SAFE
This job is supervising 12-year-olds around table saws, soldering irons, sewing machines, and kitchen ranges — physical instruction with real injury risk that no current robot or chatbot can take over. AI will absorb the paperwork tier: lesson plan drafting, rubric writing, safety-quiz generation, progress-report narratives. What remains is shop-floor demonstration, hands-on skill correction, behavior management, and legal responsibility for student safety under state teaching licensure.
Headcount grew steadily across the period.
Median pay $60,800 → $65,030 -14.4% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-2%
Percentage only. The projection counts a different population from the 16,870 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Hard to automate, but shrinking anyway
The work resists current AI, yet the BLS projects -2% by 2034. Whatever is shrinking this occupation, the evidence does not point to automation — demand, demographics, offshoring and industry decline all shrink jobs that no machine could do.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~900 openings a year on average, including replacing people who leave.
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Holding it up: embodiment . Weakest point: judgment & accountability .
Mixed — a routine tier and a judgment tier Demonstrating a proper crosscut, spotting a kid who has just tied back their hair wrong, and catching the moment a 7th grader's solder joint is cold are corrections made by eye and hand in real time — but the grading, curriculum mapping, CTE pathway documentation and Perkins-reporting side of the week is genuinely draftable by a model, which is why this lands at 13 and not 17.
Hands-on in uncontrolled environments You spend the period on your feet moving between stations — resetting a jammed sewing machine, checking a blade guard, wiping a range top, physically blocking a student from reaching over a hot surface — in a room full of powered tools and adolescents, which is about as uncontrolled as an indoor workspace gets, short of a road crew.
Licensed human required and personally liable You hold a state teaching credential, usually with a CTE or industrial-arts endorsement, and you're the named supervising adult when an injury report goes to the district and the parents' attorney; the 13 rather than 18 reflects that the district's insurance and administration absorb most exposure and your licence isn't a personal practice licence you could lose a business with.
Meaningful discretion You decide daily which student is ready for the drill press unsupervised, when a behavior pattern crosses from horseplay into a safety removal, and how to modify a project for an IEP student's motor limitations — real calls with injury consequences, but bounded by district safety protocols, tool checkout rules and the IEP itself rather than made from scratch.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (13/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (13/20) is whether the law requires a licensed human to sign. Trust premium (15/20) is whether buyers specifically pay for a person. Judgment and accountability (13/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 41 of this occupation's 70 points (59%).
Embodiment (16/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 82/100, still SAFE.
Genuine two-tier job: if AI absorbs lesson planning, rubric generation, safety-quiz writing and IEP/progress narratives, the residual day is nearly all live demonstration, tool-hand correction, and behavior management — the share of the day AI cannot do rises even with no capability change
Industry-certification bodies (NCCER, ServSafe, AWS, Snap-on) requiring that a credentialed human proctor sign off on middle-school pathway skill assessments, making the teacher the named signatory on portable credentials
State CTE facility rules that name a licensed, present adult as the sole legally responsible supervisor for powered shop equipment and set student:instructor ratios (as in existing state industrial-arts safety codes and OSHA-modeled district policy); district liability insurers already condition coverage on a certified instructor being physically in the lab, and tightening that from policy to statute/board rule would harden the shield
Formal codification of the teacher's call on student readiness to operate a given machine — e.g., a district-required tool-permit system where the instructor personally authorizes each student per machine and that authorization is auditable after an injury
State CTE funding tied to Perkins V pathway completion with employer advisory boards demanding in-person shop hours; parents and local employers rejecting virtual/simulated substitutes for hands-on hours would keep the human-taught lab a purchased requirement rather than a preference
The limit. Already SAFE and near ceiling on embodiment; the realistic gains are small and mostly consolidation of what the role already is. The live downside risk is not AI but enrollment and budget — CTE labs get cut for cost, not replaced by software.
| Dallas-Fort Worth-Arlington, TX | 1,250 | $65,310 +0% |
| New York-Newark-Jersey City, NY-NJ | 1,010 | $98,950 +52% |
| Houston-Pasadena-The Woodlands, TX | 970 | $67,290 +3% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 410 | $77,320 +19% |
| San Antonio-New Braunfels, TX | 400 | $62,310 -4% |
| Charlotte-Concord-Gastonia, NC-SC | 340 | $57,100 -12% |
| Austin-Round Rock-San Marcos, TX | 320 | $62,230 -4% |
| Seattle-Tacoma-Bellevue, WA | 300 | $103,490 +59% |
| Spokane-Spokane Valley, WA | 70 | $107,960 +66% |
| Kennewick-Richland, WA | 40 | $107,620 +65% |
| Portland-Vancouver-Hillsboro, OR-WA | 40 | $105,240 +62% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 70. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.