant behaviors and serve as a certificate of high-quality AI systems. Furthermore, we suggest premium adjustment to reflect the dynamic evolution of the inherent uncertainty in AI. Moral hazard problems are discussed and suggestions for AI liability insurance are provided.