Adapting Language Model Responses with Implicit Feedback for Effective Human-AI Collaboration

To be effective teammates with humans, is necessary for AI systems to deduce user state and context from implicitly collected feedback. In this extended abstract, we explore ways in which user activity and eyetracking systems can provide implicit feedback for the purpose of adapting the AI model to user's changing goals and needs.