| Description | Artificial Intelligence is transforming creative design, but how can we ensure humans remain engaged, empowered, and effective collaborators? This project explores human–AI co-creative systems, focusing on adaptive mixed-initiative tools that present algorithmically generated design suggestions to support creativity and decision-making. Building on recent research into MAP–Elites-driven galleries (see https://dl.acm.org/doi/abs/10.1145/3773292) and engagement metrics, students will investigate one or more of the following:
AI Algorithms: Develop or refine generative and quality-diversity algorithms (e.g., MAP–Elites) to produce diverse, high-quality design suggestions.
Human Evaluation: Design and run user studies to measure cognitive, emotional, and behavioral engagement in collaborative design tasks.
Applications: Apply these ideas to domains such as game design, engineering, or interactive art, creating tools that balance automation with human agency.
Adaptive Interfaces: Explore how systems can learn and adapt to user preferences over time to enhance trust and creativity.
The project offers flexibility: students can focus on algorithmic innovation, user experience research, or application development. Ideal candidates will have interests in AI, HCI, and creative technologies, and will gain experience in machine learning, experimental design, and interactive system development. |
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