The Case for Undoing Biden’s AI Diffusion Rule

Before leaving office, President Biden announced expanded export controls on AI. Unless the Trump Administration rescinds it, this interim final rule will restrict the export of top U.S. AI models and hardware not only to our adversaries but to dozens of our close allies. Affected “Tier 2” countries include Portugal, Switzerland, and Israel, in addition to most of the developing world. Soon, U.S. companies will have to apply for a license from the Bureau of Industry and Security to export leading closed source models and advanced AI hardware to most of the world.

While the internet is relitigating export controls on China as a result of the new DeepSeek model, they’re missing the forest for the trees. The Biden administration put export controls on most countries in the world, most of which are allies. These export controls have much less effect on adversaries like China and much greater costs to Americans.

Map by Bloomberg

This push to restrict AI exports weakens America’s alliances with the developing world at a critical juncture. Developing nations are currently making decisions on AI infrastructure that will have decades-long consequences. Competing for these markets depends not only on having more advanced AI models, but making those models available, customizable, and cheap. With its lead in AI, America is presented with an opportunity to reinforce its diplomatic and economic ties. Instead, these export controls risk surrendering the developing world’s AI infrastructure to China.

An AI provider constrained by this export rule is severely limited in their ability to run and adapt AI models in “Tier 2” countries. The rule restricts both the model weights comprising top AI models and the hardware required to run them locally. Moreover, it substantially increases the regulatory and compliance burden which, in turn, increases the cost of exporting American AI to the Global South. Meanwhile, a Chinese company expanding freely into the developing world can lower its costs, increase R&D spending, and refine its AI models with local feedback.

Competitiveness rests on economies of scale. When fixed costs are high, serving a larger market dramatically lowers the cost per customer. The cost of training AI models is rapidly growing, with GPT4 pre-training costing over 100 million dollars according to OpenAI CEO Sam Altman. The cost of operating trained AI models, known as inference cost, is significantly lower.

China has set a strategic goal to sell to the Global South. They hire local talent, speak the local language, and shape services to reflect local values. Localizing AI models requires rapid feedback loops, updating local models with new information, a process that is severely limited by the restrictions on both weights and hardware. The strongest systems evolve through trial and error in real-world environments. No matter how brilliant the engineers in California are, they cannot iterate effectively if they lack on-the-ground data in Nairobi, Jakarta, or Bogotá, all cities in “Tier 2” countries. Companies that choose to sell directly to these nations learn about their users, gaining feedback in a critical period for AI adoption. They fine-tune systems, adapt pricing structures, and modify user interfaces. By restricting that opportunity, we cut ourselves off from those markets in the long term. Even if American AI models maintain their technical advantages, lack of localization may lead to developing countries choosing Chinese alternatives.

By targeting local cultures in Africa, China built a near-monopoly on critical minerals in the region. China’s strategy for 5G networks has given them a global advantage. Allowing them to do the same for AI will have permanent consequences for the developing world’s security and economic development.

Relying on infrastructure built by adversaries introduces novel security risks. For example, Chinese 5G networking technology may introduce cybersecurity vulnerabilities, enabling Chinese surveillance and infiltration. The same considerations apply to AI. When American firms supply AI infrastructure, they ensure that the AI systems used by American allies are consistently updated to modern cybersecurity standards. Most importantly, they can prevent China from introducing backdoors, which only they are able to access. If America doesn’t provide AI infrastructure, Chinese companies will. By distributing safe and inspected American solutions, we can prevent our allies from becoming dependent on black-box systems from abroad.

Another overlooked advantage of technological exports to the Global South is soft power. When American firms invest in a country’s digital infrastructure, they become part of that nation’s modernization. The norms of their society evolve alongside their technology. They train developers, collaborate with universities, and sponsor research. The local workforce develops skill sets aligned with American standards and tools. Even if governments change, those relationships endure at the commercial and human levels. The new rule on AI exports undermines that possibility, leaving space for China to become the default partner.

What the current export controls get right is making an exemption for open source AI models. Localizing models to countries with fewer economic resources requires making models available, customizable, and cheap. The open source ecosystem excels at all three. Open source AI models reduce barriers to use, modification, and cost-saving optimization. However, China’s open source models are highly competitive with American ones, if not surpassing them. Winning the competition for global AI infrastructure will require making strategic decisions to advance and promote American AI, not hinder it.