Authors: Nicholas Davis, Chih-Pin Hsiao, Kunwar Yashraj Singh, Lisa Li, Sanat Moningi, Brian Magerko
Paper Abstract: "This paper describes a co-creative web-based drawing application called the Drawing Apprentice. This system collaborates with users in real time abstract drawing. We describe the theory, interaction design, and user experience of the Drawing Apprentice system. We evaluate the system with formative user studies and expert evaluations from a juried art competition in which a Drawing Apprentice submission won the code-based art category." (Davis et al., 2015)
Davis, N., Hsiao, C. P., Singh, K. Y., Li, L., Moningi, S., & Magerko, B. (2015, June). Drawing apprentice: An enactive co-creative agent for artistic collaboration. In Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition (pp. 185-186).
Authors: Yuyu Lin, Jiahao Guo, Yang Chen, Cheng Yao, Fangtian Ying
Paper Abstract: "Co-creative systems have been widely explored in the field of computational creativity. However, existing AI partners of these systems are mostly virtual agents. As sketching on paper with embodied robots could be more engaging for designers’ early-stage ideation and collaborative practices, we envision the possibility of Cobbie, a mobile robot that ideates iteratively with designers by generating creative and diverse sketches. To evaluate the differences in co-creativity and user experience between the co-creative robots and virtual agents, we conducted a comparative experiment and analyzed the data collected from quantitative scales, observation, and semi-structured interview. The results reveal that Cobbie is more satisfying in motivating exploration, provoking unexpected ideas and engaging designers in the collaborative ideation process. Based on these findings, we discussed the prospects of co-creative robots for future developments of human-AI collaborative systems." (Lin et al., 2020)
Lin, Y., Guo, J., Chen, Y., Yao, C., & Ying, F. (2020, April). It is your turn: collaborative ideation with a co-creative robot through sketch. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-14).
Authors: Changhoon Oh, Jungwoo Song, Jinhan Choi, Seonghyeon Kim, Sungwoo Lee, Bongwon Suh
Paper Abstract: "Recent advances in artificial intelligence (AI) have increased the opportunities for users to interact with the technology. Now, users can even collaborate with AI in creative activities such as art. To understand the user experience in this new user– AI collaboration, we designed a prototype, DuetDraw, an AI interface that allows users and the AI agent to draw pictures collaboratively. We conducted a user study employing both quantitative and qualitative methods. Thirty participants per- formed a series of drawing tasks with the think-aloud method, followed by post-hoc surveys and interviews. Our findings are as follows: (1) Users were significantly more content with DuetDraw when the tool gave detailed instructions. (2) While users always wanted to lead the task, they also wanted the AI to explain its intentions but only when the users wanted it to do so. (3) Although users rated the AI relatively low in predictability, controllability, and comprehensibility, they en- joyed their interactions with it during the task. Based on these findings, we discuss implications for user interfaces where users can collaborate with AI in creative works." (Oh et al., 2018)
Oh, C., Song, J., Choi, J., Kim, S., Lee, S., & Suh, B. (2018, April). I lead, you help but only with enough details: Understanding user experience of co-creation with artificial intelligence. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-13).
Authors: Zhang, C., Yao, C., Liu, J., Zhou, Z., Zhang, W., Liu, L. et al.
Paper Abstract: "Storytelling is a common creative activity for children. During storytelling, children need creative support and are subjected to cognitive challenges. This paper explores a co-creative agent - StoryDrawer, which supports children in creating oral stories through collaborative drawing. StoryDrawer works with children in two strategies: Child says and AI draws; and Child scribbles and AI completes. These two collaborative strategies allow children to draw their stories as an externalization and provoke unexpected ideas. This paper presents the interaction design, collaborative strategies and implementation of StoryDrawer, and conducts a user study for the fun and task effectiveness of StoryDrawer. The results reveal that our system can encourage children's active participation in storytelling and help them create novel stories through human-computer collaboration." (Zhang et al., 2021)
Zhang, C., Yao, C., Liu, J., Zhou, Z., Zhang, W., Liu, L., ... & Wang, G. (2021, May). StoryDrawer: A Co-Creative Agent Supporting Children's Storytelling through Collaborative Drawing. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-6).