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Research & IP研究与专利

AISPA: A User-Centric Framework for Auditing Hidden System Prompts in LLM ApplicationsAISPA 框架：以用户为中心审计 LLM 应用中的隐藏系统提示词

S 5.0 T1 1 sources1 个来源 R2-regulatory

Researchers propose AISPA (Artificial Intelligence System Prompt Assurance), a user-centric framework for systematically auditing the system prompts developers use to govern foundation model behavior in commercial AI applications.
The paper notes system prompts are used throughout commercial AI products but are rarely disclosed to the public or regulators, calling this a serious trust and accountability gap in widely deployed AI systems.
For automotive, the same auditing logic applies to in-vehicle AI assistants and autonomous-driving systems, where undisclosed system-prompt instructions could carry safety, regulatory-compliance, and consumer-trust implications.

研究者提出 AISPA（Artificial Intelligence System Prompt Assurance）框架，用于系统性审计开发者用来控制商用 AI 应用中基础模型行为的系统提示词。
论文指出，系统提示词广泛用于商用 AI 产品，但很少向公众或监管机构披露，这在大规模部署的 AI 系统中造成了严重的信任与问责缺口。
对汽车行业而言，同样的审计逻辑适用于车载 AI 助手和自动驾驶系统——未披露的系统提示词指令可能牵涉安全性、监管合规和用户信任等问题。

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