How information technology is reshaping economic geography has always been an interesting topic of economics. Richard Florida, a prominent urban economist, recently wrote a review of the BROOKING Institution's Urban Policy Program's AI report, sharing his views on the impact of AI on different cities in the United States.
Written by | Richard Florida
Translate | Chen Zi'an
| for translation Wang Zicheng
Source | Shanghai-Hong Kong Joint Research Institute for Development
Aerial view of Silicon Valley at dusk. The San Francisco Bay Area remains the only dominant player in the field of artificial intelligence in the United States丨 Photography: Smith Collection/Gado/Archive Photos
AI promises to be one of the most important and perhaps most disruptive technologies of our time.
It has penetrated into every aspect of our daily lives, such as: recommendations when searching, and the assisted driving function of teslas. In the future, artificial intelligence may help doctors diagnose and help the development of fully autonomous vehicles. From this perspective, AI is a truly epoch-making advance, considered a "universal technology" like wheels, steam engines, electricity, and modern factory systems.
Quasi-technology is an important force to promote new industries, reshape existing industries, and is also the basis for the rise of the entire new economic system. AI will have a huge economic impact. It is estimated that by 2030, AI will add as much as $15.7 trillion to global economic output. So it's no surprise that the U.S. government is placing AI in a high position on its list of key technologies that affect innovation, economic competitiveness, and national security.
Previously, high-tech industries were concentrated in leading technology hubs and superstar cities in the United States. Ai has the potential to reinforce or amplify this pattern of geographical imbalances. This is the main conclusion of a new study by the Brookings Metro program. The study, led by Mark Muro and Sifan Liu, focused on the geography of AI. They paint a picture of ai's impact in two key ways: (1) university research, including academic publishing, patents, and federal grants and contracts; and (2) commercialization factors such as published job titles and workforce skills. Overall, according to the study, only 10 percent of U.S. metropolitan areas (36) have a significant amount of AI present. The map below is from this study, which identifies five key categories of AI cities and metropolitan areas.
来源：Brookings analysis of Stanford HAI, Crunchbase, STAR METRICS, USPTO, Emsi data
One is the superstar of superstars. The San Francisco Bay Area, which is made up of the San Francisco and San Jose metropolitan areas, is an absolute leader in the field of artificial intelligence in the United States. There are leading academic research centers such as Stanford University and the University of California, Berkeley, and there are a large number of start-ups, such as Alphabet, Salesforce.com, Facebook and others. The San Francisco Bay Area accounts for about a quarter of all AI activity in the United States.
The second is the early adoption of the city. Thirteen urban areas with important AI clusters are referred to by the study as "Early Adopters." Together with the Bay Area, these 14 metropolitan areas account for as many as two-thirds of the nation's AI assets and capabilities. These include the major cities of the East Coast Acela mega-region — New York, Boston, and Washington, D.C.; several California cities, including Los Angeles, San Diego, Santa Barbara, and Santa Cruz; and the long-standing centers of Seattle, Austin, Raleigh, and Boulder. The only surprise is that early adopters also include two smaller communities, Santa Fe, New Mexico, and Lincoln, Nebraska. The former is near the Los Alamos Laboratory, and the latter has the University of Nebraska.
The third is the research center. The Brookings study also identified 21 metropolitan areas with solid research capabilities but low commercialization, including Pittsburgh, home to Carnegie Mellon University and the University of Pittsburgh, and smaller university towns such as Ann Arbor, Madison, and Durham-Chapel Hill. Durham-Chapel Hill is adjacent to Raleigh and is part of the Research Triangle.
Potential ai-power hubs. This group consists of 87 metropolitan areas. The study calls it "potential adoption centers," and its AI activity is milder. Overall, these cities generate a quarter of all AI patents and companies in the United States, and account for a third of all AI jobs and workers. But on a per capita basis, these cities have less than half the AI capabilities of the 13 early adopter cities. They include fast-growing "Sunbelt metros" like Atlanta, Houston, and Nashville, "Frostbelt metro areas" like Chicago and Detroit with large industrial clusters, college towns like State College, where Penn State Is home, and smaller tech hubs like Provo, Utah.
The trajectory of inequality
Many parts of the U.S. hope that as the shift in remote work caused by the pandemic and tech companies move more to the cloud rather than physical locations, their appeal to companies and talent in emerging industries such as artificial intelligence will increase. More and more states and cities are developing strategies and initiatives for AI.
The data provided by Muro points to a sign that may be promising: In 2020, ai-related jobs in several metropolitan areas will increase significantly, while the Bay Area will decline slightly. It is likely that the geography of AI's technology, jobs, or startups may not have significant data changes in a few years.
So far, though, the rise of AI has followed the spike pattern we've seen in technologies like semiconductors, software, biotech, the internet, social media, and cloud computing, where new technologies and industries grow around the heartlands of a handful of dominant technologies.
This can be seen from the fact that the Brookings Institution study found that the vast majority of the U.S. metropolitan areas (260) have almost no significant AI capabilities. This fact is astonishing. In fact, Pittsburgh's experience proves the difficulty of creating a new technology center. Carnegie Mellon University (where I taught for nearly 20 years) has long been one of the top three AI research centers in the United States, on a par with Stanford university and the Massachusetts Institute of Technology. The study included Pittsburgh on a list of research centers with limited entrepreneurship or commercialization.
Federal intervention may be needed to counter and reshape the strong trends that are unfolding
Artificial intelligence is different from the previous high-tech field, and its rise is not only happening in the United States, but around the world. It is growing in a range of global technology hubs such as London, Berlin, Tel Aviv, Shanghai, Beijing, Bangalore, Montreal and Toronto. In fact, the Brookings institution study mentions that Toronto's Vector Institute (a consortium of universities and global companies) is an example of what regions can look to when it comes to building their AI clusters and ecosystems. My research by Ian Hathaway and I paints a picture of the rise of global tech hubs against the backdrop of the fact that the U.S. share of global venture capital spent on startups has fallen from 90 percent or more in the 1990s to less than half of what it is today. This rise of global tech hubs is likely to increase in the future if COVID-19-era travel, immigration restrictions continue, and many of the world's cities become more attractive as hubs for local and global talent.
In addition to these geographic challenges, AI is expected to have a huge impact on employment, potentially eliminating not only a large number of low-skill jobs in manufacturing and services (such as transportation, logistics, and retail), but also jobs in professional and knowledge work areas such as medicine, law, and engineering. Given this threat to employment and existing industries, the Brookings institution's research encourages all regions to carefully assess the threats and opportunities that AI poses to their economies and workforces. This is very important.
Federal intervention may be needed to counter and reshape the strong trends that are unfolding. The Innovation and Competition Act of 2021, proposed by the Biden administration and considered by Congress, would invest $250 billion in key technologies such as artificial intelligence, driving the development of new "regional technology hubs" across the United States.
If AI is allowed to grow freely, it will strengthen and exacerbate the "winner-take-all" nature of the economic and geographic landscape.
Topic: Wu Jianfeng, some illustrations are selected by the translator.
Original: https://www.bloomberg.com/news/articles/2021-09-08/san-francisco-bay-area-dominates-race-for-ai