A Taxonomy for AI Hazard Analysis

Abstract

With the rise of artificial intelligence in safety-critical systems like surface transportation, there is a commensurate need for new hazard analysis approaches to determine if and how AI contributes to accidents, which are also increasing in number and severity. The original Swiss Cheese model widely used for hazard analyses focuses uniquely on human activities that lead to accidents, but cannot address accidents where AI is a possible causal factor. To this end, the Taxonomy for AI Hazard Analysis (TAIHA) is proposed that introduces layers focusing on the oversight, design, maintenance, and testing of AI. TAIHA is illustrated with real-world accidents. TAIHA does not replace the traditional Swiss Cheese model, which should be used in concert when a joint human-AI system exists, such as when people are driving a car with AI-based advanced driving assist features.