Chinese content platforms are taking action to regulate the mechanized content production that is traffic-oriented and ignores authenticity and informational value.
Zhuo Wei'an
Recently, a popular story widely circulated on Chinese social media claimed that a couple used generative AI to mass-produce WeChat articles, earning an annual income of up to 2 million yuan (approximately 293,000 USD). The appeal of this story lies in its extremely simplified narrative: low investment, high returns, seemingly an effortless shortcut to making money.
However, within just a few days, this narrative encountered a more realistic twist: Tencent (0700.HK) has banned accounts related to such operations.
Tencent did not view this incident as a single violation case but rather as an issue to be addressed at the regulatory level. The company issued a statement through official channels, clearly proposing a principle that is rapidly becoming a consensus in China's content governance: AI can assist in creation but cannot replace humans.
There is a deep-seated concern among content platforms: if generative AI lacks regulation, it will lead to a surge of homogenized, low-value content, further eroding user trust and diminishing the survival space for original authors.
Tencent's action appears more like a preventive measure against online abuse. Its focus is not on the technology itself but on the potential for this technology to give rise to what is called &#34;content industrialization,&#34; which refers to the mechanized production of articles driven by the pursuit of traffic rather than authenticity and insight.
This phenomenon is not new. The Chinese internet ecosystem has already gone through multiple waves of content monetization, from clickbait to the endless rewriting of &#34;pseudo-original&#34; content. However, generative AI brings about a qualitative change: content production that previously required human collaboration can now be rapidly achieved by algorithms at a very low cost.
The result may be a flood of homogenized content. Articles may have different surface wording, but their essential content is similar, flooding the information streams of major platforms. In such an environment, differentiation becomes difficult, and the informational value of content rapidly declines.
In addition to Tencent, Xiaohongshu is also tightening its regulation on AI-generated content, especially taking a stricter stance on commercial promotion-related content.
Xiaohongshu has released relevant guidelines emphasizing content authenticity and information disclosure, explicitly prohibiting the use of AI to fabricate user experiences, such as generating product reviews without actual exposure. Enforcement is not merely formal; violations have been taken down, and repeat offenders have faced penalties.
It is noteworthy that there is a high degree of consistency in the underlying logic across platforms. The issue is not with AI itself but with its use as a tool to confuse and mislead, where automated generation is packaged as human creation, and large-scale production comes at the expense of content quality.
In other words, Chinese platforms are gradually forming a consensus: AI can serve as an auxiliary tool but cannot be used as a means of confusion and deception.
In contrast, across the ocean, the regulatory atmosphere is much more relaxed, even somewhat encouraging. Meta has fully integrated generative AI functions into its ecosystem, including Instagram, where AI-assisted creation is gradually becoming the norm. Meanwhile, the X platform has also become an important testing ground for AI-native content, with everything from synthetic posts to algorithm-generated images becoming increasingly popular
This reflects a highly competitive, interaction-oriented market environment where platforms are motivated to lower the barriers to creation and increase the speed of content output. In this framework, AI is less of a risk to be guarded against and more of an accelerator to be leveraged.
However, Western platforms do not completely ignore the associated risks. Labeling policies for AI-generated content, especially in the political and advertising fields, are gradually being established. But overall implementation remains relatively fragmented, with high entry barriers.
Therefore, the difference between the two sides lies not in whether they recognize the issues, but in their strategic choices: Chinese platforms tend to impose preemptive limits, while Western platforms lean more towards inclusivity and adaptation.
Ultimately, the debate surrounding AI content governance is essentially a question of &#34;information effectiveness.&#34; In an era where content production is no longer restricted, what constitutes truly valuable content?
Chinese platforms tend to emphasize the informational density and authenticity of content, attempting to limit any practices that undermine these two aspects; in contrast, Western platforms allow for more diversity, prioritizing interaction data and creative plurality.
Both models come with costs; excessive restrictions may stifle innovation, while excessive leniency may lower content quality. The key is to find a line that is neither overly restrictive nor overly permissive.
Amid these differences, a set of preliminary principles is gradually taking shape.
First, AI-native content itself is not the problem. Incorporating AI into content creation is an inevitable trend and has positive implications in many respects. It expands creative tools and lowers entry barriers. A complete ban on AI-generated content is not only unrealistic but counterproductive.
Second, platforms should not suppress AI but should guard against its misuse. Platforms have a responsibility to curb behaviors such as &#34;content rewriting&#34; using AI. The focus should not be on regulating the creation itself but on preventing content quality from being eroded by industrialized operations.
Third, transparency and originality are non-negotiable. Promoting AI-assisted creation must be based on clear labeling and substantial human judgment involvement. Labeling AI-generated content is not just a compliance requirement but a key mechanism for maintaining trust among creators, platforms, and users. At the same time, platforms must continue to encourage original thinking, ensuring that the human perspective remains at the core of value creation.
From this perspective, Tencent's recent actions can be seen not merely as a single enforcement action but as a barometer. It reflects a growing consensus within the industry: the future form of content will neither be completely human-led nor entirely machine-dependent, but rather a balanced integration of both.
This article represents the author's personal views and does not reflect the views of Yongzhu Fang.
Zhu Wei'an, a reporter based in Singapore, focuses on technology reporting and is also a co-founder of the tech media startup Tech Tech China. Her contact information: vivian_toh@techtechchina.com
This article was originally published in China Bizz Buzz

Chinese content platforms are cracking down on AI-generated content that is traffic-oriented and disregards authenticity. Tencent has banned related accounts, emphasizing that AI should assist in creation rather than replace humans, to prevent content homogenization and a decline in user trust. Xiaohongshu has also strengthened regulation, prohibiting AI content that fabricates user experiences. Various platforms are demonstrating consistency in content governance, aiming to maintain the authenticity and value of content

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