CURE2026: Communicating Uncertainty to foster Realistic Expectations via Human-Centered Design

CURE2026 workshop provides a venue for research on how interactive and intelligent interfaces can be leveraged to ensure effective uncertainty communication. With the increased capabilities of black-box AI models, particularly large language models (LLMs), there is a growing urgency to understand exactly what these models can and cannot do. Effective uncertainty communication can help users calibrate their trust and reliance on the AI system. However, effectively conveying uncertainty, be it through conversation or by visualizing their confidence levels, remains a major challenge, as users often get confused or misinterpret uncertainty information due to poorly designed interfaces. CURE2026 workshop brings together researchers from HCI, AI, design, and psychology to investigate how we can design, develop, and evaluate intelligent and interactive interfaces for uncertainty communication. The workshop includes a mini-conference section aimed at inspiring discussion and investigating the role of intelligent and interactive interfaces in uncertainty communication. The workshop also features keynotes by Professors Jessica Hullman and Katrien Verbert. Finally, a part of the workshop is dedicated to an interactive activity to discuss and develop guidelines for communicating uncertainty across different domains and tasks.