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Making money in Chinese AI safety

Jordan Schneider uncovers a hidden economy where the most valuable commodity isn't code, but the ability to navigate a labyrinthine government approval process. While Western observers often debate the philosophical merits of AI safety, Schneider reveals a pragmatic marketplace in China where safety is a mandatory, billable service required to launch any product with "public opinion attributes."

The Compliance Marketplace

Schneider begins by dismantling the assumption that regulatory hurdles are merely bureaucratic noise. He notes that any company deploying generative AI with "public opinion attributes or social mobilization capabilities" must file with the Cyberspace Administration of China. The requirements are staggering: a 100+ page safety assessment report and a keyword interception list of at least 10,000 blocked terms. "The CAC doesn't distinguish between billion-dollar incumbents and five-person founding teams; all these different players have to navigate the same compliance maze," Schneider writes. This observation is crucial because it highlights how the state's rigid framework inadvertently creates a massive service industry for intermediaries.

Making money in Chinese AI safety

The author's investigation into the "Taobao Method" is particularly revealing. By searching for "AI evaluation testing" on China's largest e-commerce platform, Schneider found a cottage industry of vendors selling compliance services for as little as $1.30, though actual costs for full generative AI filings range from $2,000 to $11,000. "We are responsible for writing the materials for the large-scale model registration, while you are responsible for optimizing the model," one vendor told him, promising a full refund if the application fails. This dynamic creates a unique economic reality where safety is not an ethical choice but a transactional necessity. The author effectively illustrates how the regulatory bottleneck forces startups to outsource their relationship with the state, turning compliance into a distinct line item on a balance sheet.

Critics might argue that this system prioritizes ideological alignment over genuine technical safety, but Schneider's point stands: the market has adapted to the state's demands with remarkable efficiency. The existence of these vendors proves that the regulatory regime is not just a barrier, but a driver of a specific type of commercial activity.

In AI terms, that kind of delay can feel like an eternity, with your hot product today facing the risk of becoming obsolete.

From Paperwork to Infrastructure

The commentary shifts from the "Taobao" vendors to formal third-party safety firms like RealAI and BotSmart, which offer more than just paperwork. These companies are building end-to-end safety infrastructure, including adversarial testing and "ideological alignment" checks. Schneider notes that while Western safety vendors often rely on voluntary demand or philanthropic grants, the Chinese market is "policy-driven." He cites a white paper from BotSmart projecting the market to reach 242 billion yuan by 2028, driven by the principle of "mandatory review before launch."

This distinction is the article's most significant contribution to the global discourse. "In the West, governance vendors... help enterprises document risk and prepare for frameworks like the EU AI Act," Schneider explains, contrasting this with China where "safety and technological progress as opposing forces" is a tension far less pronounced. The author argues that in China, the state sets the terms, removing the friction between safety advocates and industry progress. This framing challenges the Western narrative that safety regulations inherently stifle innovation; instead, Schneider shows how a clear, albeit rigid, regulatory path can create a predictable business environment for safety services.

However, the author acknowledges a potential flaw in this growth trajectory. The reliance on political content control means that "deeper" safety concerns, such as chemical or biological misuse (CBRN), are often overlooked. "If that posture continues, demand for 'deeper' safety services may remain limited," Schneider warns. This is a vital counterpoint: the market is booming, but it may be solving the wrong problems by Western standards, focusing on political stability rather than existential risk.

The Agent Question and Future Risks

As the piece concludes, Schneider turns to the rise of agentic AI, noting that these more autonomous systems currently lack a dedicated national regulatory regime. This creates a potential blind spot. While the current system handles text generation well, the shift toward agents that can take actions in the real world may strain the existing framework. The author suggests that the current focus on "public opinion attributes" might not be sufficient for the next generation of AI capabilities.

The article's strength lies in its refusal to moralize the Chinese approach. Instead, it treats the safety industry as a rational response to a specific set of constraints. "Safety becomes not just best practice, but a prerequisite for launch," Schneider writes, summarizing the core dynamic. This clarity is refreshing in a field often clouded by ideological posturing. The author successfully demonstrates that while the motivations behind Chinese AI safety differ from the West, the resulting market dynamics are equally complex and commercially significant.

The Interim Measures for the Management of Generative Artificial Intelligence Services establish a principle of "mandatory review before launch," turning AI security into a rigid, unavoidable requirement for companies.

Bottom Line

Schneider's most compelling argument is that China has successfully monetized regulatory compliance, creating a safety industry that is both robust and narrowly focused on state priorities. The piece's greatest vulnerability is its reliance on market projections that assume the regulatory scope will expand to cover technical risks like CBRN, which current enforcement suggests is unlikely. Readers should watch whether the rise of agentic AI forces the Chinese state to broaden its definition of safety beyond political content, potentially unlocking the next phase of this unique market.

Sources

Making money in Chinese AI safety

by Jordan Schneider · ChinaTalk · Read full article

Jordan Schneider uncovers a hidden economy where the most valuable commodity isn't code, but the ability to navigate a labyrinthine government approval process. While Western observers often debate the philosophical merits of AI safety, Schneider reveals a pragmatic marketplace in China where safety is a mandatory, billable service required to launch any product with "public opinion attributes."

The Compliance Marketplace.

Schneider begins by dismantling the assumption that regulatory hurdles are merely bureaucratic noise. He notes that any company deploying generative AI with "public opinion attributes or social mobilization capabilities" must file with the Cyberspace Administration of China. The requirements are staggering: a 100+ page safety assessment report and a keyword interception list of at least 10,000 blocked terms. "The CAC doesn't distinguish between billion-dollar incumbents and five-person founding teams; all these different players have to navigate the same compliance maze," Schneider writes. This observation is crucial because it highlights how the state's rigid framework inadvertently creates a massive service industry for intermediaries.

The author's investigation into the "Taobao Method" is particularly revealing. By searching for "AI evaluation testing" on China's largest e-commerce platform, Schneider found a cottage industry of vendors selling compliance services for as little as $1.30, though actual costs for full generative AI filings range from $2,000 to $11,000. "We are responsible for writing the materials for the large-scale model registration, while you are responsible for optimizing the model," one vendor told him, promising a full refund if the application fails. This dynamic creates a unique economic reality where safety is not an ethical choice but a transactional necessity. The author effectively illustrates how the regulatory bottleneck forces startups to outsource their relationship with the state, turning compliance into a distinct line item on a balance sheet.

Critics might argue that this system prioritizes ideological alignment over genuine technical safety, but Schneider's point stands: the market has adapted to the state's demands with remarkable efficiency. The existence of these vendors proves that the regulatory regime is not just a barrier, but a driver of a specific type of commercial activity.

In AI terms, that kind of delay can feel like an eternity, with your hot product today facing the risk of becoming obsolete.

From Paperwork to Infrastructure.

The commentary shifts from the "Taobao" vendors to formal third-party safety firms like RealAI and BotSmart, which offer more than just paperwork. These companies are building end-to-end safety infrastructure, including adversarial ...