AI's labor market squeeze tightens (www.axios.com)

U.S. tech firms are pouring unprecedented resources into AI research and engineering — a “modern Manhattan Project” chase to edge past China toward ever-more-capable models — while federal preparations for the economic fallout lag or are absent. That split is already producing a tightening labor-market squeeze: companies and well-paid AI workers and investors are reaping the gains of automation and model advances, even as many ordinary Americans face displacement or wage pressure in sectors where cognitive and routine tasks can be automated today. For the AI/ML community this matters beyond headline drama: compute, data, and talent are increasingly concentrated in a few firms, accelerating capability development and deployment at scale. Technical implications include faster automation of white‑collar work (customer support, coding, content creation), shifting demand for skills toward ML engineering and prompt/system design, and growing urgency for robust impact measurement, reskilling tools, and deployment safety. The widening gap raises policy questions—workforce retraining, income support, and governance—so researchers and engineers should prioritize transparency, socio‑economic impact studies, and practical mitigation technologies alongside research on raw capability.