AI Safety vs. AI Security: Demystifying the Distinction and Boundaries

TL;DR

This paper clarifies the distinct concepts of AI Safety and AI Security, emphasizing their differences, interdependencies, and importance for guiding research, policy, and trustworthy AI deployment.

Contribution

It provides rigorous definitions and analogies to demystify the distinction between AI Safety and AI Security, guiding clearer research and policy directions.

Findings

Defined AI Safety and AI Security clearly

Explored their interdependency and potential failure cascades

Provided analogies to illustrate distinctions

Abstract

Artificial Intelligence (AI) is rapidly being integrated into critical systems across various domains, from healthcare to autonomous vehicles. While its integration brings immense benefits, it also introduces significant risks, including those arising from AI misuse. Within the discourse on managing these risks, the terms "AI Safety" and "AI Security" are often used, sometimes interchangeably, resulting in conceptual confusion. This paper aims to demystify the distinction and delineate the precise research boundaries between AI Safety and AI Security. We provide rigorous definitions, outline their respective research focuses, and explore their interdependency, including how security breaches can precipitate safety failures and vice versa. Using clear analogies from message transmission and building construction, we illustrate these distinctions. Clarifying these boundaries is crucial for guiding precise research directions, fostering effective cross-disciplinary collaboration, enhancing policy effectiveness, and ultimately, promoting the deployment of trustworthy AI systems.