Topic
human-ai interaction
New Research Identifies Principles for Positive Human-AI Agent Interaction in Business
Researchers Paimann, Valarini, and Juhl used mixed-methods to identify principles for positive UX with AI agents in business, providing a foundation for designing intuitive interactions.
Explainable deep learning improves human mental models of self-driving cars, study finds
A new method called Concept-Wrapper Network (CW-Net) provides faithful explanations of deep neural network planners in self-driving cars, improving human drivers' ability to anticipate vehicle behavior, especially in surprising situations. Deployed on a real autonomous vehicle, the system shows that explainable AI can be practical and useful in real-world settings.
Cognitive Trajectory Modeling: A New Framework for Quantifying Human-AI Co-Creation
Cognitive Trajectory Modeling (CTM) is a novel cognitive theory of interaction dynamics that conceptualizes cognition and creative processes as temporally organized trajectories. It provides a framework for quantifying how human-AI co-creation evolves over time, distinguishing cognitive trajectories from mere interaction traces.