Design, Development, and Deployment of Context-Adaptive AI Systems for Enhanced User Adoption

Published in CHI EA 24: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems, 2024

Recommended citation: Christine P. Lee. 2024. Design, Development, and Deployment of Context-Adaptive AI Systems for Enhanced User Adoption. In Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems (CHI EA 24). Association for Computing Machinery, New York, NY, USA, Article 429, 1–5.

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Abstract: My research centers on the development of context-adaptive AI systems to improve end-user adoption through the integration of technical methods. I deploy these AI systems across various interaction modalities, including user interfaces and embodied agents like robots, to expand their practical applicability. My research unfolds in three key stages: design, development, and deployment. In the design phase, user-centered approaches were used to understand user experiences with AI systems and create design tools for user participation in crafting AI explanations. In the ongoing development stage, a safety-guaranteed AI system for a robot agent was created to automatically provide adaptive solutions and explanations for unforeseen scenarios. The next steps will involve the implementation and evaluation of context-adaptive AI systems in various interaction forms. I seek to prioritize human needs in technology development, creating AI systems that tangibly benefit end-users in real-world applications and enhance interaction experiences.