Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence?

Jennifer Hunt, Iain Cockburn () and James Bessen ()
Additional contact information
Iain Cockburn: Boston University
James Bessen: Boston University

No 17325, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Using our own data on Artificial Intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in U.S. locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs' share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations.

Keywords: Artificial Intelligence; technology adoption and diffusion (search for similar items in EconPapers)
JEL-codes: O33 R12 (search for similar items in EconPapers)
Pages: 73 pages
Date: 2024-09
New Economics Papers: this item is included in nep-ain, nep-cse, nep-geo, nep-ino, nep-lma, nep-sbm, nep-tid and nep-ure
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Related works:
Working Paper: Is distance from innovation a barrier to the adoption of artificial intelligence (2024)
Working Paper: Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence? (2024)
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