As the federal government considers spending tens of billions of dollars to counter China and boost U.S. “critical technologies” like artificial intelligence, advocates have all but ignored perhaps the easiest and most cost‐effective way to do both: substantially expanding immigration. New research from economist Gordon Hanson shows just how effective the policy could be (emphasis mine):
I examine the specialization of US commuting zones in AI‐related occupations over the 2000 to 2018 period. I define AI‐related jobs based on keywords in Census occupational titles. Using the approach in Lin (2011) to identify new work, I measure job growth related to AI by weighting employment growth in AI‐related occupations by the share of job titles in these occupations that were added after 1990. Overall, regional specialization in AI‐related activities mirrors that of regional specialization in IT. However, foreign‐born and native‐born workers within the sector tend to cluster in different locations. Whereas specialization of the foreign‐born in AI‐related jobs is strongest in high‐tech hubs with a preponderance of private‐sector employment, native‐born specialization in AI‐related jobs is strongest in centers for military and space‐related research. Nationally, foreign‐born workers account for 55% of job growth in AI‐related occupations since 2000. In regression analysis, I find that US commuting zones exposed to a larger increases in the supply of college‐educated immigrants became more specialized in AI‐related occupations and that this increased specialization was due entirely to the employment of the foreign born. My results suggest that access to highly skilled workers constrains AI‐related job growth and that immigration of the college‐educated helps relax this constraint.
Based on his findings, Hanson concludes that U.S. immigration restrictions effectively deter the development of AI in the United States: “access to high‐skilled immigration relaxes the talent constraint that limits the expansion of AI. The US government, by regulating the volume and composition of high‐skilled labor inflows from abroad, in effect regulates the pace of growth in AI.” This “regulation,” in turn, will greatly affect whether the United States’ market‐based model for developing AI has an “advantage” over China’s state‐directed approach.
Other recent research on AI and U.S. immigration policy comes to similar conclusions:
Countries all over the world are vying for limited AI talent and implementing transparent, straightforward immigration pathways to attract them. Without a similar system, the United States will fall behind. America can no longer rely on only its reputation for stellar research programs and top‐ranking companies to attract the best talent. If it is too difficult to work, stay, and put down roots in the United States, AI professionals will go elsewhere. With AI so inextricably linked with both future economic and national security advances, the stakes are high.
As I’ve noted previously, immigration has also been found to be similarly essential for semiconductors — another “critical technology” that federal officials now want to subsidize — and for U.S. innovation more broadly. Unfortunately, U.S. tech and China policy today is heavy on subsidies and top‐down planning and light (at best) on immigration liberalization and other market‐oriented policies that have been shown to boost U.S. innovation and economic growth.
U.S. officials thus appear more eager to copy Chinese policy than to effectively counter it.