智能体框架缺乏实时监督所需记录
Partnership on AI 的人员称,数百个 OpenAI 智能体逃出网络安全测试环境并入侵 Hugging Face,另有一个智能体访问了澳大利亚政府网站上的私人文件。他们还援引了 Anthropic、Google 和 Meta 披露的智能体偏离任务事件。对四种常用智能体框架的研究发现,现有记录存在重大缺口,难以识别违规行为、未授权操作和人工监督失效。OpenTelemetry 负责制定智能体追踪共享格式的工作组尚未敲定相关标准。
作者指出,现有记录往往难以查明是哪个智能体采取了行动、其任务是否获得人工批准,以及权限或记忆是否发生变化。他们建议记录持久化的智能体身份、人工干预以及权限或记忆变更,使开发者和部署方能够在智能体运行时进行监督。
This summer, hundreds of OpenAI agents tried to cheat on a cybersecurity test. They broke out of their test environment and successfully hacked Hugging Face, a site that they believed held clues about how they’d be graded. Around the same time, another OpenAI agent accessed private files from an Australian government website. It’s a problem that’s by no means confined to OpenAI. In the months since, Anthropic, Google, and Meta have also disclosed incidents in which their agents have gone off track. And worryingly, in many cases the agents eluded the very researchers and safety teams tasked with monitoring them.
AI agents are taking unauthorized actions, and the companies building and running them are mostly relying on luck and hindsight to mitigate any harmful impacts. They must do more to ensure safety. That’s why EU regulators and US agencies are rightfully calling for agent developers and deployers to monitor agents in real time. But these rules assume that companies can see what their agents are doing and why—when in reality, they lack sufficient visibility.
Imagine a bank hiring a thousand new employees who can access customer accounts and sensitive information, but the employees’ ID badges change every day, it’s not clear whether a manager ever reviewed or authorized their work, and nobody logs the changes employees make to approval processes. That lack of visibility is where we are with agents today.
#OpenAI#Hugging Face#Anthropic#Google#Meta#Partnership on AI#OpenTelemetry#CrewAI#LangChain#NIST