Open Questions | Jeffrey Ding on why diffusion, not innovation, is the secret to victory in the AI race

Jeffrey Ding is an assistant professor of political science at George Washington University. He is the author of Technology and the Rise of Great Powers, an award-winning book exploring the impact of technology on geopolitical competition, as well as the founder of the ChinAI newsletter, which tracks developments in China’s artificial intelligence (AI) industry.

In this interview, Ding explains why “diffusion”, not innovation, will determine whether China or the US will prevail in the AI race, the Trump administration’s “counterproductive” policies around the technology, misconceptions about the two countries’ respective strengths in the field and why human capital is the key to victory.

You recently wrote an article for Rand Corporation, the influential US think tank, in which you argued that the US is “training for the wrong race” in AI. What did you mean?

The main reason I wrote that piece was to clarify what I see as a lot of confusion out there about what the US and China are actually competing for in AI. Others have already articulated different visions of this US-China AI race, but I wanted to put forth clearly that there is one type of race that I think the US should optimise for, which is this “diffusion marathon” rather than a sprint towards a clear finish line.

The “diffusion marathon” refers to the progress the two countries make in spreading AI throughout their respective economies.

This can be contrasted with a vision of the AI race as an “innovation sprint” – the view of many in US national security circles – where the key question is which country can innovate its way to developing an artificial general intelligence (AGI) with “God-like powers”, in the words of Jake Sullivan, the National Security Adviser under the Joe Biden administration.