厘清AI安全与AI安全的边界，避免概念混淆。
AI Safety vs. AI Security: Demystifying the Distinction and Boundaries
- 用通信和建筑类比区分安全与安全机制。
- 指出安全漏洞可引发安全问题，反之亦然。
- 适合研究者、政策制定者和系统设计者参考。
人工智能正快速融入医疗、自动驾驶等关键领域，带来巨大效益的同时也引入显著风险，尤其是滥用风险。在风险管控讨论中，'AI安全'与'AI安全'常被混用，导致概念模糊。本文旨在厘清二者区别，明确各自研究边界。通过严谨定义，阐述其研究重点及相互依存关系，说明安全漏洞可能引发安全问题，反之亦然。借助消息传输与建筑施工的类比，直观展示差异。澄清这些边界对指引精准研究方向、促进跨学科协作、提升政策效力至关重要，最终推动可信AI系统的部署。
原文摘要 · Abstract (English)
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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