2026 - present

Generative AI systems are increasingly embedded in our daily lives. However, current human-AI interaction is designed primarily around optimizing for productivity and efficiency, leaving users as passive consumers of AI-produced content. This dynamic has been shown to erode critical thinking, reduce creative diversity, and foster over-reliance on AI-generated outputs. In this project, we propose Human-AI Co-Interpretation Interaction as a new interaction model that repositions AI as a resource for expanding human thought. Rather than designing AI systems that strive to deliver definitive answers, we center on the human reinterpretation of AI outputs in the user’s own way, foregrounding the user’s own meaning-making as the core value of the interaction.

To ground this model, we draw on generative AI’s inherent variability, its probabilistic nature produces unexpected, open-ended outputs that defamiliarize the familiar, invite multiple interpretive angles, and leave room for users to reason and imagine beyond what the system explicitly provides. We explore Human-AI Co-Interpretation Interaction across three application domains: personal informatics, creativity support tools, and everyday smart objects. Through this project, we aim to develop a conceptual framework and design guidelines for AI systems based on co-interpretation, ultimately building toward interactions that enhance rather than diminish users’ critical, reflective and creative capacities.

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