CUI@CHI 2024: Building Trust in CUIs-From Design to Deployment
Smit Desai, Christina Wei, Jaisie Sin, Mateusz Dubiel, Nima Zargham, Shashank Ahire, Martin Porcheron, Anastasia Kuzminykh, Minha Lee, Heloisa Candello, Joel Fischer, Cosmin Munteanu, Benjamin R Cowan
TL;DR
This paper outlines a CHI 2024 workshop proposal on Building Trust in CUIs—From Design to Deployment, addressing the paucity of a unified understanding of trust in conversational interfaces across design, evaluation, and deployment. It advocates a multidisciplinary approach to clarify trust concepts, develop design techniques, and establish integrative measurement methods, including XAI and trust calibration, within privacy-sensitive contexts. The workshop combines keynote sessions, breakout activities, and asynchronous engagement to foster cross-domain collaboration and a cohesive research agenda. The practical impact lies in advancing trustworthy CUIs that balance user agency, privacy, and reliability through coordinated research and dissemination efforts, including a planned special journal issue and open-access proceedings.
Abstract
Conversational user interfaces (CUIs) have become an everyday technology for people the world over, as well as a booming area of research. Advances in voice synthesis and the emergence of chatbots powered by large language models (LLMs), notably ChatGPT, have pushed CUIs to the forefront of human-computer interaction (HCI) research and practice. Now that these technologies enable an elemental level of usability and user experience (UX), we must turn our attention to higher-order human factors: trust and reliance. In this workshop, we aim to bring together a multidisciplinary group of researchers and practitioners invested in the next phase of CUI design. Through keynotes, presentations, and breakout sessions, we will share our knowledge, identify cutting-edge resources, and fortify an international network of CUI scholars. In particular, we will engage with the complexity of trust and reliance as attitudes and behaviours that emerge when people interact with conversational agents.
