AI Is Wrecking Young Americans' Job Prospects

Original Article ↗ Hacker News Discussion ↗

Study Findings vs. Headline

  • Underlying paper finds:
    • Young workers (22–25) in AI-automatable roles see employment declines.
    • Young workers in AI-augmentative roles see employment growth.
  • Some see this as “canaries in the coal mine”; others note the overall job market was stronger 3–4 years ago and question how much is truly AI-driven.
  • Several ask for serious causal critiques of the paper rather than assumption-driven takes.

Is It Really AI, or Macro + Over-Supply?

  • Alternative explanations raised:
    • High interest rates, end of ZIRP, reversal of tax rules (e.g., IRC §174) pushing tech to run lean.
    • Pandemic e‑commerce hiring boom unwinding; concern the paper may not fully adjust for that.
    • Large increase in CS grads and bootcamp output; example: one university went from 3% to 21% of degrees in CS since 2011.
  • Others argue the paper explicitly compares AI-exposed vs. less-exposed occupations and still finds a disproportionate hit to young workers.

Juniors, LLMs, and Hiring Strategy

  • Some believe savvy firms should aggressively hire juniors now, building a talent moat while others overbet on GenAI.
  • Counterpoint: individual firms bear training costs but lose people when they become mid/senior; game-theory argument that this discourages junior hiring.
  • Debate over long-term contracts for juniors: seen by some as fair, by others as coercive.
  • Practitioners report LLMs ≈ “incompetent interns”:
    • Hidden costs in review, regressions, and rework.
    • If coding is ~20% of dev time, even big coding gains only modestly move total productivity.
    • Expectation that entry-level talent quality may rise due to AI as a learning tool, but near-term hiring is disrupted.

AI Capability Trajectory and Long-Term Jobs

  • Split views:
    • Some think AI will eventually eat “most jobs” over decades, implying a post-work society.
    • Others doubt current LLM paradigm can reach that, or fear a “post-work” world where owners no longer need most people.
  • Historical analogies (mechanization, looms) are invoked, but several note those waves created large new job categories; it’s unclear what analogous mass occupations AI will create.

Other Factors and Frictions

  • H1B and immigration cited as making markets “hyper-competitive,” though critics note immigration trends don’t neatly match the post‑2022 junior downturn.
  • Disagreement over whether discretionary income is generally shrinking or rising; data cited both ways and distributional effects flagged.
  • Concern about degraded CS curricula (less theory, more “trade”) and grade inflation possibly flooding the market with weaker juniors.
  • Example sectors like translation and customer service are seen as clearly impacted by AI, with extra “AI optimization” costs (GAIO) now added for small businesses.