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User Interaction for Human–AI Interaction and Collaboration
Wu Dan (Wuhan University), Qingyue Guo
Résumé : It is of great importance to integrate human-centered design concepts at the core of both algorithmic research and the implementation of applications. In order to do so, it is essential to gain an understanding of human–computer interaction and collaboration from the perspective of the user. To address this issue, this chapter initially presents a description of the process of human–AI interaction and collaboration, and subsequently proposes a theoretical framework for it. In accordance with this framework, the current research hotspots are identified in terms of interaction quality and interaction mode. Among these topics, user mental modeling, interpretable AI, trust, and anthropomorphism are currently the subject of academic interest with regard to interaction quality. The level of interaction mode encompasses a range of topics, including interaction paradigms, role assignment, interaction boundaries, and interaction ethics. To further advance the related research, this chapter identifies three areas for future exploration: cognitive frameworks about Human–AI Interaction, adaptive learning, and the complementary strengths of humans and AI.