The AI jobs numbers look calm until you cut them by age. This episode examines the June 2026 Stanford Digital Economy Lab and ADP Research data, which shows early-career workers in the most AI-exposed jobs contracting near 4 percent a year while their least-exposed peers keep growing, and it works through why the entry-level on-ramp is the first thing AI removes.

The conversation covers the augmentation versus automation split that decides whether jobs grow or vanish, the limit of a population dashboard that can diagnose the trend but cannot see whether any single worker is being grown or replaced, and the case for measuring the person in real time with a named human at the checkpoint. It closes on the hardest question the data raises: if AI absorbs the tasks that used to train people, where does the next generation of capable, accountable workers come from.

Read the full article, with the complete data, the honest caveats, and every source:

https://basilpuglisi.com/ai-jobs-on-ramp-measurement/

The Other AI: Audio Briefings on Augmented Intelligence and AI Governance

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