The Reversed Value of Human Authenticity in the AI Era, as Revealed by "Gyūrai"

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The Chinese self-produced animation “Gyūrai” has sparked an unusual viral phenomenon on TikTok (Douyin). Its rough modeling, clumsy character movements, and technically immature camera work. Paradoxically, these “flaws” captured viewers’ attention, leading to the spread of derivative works and memes. According to a report by Huxiu.com’s AIGC 0-to-1, a different perspective eventually began appearing in the comment sections: “Sure, it doesn’t look good, but you can tell someone actually finished making this.” Exact figures for production costs, box office revenue, and the main creative staff’s backgrounds are still awaiting verification. However, this phenomenon starkly highlights the issue of how traces of human creation are being re-evaluated in the era of ubiquitous AI-generated content.

The Perception of Human Authenticity Born

from Roughness

“Living human authenticity” is fundamentally different from imitating sloppiness. Attempts to create a human touch by using hand-drawn style filters, intentionally adding noise, or deliberately mixing unnaturalness into AI footage often provoke discomfort in viewers. True “living human authenticity” stems from the choices and sacrifices within the work, the hesitation that couldn’t be hidden, and the motivation of a specific person who was determined to see it through. Viewers are not aware of the entire production process. However, from the unevenness of the image, the relentless narration, and the obsession with certain details, they perceive the presence of a real human being.

The dissemination process of “Gyūrai” illustrates this point. Initially viewed with the curiosity of “what is this?”, it later transformed into “an object worthy of explanation.” When viewers recognized it as a long-term, self-produced effort by a small team, the interpretation of elements initially deemed flaws shifted. The choppiness became a trace left by the limits of ability, and the unnatural camera work evoked continuous effort in an area of weakness. Huxiu.com’s article described this phenomenon: “The rough handiwork beat the fake AI, and humanity scored another point with sincerity.”

The Severed Result Value and Provenance

Value by AI

Artistic value originally incorporated the attribute of “provenance.” A genuine Van Gogh painting and its pixel-perfect reproduction are visually similar, but their market values are vastly different. Collectors are purchasing not just color and brushstrokes, but also the era, the person, and the irreplicable creative relationship. Before AI, visual results, human labor, and authorial intent were bound together as a triad. Generative AI has severed this trinity. While results are obtained instantly and labor is drastically compressed, authorial intent doesn’t automatically vanish; instead, it becomes something viewers wish to confirm more strongly.

Existing psychological experiments support this trend. Even when subjects cannot stably distinguish visually between AI images and human works, learning that a work is AI-generated leads to downward revisions in assessments of skill, creativity, and value. Viewers are not merely buying a picture; they are simultaneously buying “who accomplished it, why it was made, and what meaning it holds for whom.” As AI becomes capable of providing visual results of ever-higher quality at lower cost, the process is emerging as a key differentiator.

As symbolized by Meta’s announcement of its free AI image generation model Muse, the capabilities of generative AI are advancing daily. Meta Announces Free AI Image Generation Model Muse. The more the homogenization of visual results progresses, the rarer the traces of human judgment and choice behind them become.

The Three Accounts Mixed in “No AI”

The “No AI” claim should not be dismissed as a mere emotional backlash against technology by creators. According to Huxiu.com’s analysis, this movement is underpinned by the intermingling of three distinct problems: aesthetic, labor, and rights.

From the aesthetic account perspective, the crucial factor is whether human creative intent exists in the work, not the tools used. Photography, generative art, ready-mades, and algorithmic art are all examples where the artist doesn’t decide every pixel directly, yet can possess strong authorship. The issue isn’t “whether AI has a soul,” but whether there is a worthy human intent behind the work, whether materials were selected and decisions were made, and whether responsibility was taken for the final expression.

From the labor account perspective, the concerns are more concrete. Citing recent surveys by British creator groups and the illustration industry, Huxiu.com points to notable increases in canceled orders, reduced compensation, and worsening income prospects. After major stock image sites began accepting AI images, total supply and transaction volume increased, but the production, sales, and active creators of non-AI images simultaneously decreased. While the overall market expanded, a structural reshuffling is underway where some existing producers are being marginalized.

The core of the rights account boils down to the issues of training data consent and revenue distribution. Mixing these three accounts into the single question “Is AI art?” blurs the unique scope of each issue and makes constructive consensus-building difficult.

The Layered Structure of the Visual

Production Market Restructured by AI

The proliferation of AI has the potential to restructure the visual production market into three layers. First, the result-oriented synthetic visuals market. AI will dominate areas prioritizing visual effects, such as advertising banners, eye-catching images, and product photo substitutes. Second, the hybrid production market. In this domain combining human judgment with AI’s generative capabilities, scarcity will shift to human taste and discernment. Third, the handcrafted niche market. Works with clear human provenance will stand as independent labels, where the process itself becomes part of the value.

These layers are expected to coexist in the long term. The more AI raises results above a passable standard, the more important the process becomes as a differentiator. Not everyone will pay for the process, but more people will do so. The viral spread of “Gyūrai” can be considered one case study illustrating the initial stage of this market restructuring.

Editorial Opinion

Short-term Impact The spread of “Gyūrai” suggests platform algorithms may begin to favor “content with human traces” over “perfectly generated AI artifacts.” Over the next 3-6 months, video platforms like TikTok may see trends expand that intentionally create a “handcrafted feel” to counter AI homogenization. However, this will also increase AI content mimicking real human labor, further blurring the line between authentic and artificial. Long-term Perspective Over a 1-3 year span, a “provenance certification” mechanism may emerge in the content market. Alongside the proliferation of technical means (such as C2PA metadata standards) to distinguish AI-generated works from human-made ones, a market where the guarantee “this work was made by a person” itself holds commercial value seems poised to mature. The three-layer market structure pointed out by Huxiu.com will fundamentally change creators’ revenue models. Question from the Editorial Team The core question is: until when will “living human authenticity” retain its scarcity?

References

• ” 《牛来》出圈：AI 越会生成，“活人感”为何越值钱 ”, by AIGC从0到1 — 虎嗅网, 2026-08-15T20:18:28.000Z (ARR)
• Source URL: https://www.huxiu.com/article/4883406.html?f=rss