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entry · p2026-09-06-139 · validated

Generative AI in AI-exposed occupations

employment of young workers (ages 22–25) in AI-exposed jobs now stands 19% below where it would be
tech
generative-ai-labour
passes the definition as
large language models fit to text, adopted across occupations whose tasks the models perform
from
2022-11
region
US
domain
work
side
loss
people
5,000,000 employees per month in the ADP analysis sample (2026-06)
effect
19 percent (2026-06) — employment of 22–25 year olds in AI-exposed occupations stands 19% below where it would be had it tracked their less-exposed peers
reversible
yes
who holds the switch
owner:employers
attribution
scale
source kind
primary
the statistic
Using ADP administrative payroll data (ADP serves firms employing over 26 million U.S. workers; the balanced analysis panel is 3.5–5 million employees per month, Jan 2021–Jun 2026), the young-worker AI-exposure employment shortfall was 15% at the July 2025 vintage and 19% as of June 2026; experienced workers show no comparable gap and there is no evidence of economy-wide displacement.
source
https://digitaleconomy.stanford.edu/app/uploads/2026/08/Canaries_August2026.pdf
proposed by
researcher (opus), brief 2026-09-06, era-2024-2026
received
2026-09-06T09:39:39-04:00
harvest report
impacts/harvest/2026-09-06-era-2024-2026.md

Rulings, in order

  1. 2026-09-06T09:39:47-04:00 · validatorpass — quote found on the fetched page (exact match; HTTP 200 application/pdf)
  2. 2026-09-06T09:59:36-04:00 · sessionseverity — young workers not hired into AI-exposed occupations: livelihood, no floor
  3. 2026-09-06T10:00:50-04:00 · sessionseverity — livelihood; but the only count is the ADP sample (5 million) and the effect is a percentage — no count of the young workers affected, so this cannot band until a source gives one
The proposal as it arrived (JSON)
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 "id": "p2026-09-06-139",
 "received": "2026-09-06T09:39:39-04:00",
 "proposer": "researcher (opus), brief 2026-09-06, era-2024-2026",
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  "tech": "generative-ai-labour",
  "tech_name": "Generative AI in AI-exposed occupations",
  "definition": "large language models fit to text, adopted across occupations whose tasks the models perform",
  "from": "2022-11",
  "region": "US",
  "domain": "work",
  "side": "loss",
  "people": {
   "n": 5000000,
   "unit": "employees per month in the ADP analysis sample",
   "date": "2026-06"
  },
  "effect": {
   "n": 19,
   "unit": "percent",
   "date": "2026-06",
   "what": "employment of 22–25 year olds in AI-exposed occupations stands 19% below where it would be had it tracked their less-exposed peers"
  },
  "reversible": true,
  "switch": "owner:employers",
  "statistic": "Using ADP administrative payroll data (ADP serves firms employing over 26 million U.S. workers; the balanced analysis panel is 3.5–5 million employees per month, Jan 2021–Jun 2026), the young-worker AI-exposure employment shortfall was 15% at the July 2025 vintage and 19% as of June 2026; experienced workers show no comparable gap and there is no evidence of economy-wide displacement.",
  "source": "https://digitaleconomy.stanford.edu/app/uploads/2026/08/Canaries_August2026.pdf",
  "quote": "employment of young workers (ages 22–25) in AI-exposed jobs now stands 19% below where it would be",
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 },
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