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
Attaining Human`s Desirable Outcomes in Human-AI Interaction via Structural Causal Games
Anjie Liu, Jianhong Wang, Haoxuan Li, Xu Chen, Jun Wang, Samuel Kaski, Mengyue Yang
Improving Health Professionals' Onboarding with AI and XAI for Trustworthy Human-AI Collaborative Decision Making
Min Hun Lee, Silvana Xin Yi Choo, Shamala D/O Thilarajah
Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization
Benjamin Alt, Johannes Zahn, Claudius Kienle, Julia Dvorak, Marvin May, Darko Katic, Rainer Jäkel, Tobias Kopp, Michael Beetz, Gisela Lanza
AI, Pluralism, and (Social) Compensation
Nandhini Swaminathan, David Danks
Scalable Interactive Machine Learning for Future Command and Control
Anna Madison, Ellen Novoseller, Vinicius G. Goecks, Benjamin T. Files, Nicholas Waytowich, Alfred Yu, Vernon J. Lawhern, Steven Thurman, Christopher Kelshaw, Kaleb McDowell
Maia: A Real-time Non-Verbal Chat for Human-AI Interaction
Dragos Costea, Alina Marcu, Cristina Lazar, Marius Leordeanu