6 papers
What Makes an AI Writing Companion a Good Fit? A Personality-Informed Co-Design Study
Mengke Wu, Kexin Quan, Weizi Liu +2
The growing popularity of AI writing assistants creates exciting opportunities to support diverse writers. This study examines how personality shapes expectations for AI writing co…
Rethinking User Empowerment in AI Recommender System: Innovating Transparent and Controllable Interfaces
Mengke Wu, Weizi Liu, Yanyun Wang +2
AI-driven recommender systems are often perceived as personalization black boxes, limiting users' ability to understand how their data shapes content (information asymmetry) or to…
Revisiting Trust in the Era of Generative AI: Factorial Structure and Latent Profiles
Haocan Sun, Weizi Liu, Di Wu +2
Trust is one of the most important factors shaping whether and how people adopt and rely on artificial intelligence (AI). Yet most existing studies measure trust in terms of functi…
Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use
Haocan Sun, Di Wu, Weizi Liu +2
Concerns over the potential over-pathologization of generative AI (GenAI) use and the lack of conceptual clarity surrounding GenAI addiction call for empirical tools and theoretica…
"Pragmatic Tools or Empowering Friends?" Discovering and Co-Designing Personality-Aligned AI Writing Companions
Mengke Wu, Kexin Quan, Weizi Liu +2
The growing popularity of AI writing assistants presents exciting opportunities to craft tools that cater to diverse user needs. This study explores how personality shapes preferen…
Negotiating the Shared Agency between Humans & AI in the Recommender System
Mengke Wu, Weizi Liu, Yanyun Wang +1
Smart recommendation algorithms have revolutionized content delivery and improved efficiency across various domains. However, concerns about user agency arise from the algorithms'…