"Especially alarming to many has been AI's effect on entry-level jobs. A blockbuster Stanford study in August was especially rattling, as it claimed to find a "significant and disproportionate impact" on entry-level jobs most exposed to AI automation-like software development and customer service-have seen steep relative declines in employment. This came out close to the MIT study that said 95% of generative AI pilots were failing and the somewhat sudden realization that AI could be building toward a bubble."
"The new study examined multiple measures of labor market disruption, drawing on Bureau of Labor Statistics (BLS) data on job losses, spells of unemployment, and shifts in broader occupational composition. The conclusion: there's movement, but nothing out of the ordinary. While the mix of occupations has shifted slightly in the past years, the authors stress that this change is still well within historical norms. Right now, the forces driving those shifts appear to be macroeconomic rather than technological."
Entry-level jobs most exposed to AI, such as software development and customer service, have experienced steep relative declines in employment in some analyses. Generative AI pilot programs have shown high failure rates and raised concerns about a potential bubble. Some observers report younger workers, recent graduates, and minorities facing employment difficulties. Other analyses characterize these instances as isolated "lightning strikes" rather than widespread disruption. Multiple labor-market measures, including job losses, unemployment spells, and occupational composition, continue to move within historical norms. Current job mix shifts appear driven more by macroeconomic forces—slowing growth, an aging population, and lower immigration—than by AI.
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