AI job retraining ignores the wage collapse: a translator's story
PeterHndrsn · x · 2026-09-09
The author argues the current AI labor-impact debate misses a key dynamic: people spend their whole lives climbing to the top of a field and building stable income, and having that pulled out from under them—forcing a restart at much lower wages—is bound to breed resentment.
He recalls a translator at the Montreal AI Symposium who loved the craft of translation, with years of training and certification, now reduced to "you have five minutes to verify this AI output and make minor edits." While machine translation made the service nearly free and broadly beneficial, the human cost to those who thought they'd reached stability is severe.
He calls for solutions that prevent people from being stuck starting over or losing decent wages, and for measuring these externalities in labor economics—even if aggregate employment stays stable through entrepreneurship. Many professions face this now or soon: mathematics lately, then law, and eventually everything else.
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