Concrete Problems in AI Safety, Revisited

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. The rapid adoption and widespread experimentation and deployment of AI systems has triggered a variety of failures. Some are catastrophic and visible such as in the case of fatal crashes involving autonomous vehicles. Other failures are much more subtle and pernicious, such as the development of new forms of addiction to personalized content.