Model-Based Reasoning for Explainable AI as a Service

摘要

As AI systems are increasingly being adopted into application solutions, the challenge of providing explanations and supporting interaction with humans is becoming crucial. Partly this is to support integrated working styles, in which humans and intelligent systems cooperate in problem-solving, but also it is a necessary step in the process of building trust as humans migrate greater responsibility to such systems. In this talk we discuss progress made in Explainable Planning, particularly in scenarios involving human-AI teaming, and we present recent advances in using model-based reasoning for designing Explainable AI as a Service.