Doctoral candidate Qingxiao Zheng successfully defended her dissertation, "Shifting Paradigms in the UX Evaluation of Human-AI Interaction: From Dyadic to Monadic Designs," on May 27.
Her committee included Associate Professor Yun Huang (chair); Mike Yao, professor at the Institute of Communications Research; Associate Professor Yang Wang; and Assistant Professor Nigel Bosch.
Abstract: This dissertation identifies a paradigm shift in the UX evaluation of human-AI interaction. Prior to generative AI, UX research began with examining dyadic interactions between end users and AI, progressively expanding to polyadic interactions, where AI mediates between end users adopting multi-stakeholder perspectives. With generative AI, individuals with minimal AI literacy can become creators, introducing a new modality–monadic interaction–which emphasizes the unity and feedback loop between AI and their users. These users actively participate in defining and refining the AI's functions, allowing both to adapt and evolve. Although humans and AI systems can leverage their respective strengths to achieve better outcomes than either could independently, assessing how well AI aligns with users' values and intentions poses significant challenges, particularly when users' norms deviate from broader societal standards. This dissertation further introduces a UX evaluation framework, called EvalignUX (evaluating alignment of UX), designed to guide the evaluation of the three interaction modalities. The proposed EvalignUX framework can assist UX researchers and design tool makers in addressing the challenges of evaluating AI systems in a responsive fashion.