This is a useful time to see changes in employment growth in different regions of the country and compare it to a large-scale pre-competitive economy, as overall job growth is currently only one lower than in 2019. U.S. jobs grew 1.2%, up from a year ago, close to 1.3% in 2019.
Let’s start with moving from cold countries to warm states in the most affected employment data. House prices are a useful agent for interstate migration. According to the S&P Corelogic Case-Shiller Index, the two metropolises with the weakest growth in home prices are the metropolis in Dallas and Tampa, Florida. Starting a year ago, Dallas jobs rose 1.4% in March, about half of its 2019 year-on-year, while in Tampa, it grew only 0.9%, accounting for one-third of the 2019 pace. On the other hand, the decline in immigration from the Northeast and Midwest helped explain why jobs grew more than the pre-pandemic pace in Buffalo, New York and Pittsburgh, Pennsylvania.
In theory, fewer interstate migrations should also increase the fate of the San Francisco Bay Area, a region known for being away from people with high housing costs. However, employment in the region has been declining since the pandemic peak in November 2022, coincidentally, Openai’s Chatgpt month began.
This boils down to tech companies that lay off jobs in 2023 and early 2024 to stay profitable after previous years of recruitment frenzy. Meta Platforms Inc., driven by the 2023 “Efficiency Year”, fell 22% year-on-year. But the elimination measures after this excitement have lagged behind – big tech companies are investing hundreds of billions of dollars in AI, while Meta’s total has grown 10% over the past year. It is therefore worth noting that employment in the country’s technological heartland continues to decline, with large-scale investments in the Gulf and fewer people leaving the region in theory.
The most likely culprit is the impact of AI on labor demand. The types of white-collar jobs narrow down the fastest jobs in the United States, including categories such as software engineers, data engineers and application engineers. Indeed, on the recruitment website, the software engineer job posting is currently lower than the jobs in spring 2020. Some of these may be due to increased efficiency in AI, while some of the declines may be due to companies that need to control their employees, which need to pile up a lot of money in advanced chips and data centers here, while another Boston knowledge rate of 5% is the range of 3. models. past year, the highest level outside of the pandemic period since 2015. The education hub may be more vulnerable than some other cities to AI adoption since the technology tends to be good at the kind of work that would typically be offered to young college graduates. These are dynamics we should expect to see, according to “From San Francisco to Savannah? The Downstream Effects of Generative AI,” a paper by researchers at Louisiana State University and Massachusetts Institute of Technology. Metropolitan areas with high education and high cost of living are most vulnerable to AI disruption. These cities have many types of jobs AI that can be replaced and cut jobs there help to reduce employee expenses faster. Authors Scott Abrahams and Frank S. Levy highlighted similarities to the 1980s, when the negative impact of automation and globalization had the greatest impact on manufacturing communities with lower education levels.
This doesn’t mean that San Francisco will become a tech rust belt – after all, the region is at the forefront of AI innovation, and even if it ends up getting less software development work, it can be replaced by different types of AI-enhanced knowledge work. Abrahams and Levy pointed out that the manufacturing shock benefits the southern United States, not just Asian exporters, but the AI shock may lead to a more balanced economic development across the United States. However, this may take time, especially as interstate migration is still restricted by the dysfunctional housing market. Given our experience of manufacturing losses and signs that another labor market reordering is coming, it is time for policy makers at the local and national levels to start taking AI disruption seriously.
