But let's blame AI
It presents a difference-in-differences (https://en.wikipedia.org/wiki/Difference_in_differences) design that exploits staggered adoption of generative AI to estimate the causal effect on productivity. It compares headcount over time by age group across several occupations, showing significant differentials across age groups.
Page 3: "We test for a class of such confounders by controlling for firm-time effects in an event study regression, absorbing aggregate firm shocks that impact all workers at a firm regardless of AI exposure. For workers aged 22-25, we find a 12 log-point decline in relative employment for the most AI-exposed quintiles compared to the least exposed quintile, a large and statistically significant effect."
The OP's point could still be valid: it’s still possible that macro factors like inflation, interest rates, or tariffs land harder on the exact group they label ‘AI-exposed.’ That makes the attribution messy.
Is AI being used to attempt to mitigate that effect?
I don't think their methods or any statistical method could decouple a perfectly correlated signal.
Without AI, would junior jobs have grown as quickly as other?