Contrary to common Western assumptions, China's official AI blueprint focuses on practical applications like scientific discovery and industrial transformation, with no mention of AGI or superintelligence. This suggests a more grounded, cautious approach aimed at boosting the real economy rather than winning a speculative tech race.

In China, mayors and governors are promoted based on their ability to meet national priorities. As AI safety becomes a central government goal, these local leaders are now incentivized to create experimental zones and novel regulatory approaches, driving bottom-up policy innovation that can later be adopted nationally.

Leaders must resist the temptation to deploy the most powerful AI model simply for a competitive edge. The primary strategic question for any AI initiative should be defining the necessary level of trustworthiness for its specific task and establishing who is accountable if it fails, before deployment begins.

In China, academics have significant influence on policymaking, partly due to a cultural tradition that highly values scholars. Experts deeply concerned about existential AI risks have briefed the highest levels of government, suggesting that policy may be less susceptible to capture by commercial tech interests compared to the West.

The argument that the U.S. must race to build superintelligence before China is flawed. The Chinese Communist Party's primary goal is control. An uncontrollable AI poses a direct existential threat to their power, making them more likely to heavily regulate or halt its development rather than recklessly pursue it.

China remains committed to open-weight models, seeing them as beneficial for innovation. Its primary safety strategy is to remove hazardous knowledge (e.g., bioweapons information) from the training data itself. This makes the public model inherently safer, rather than relying solely on post-training refusal mechanisms that can be circumvented.

A fundamental tension within OpenAI's board was the catch-22 of safety. While some advocated for slowing down, others argued that being too cautious would allow a less scrupulous competitor to achieve AGI first, creating an even greater safety risk for humanity. This paradox fueled internal conflict and justified a rapid development pace.

For Chinese policymakers, AI is more than a productivity tool; it represents a crucial opportunity to escape the middle-income trap. They are betting that leadership in AI can fuel the innovation needed to transition from a labor-intensive economy to a developed one, avoiding the stagnation that has plagued other emerging markets.

An FDA-style regulatory model would force AI companies to make a quantitative safety case for their models before deployment. This shifts the burden of proof from regulators to creators, creating powerful financial incentives for labs to invest heavily in safety research, much like pharmaceutical companies invest in clinical trials.