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

• URL: http://arxiv.org/abs/2506.18932v1
• Date: Sat, 21 Jun 2025 18:36:03 GMT
• Title: AI Safety vs. AI Security: Demystifying the Distinction and Boundaries
• Authors: Zhiqiang Lin, Huan Sun, Ness Shroff,
• Abstract summary: "AI Safety" and "AI Security" are often used, sometimes interchangeably, resulting in conceptual confusion.<n>This paper aims to demystify the distinction and delineate the precise research boundaries between AI Safety and AI Security.
• Score: 37.57137473409321
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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