{"data":{"slug":"jobs-automation","etype":"concept","name":"Jobs & Automation","cat":"Economics & Society","subtitle":"What the models do to work — early evidence, loud predictions.","summary":"Predictions run from Amodei's warning that AI could displace half of entry-level white-collar work within years, to economists (Acemoglu) modeling modest near-term GDP effects. Early data is mixed: studies show large productivity gains for juniors in coding and support, while 2025 saw the first layoffs framed explicitly around AI and falling junior-developer hiring. History's pattern — tasks automate, jobs recompose, transitions hurt — is the base case both sides argue against.","attrs":null,"kf":null,"aliases":["automation","technological unemployment","future of work"],"ticker":null,"exchange":null,"hq":null,"founded":null,"website":null,"status":null,"region":null,"asof":"2026-01-15","sources":[{"url":"https://www.nber.org/","label":"NBER working papers on generative AI"}]},"meta":{"found":true,"count":1,"served_from":"site cache (no live upstream calls)","as_of":"2026-10-14T06:54:13+00:00","disclaimer":"Research and information only — not investment advice. Structured records carry basis labels (vendor spec / reported / estimate); market quotes are delayed/indicative.","attribution":"Records compiled from vendor documentation, official filings and reputable public reporting; market quotes via financial data providers. See /data-sources."}}