Drawing Apprentice: Co-Creative Drawing Partner

Brian Magerko, Ellen Yi-Luen Do
Nicholas Davis, Chih-Pin Hsiao, Kunwar Yashraj Singh, Brenda Lin, Lily Lau, Ricardo Maclas

Collaboration is known to push creative boundaries and help individuals sustain creative engagement, explore a more diverse conceptual space, and synthesize new ideas. While the benefits of human collaboration may seem obvious, the cognitive mechanism and processes involved in open-ended improvisational collaboration are active areas of research. Our research group has developed a co-creative drawing partner called the Drawing Apprentice to investigate creative collaboration in the domain of abstract drawing. The Drawing Apprentice draws with users in real time by analyzing their input lines and responding with lines of its own. With this prototype, we study the interaction dynamics of artistic collaboration and explore how a co-creative agent might be designed to effectively collaborate with both novices and expert artists. The prototype serves as a technical probe to investigate new human-computer interaction concepts in this new domain of human-computer collaboration, such as methods of feedback to facilitate learning and coordination (for both the user and system), turn-taking patterns, and the role control and ambiguity plays in effective collaboration.

Brian Magerko
Jason Freeman, Duri Long
Takeria Blunt, Erin Truesdell, Manoj Deshpande, Sarah Mathew, Atefeh Mahdavi

The Expressive Machinery Lab (formerly ADAM Lab) explores the intersection between cognition, creativity, and computation through the study of creative human endeavors and by building digital media artifacts that represent our findings. Applications of our findings range from AI-based digital performance to interactive narrative experiences to educational media design and development.