AI-Driven Personalization to Support Human-AI Collaboration
Cristina Conati · 2024
At the Human-AI Interaction group at the University of British Columbia, we investigate how to support Human-AI collaboration via AI artifacts that can understand relevant properties of their users (e.g., states, skills, needs) and personalize the interaction accordingly in a manner that preserves transparency, user control and trust. In this talk, I will illustrate examples of our research in AI-drive personalization spanning areas such as User Adaptive Visualizations, intelligent Tutoring Systems, and Personalized Explainable AI.