Tracing Generative AI in Digital Art: A Longitudinal Study of Chinese Painters' Attitudes, Practices, and Identity Negotiation

TL;DR

This longitudinal study explores how Chinese digital painters' attitudes and practices towards generative AI evolved over five years, revealing a shift from resistance to reflective integration amid ongoing identity and value negotiations.

Contribution

It provides rare longitudinal empirical data and introduces a theoretical framework of identity and value negotiation in the context of AI in digital art.

Findings

Shift from resistance to pragmatic adoption of AI

Persistent concerns about copyright and labor

Emotional and peer influences shape attitudes

Abstract

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.