AI Hubs Are Few and Far Between

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A new study warns that the geographic concentration of AI in the United States is making the industry too insular.
What’s new: A report by the Brookings Institution documents the extent to which a few metropolitan areas dominate AI in the U.S., risking group-think, geographic bias, and other pitfalls.
AI Hubs Actual and Potential: The report scores AI research and commercialization in 384 regions based on an analysis of federal grants, research papers, patent filings, job postings, and companies.

  • The San Francisco Bay Area, which comprises San Francisco, Silicon Valley, and adjacent cities, is the undisputed AI capital in the U.S., accounting for one quarter of all papers, patents, and companies.
  • A dozen-plus other cities including Austin, New York, and Seattle dominate the rest. Combined with the Bay Area, they make up two-thirds of the national AI industry.
  • Another 21 cities host universities with strong AI programs, thanks largely to government funding. However, they lack commercial AI activity.
  • The report also spotlights nearly 90 cities with high potential to commercialize AI. These areas are buoyed by startups such as Salt Lake City’s Recursion, a healthcare venture, and large, non-tech firms that are making big investments in automation such as Target in Minneapolis.

Behind the news: The Bay Area’s dominance in AI dates to the late 1950s, when the nascent semiconductor industry spawned what became the modern tech industry. Owing partly to this history, the region hosts a thriving ecosystem of universities, businesses, and financiers that focus on technological innovation.
Why it matters: AI’s lopsided geographic concentration not only undermines demographic and intellectual diversity, it “locks in a winner-take-most dimension to this sector,” Mark Muro, the study’s coauthor, told Wired. This imbalance between risk and reward highlights a need for policy and investment that promotes AI in other parts of the country, he said.
We’re thinking: Other industries are geographically concentrated; for instance entertainment, fashion, and finance. But AI has a special need for a diverse talent pool to ensure that the systems we build are fair and broadly beneficial.

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