Embodied AI (eAI) uses artificial intelligence based on machine learning to interact with the physical world. We are already seeing eAI deployed in the real world in robotaxis, smart medical devices, household robots, and other applications. However, everyone is struggling with the safety of these devices: how to design for safety, how to evaluate safety, and how to think about whether any particular eAI system is acceptably safe.
This talk provides an overview of my new book on this topic, with robotaxi safety as a concrete example. Anyone working in this area needs a basic understanding of four core areas: safety engineering, cybersecurity engineering, machine learning technology, and human/computer interaction. The talk also discusses eAI safety issues in the wild, the complexities of establishing what risks might be acceptable, and open challenges in eAI safety. A proposal for reimagining safety engineering responds to the huge disruption that eAI technology creates when applying traditional computer-based system safety approaches. The talk finishes with a call to build justifiable trust in eAI safety.