Tracing Generative AI in Digital Art: A Longitudinal Study of Chinese Painters' Attitudes, Practices, and Identity Negotiation
It addresses how digital artists negotiate identity and values in response to AI, offering empirical data and theoretical insights for human-AI collaboration, but is incremental in its focus on a specific cultural context.
This study tracked 17 Chinese digital painters over five years to understand their evolving attitudes and practices with generative AI, revealing a shift from resistance to pragmatic adoption and reflective reconstruction, influenced by peer pressures and emotional changes.
This study presents a five-year longitudinal mixed-methods study of 17 Chinese digital painters, examining how their attitudes and practices evolved in response to generative AI. Our findings reveal a trajectory from resistance and defensiveness, to pragmatic adoption, and ultimately to reflective reconstruction, shaped by strong peer pressures and shifting emotional experiences. Persistent concerns around copyright and creative labor highlight the ongoing negotiation of identity and values. This work contributes by offering rare longitudinal empirical data, advancing a theoretical lens of "identity and value negotiation," and providing design implications for future human-AI collaborative systems.