While official unemployment remains low, America’s labor market is stagnating: wage growth has slowed, job creation has weakened, and labor force participation is in decline. White-collar employment, particularly in tech, has fallen by 1.9 percent since its peak in 2022.
This may sound modest, but previous recessions in 2008 and 2020 began with similar declines. In the tech industry, layoffs are up 36 percent from last year. What began in 2022 as start-up downsizing has since spread to larger, higher-profile companies such as Microsoft, Google, Salesforce, and Meta.
Mainstream explanations attribute these cuts to the rise of artificial intelligence (AI). Generative AI, a branch of machine learning that draws associations across massive data to generate images, text, or predictions without preset instruction, has been cast as a disruptive force capable of reshaping society. The CEO of Anthropic, one of the leading generative AI firms, says we need to stop “sugarcoating”: AI could “wipe out half of all entry-level white-collar jobs and spike unemployment to 10-20 percent in the next five years.”
There are reasons to be skeptical of this alarmism. A recent Yale Budget Lab study finds that “while the anxiety over the effects of generative AI on today’s labor market are widespread, our data suggests it remains largely speculative.” Similarly, Nobel laureate economist Daron Acemoğlu sees no evidence that the new technology will have “revolutionary effects” on the economy. Countering claims that AI will double US GDP growth, he…
Auteur: Sophie Bandarkar
