Conversational Health Interfaces in the Era of LLMs

Designing for Engagement, Privacy, and Wellbeing

authored by

Shashank Ahire, Melissa Guyre, Bradley Rey, Minha Lee, Heloisa Candello

Abstract

As Large Language Models (LLMs) revolutionize Conversational User Interfaces (CUIs) in health and wellbeing, these technologies offer unprecedented potential to enhance user wellbeing by improving physical health, psychological resilience, and social connectivity. However, the integration of such advanced AI into everyday CUI health applications brings substantial challenges, including privacy, user agency, and the psychological impacts of AI interactions. This workshop will provide a platform for collaborative dialogue to explore leveraging these advancements to improve health outcomes while addressing the ethical challenges and risks. Through presentations, breakout sessions, and collaborative discussions, participants will delve into themes such as designing multimodal CUI interventions, structuring conversational interventions for privacy and engagement, personalizing user experiences, and developing proactive and context-adaptive CUI strategies. These discussions aim to develop effective, user-centered CUI strategies that ensure the benefits of LLM-driven innovations are realized without compromising user wellbeing.

Organisation(s)

Human-Computer Interaction Section  

External Organisation(s)

Bentley University
University of British Columbia
Eindhoven University of Technology (TU/e)
IBM Research

Type

Conference contribution

Pages

1-6

Publication date

07.07.2025

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Human-Computer Interaction, Software

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.1145/3719160.3728628 (Access: Closed)