← Risk register Form CI-R · rev. 2026-08-11

Reports

Every occupation, every dimension, and seven years of BLS employment — sliced however you need it. Nothing here is computed on a server: the whole dataset loads once and filters instantly, and you can download exactly what you're looking at.

Employment for this selection

Total US employment across the filtered occupations, by year. Counted by the BLS — the one series here that isn't our judgement.

Occupation Verdict Score Workers 2019–25 Median wage

Prefer a ready-made cut? Six rankings — safest, most exposed, best paid and safe, largest, growing, and already shrinking.

The safest big jobs are not the good jobs

The largest occupation in the United States is Home Health and Personal Care Aides — 4,305,810 people, scored 70, one of the most resistant on the register. It pays $35,800. Cashiers, scored 23 and COOKED, pay $32,880. Whatever protects the first job from automation is not paying for it.

Resistance score against median annual wage, 825 US occupations A scatter plot. Each circle is one occupation, sized by employment and placed by its resistance score horizontally and its median wage vertically on a logarithmic scale. The correlation is 0.35, so the score accounts for about 12 percent of the variation in pay. The largest circles sit low on the wage axis at the safe end: Home Health and Personal Care Aides, 4,305,810 workers at $35,800; Nursing Assistants, 1,448,910 workers at $42,260. $25,000 $50,000 $100,000 $200,000 0255075100 resistance score — higher is safer median annual wage (log scale) Home Health and Personal Care Aides · $35,800 Nursing Assistants · $42,260

COOKED EXPOSED SAFE · circle size is employment · 825 occupations

0.35 correlation (r) score vs log wage
12% of wage variation explained r² = 0.123
0.248 r, weighted by employment weaker where the people are
5.8M workers, SAFE and under $45,000 2 occupations above a million

Safer work does pay more on average — the median SAFE occupation pays $68,080 against $48,500 for the median COOKED one. But the association is weak, and it gets weaker where it matters most: weight every occupation by how many people are actually in it and r falls from 0.35 to 0.248. The link between being hard to automate and being well paid is loosest at the exact end of the distribution where the most people work.

The reason is visible in the chart. The work current AI cannot do is disproportionately physical care work — in homes, at bedsides, with people who cannot be scheduled — and physical care work is badly paid. That is a fact about the labour market, not a fact about AI, and no amount of automation resistance changes it.

What this number is not
  • Not causal, in either direction. This describes how two published medians co-vary across occupations. It is not evidence that automation resistance depresses pay, or that low pay protects work from automation.
  • Occupations, not people. These are occupation-level medians, so every distribution inside an occupation is invisible. Each occupation counts once whether it holds 300 workers or 4.3 million — which is exactly why the employment-weighted figure is published beside the plain one.
  • r = 0.35 is a weak-to-moderate association. It leaves 88% of the variation in pay to everything else: licensing, unionisation, credential length, hours, who does the work and what the country has historically been willing to pay them.
  • The wage axis is top-coded. The BLS publishes annual medians above $239,200 as a ceiling rather than a figure, so the highest earning occupations are compressed against the top of the chart.
  • 5 occupations are missing from the 825 plotted, because the BLS suppressed their wage or employment. Suppressed is not zero, so they are dropped rather than imputed.

Using this data