While the Tiaolouji incident brought AI and human performers into direct comparison, it’s important to remember that AI-singing is never fully autonomous — it is, at its core, a collaborative process. Every AI-Singing is shaped by the creative labor of a human trainer who collects vocal datasets, fine-tunes voice models, experiments with emotional delivery, and refines the musical output. Human and AI actors co-create these performances, and it is this collaboration that enables AI-singing to thrive as a participatory, remix-based phenomenon on platforms like Bilibili.

Yet once these co-produced voices enter the public sphere, the framing often shifts from collaboration to competition. In the Tiaolouji case, public discourse focused less on the creative process and more on who “performed better” — the original V-Tuber or her AI-generated double. This shift exposes underlying tensions around authorship, recognition, and economic value, particularly in the context of digital creators whose voices are central to their marketability and professional identity. For performers like Dongxuelian, vocal performance is not just artistic expression — it is integral to their visibility, branding, and income in a platform-based economy.

This contrasts with other uses of AI-generated voice, such as in navigation systems. For example, Gaode Map ( a Chinese software) has invited celebrities to "lend" their voices to AI navigators — and many embrace the opportunity. These collaborations are seen not as threats, but as brand extensions that enhance their visibility.