Concrete Problems in AI Safety, Revisited

随着人工智能系统在社会中的普及，人工智能界越来越关注人工智能安全的概念，即预防由于人工智能部署中系统行为与设计者意图不符而导致的意外故障。我们通过对此类事件的真实案例进行分析，证明尽管当前的词汇表涵盖了人工智能部署中遇到的一系列问题，但需要扩展社会技术框架以更全面地理解人工智能系统和实施的安全机制在现实生活中的成功和失败。

As AI systems proliferate in society, the AI community is increasingly preoccupied with the concept of AI Safety, namely the prevention of failures due to accidents that arise from an unanticipated departure of a system's behavior from designer intent in AI deployment. We demonstrate through an analysis of real world cases of such incidents that although current vocabulary captures a range of the encountered issues of AI deployment, an expanded socio-technical framing will be required for a more complete understanding of how AI systems and implemented safety mechanisms fail and succeed in real life.