Human AI Interaction
Human-AI interaction research focuses on designing effective and safe collaborations between humans and artificial intelligence systems, primarily aiming to optimize task performance, user experience, and ethical considerations. Current research emphasizes developing novel interaction paradigms beyond simple turn-based exchanges, utilizing large language models (LLMs) and reinforcement learning algorithms to create more natural and intuitive interfaces, including non-verbal communication methods. This field is crucial for advancing AI safety, improving the usability of AI tools across various sectors (healthcare, education, industry), and informing the ethical development and deployment of increasingly autonomous AI systems.
Papers
Understanding User Perceptions, Collaborative Experience and User Engagement in Different Human-AI Interaction Designs for Co-Creative Systems
Jeba Rezwana, Mary Lou Maher
Exploring How Anomalous Model Input and Output Alerts Affect Decision-Making in Healthcare
Marissa Radensky, Dustin Burson, Rajya Bhaiya, Daniel S. Weld