AI Liability Insurance With an Example in AI-Powered E-diagnosis System
This work addresses the reluctance in adopting AI systems due to risks, proposing insurance as an economic solution for stakeholders like insurers and AI developers, but it is incremental as it builds on existing insurance concepts applied to AI.
The paper tackles the problem of AI liability insurance as a solution to mitigate risks and uncertainties in AI systems, using an AI-powered e-diagnosis system as an example to develop a quantitative risk assessment model and discuss insurability criteria, showing that it can incentivize compliance and certify high-quality AI.
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.