Human-AI Schema Discovery and Application for Creative Problem Solving
This work addresses the challenge of schema discovery and application for creative problem solving in domains like writing or design, offering incremental improvements in human-AI collaboration.
The research tackled the problem of discovering and applying structural patterns (schemas) for creative tasks by developing a human-AI framework, resulting in systems that help users abstract schemas from examples and use them in co-creative workflows to make implicit knowledge more accessible.
Humans often rely on underlying structural patterns-schemas-to create, whether by writing stories, designing software, or composing music. Schemas help organize ideas and guide exploration, but they are often difficult to discover and apply, especially in complex or unfamiliar domains. My Ph.D. research develops a framework for human-AI schema discovery and application to support creative problem solving. I design systems that support users in sensemaking over examples to abstract schemas, and in operationalizing schemas into human-AI co-creative workflows for application. This research offers insights into how schema-guided interaction can make implicit knowledge more accessible and actionable, advancing more transparent and collaborative human-AI systems.