SAFE
The paperwork layer of this job — lesson plans, worksheets, rubrics, differentiated reading passages, parent newsletters, report-card comment drafts — is already being generated by AI in minutes. But the actual work is keeping 24 seven-year-olds regulated, safe, and learning in one room for six hours, which is embodied supervision of minors that no software or robot performs. State licensure, mandated-reporter duty, and in loco parentis custody make a certified adult legally necessary in the room; that shield is regulatory and durable but not permanent.
Roughly flat across the period, with year-to-year wobble.
Median pay $59,670 → $63,970 -14.2% 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% 1,422,700 → 1,394,800 on the projections basis
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.
~91,000 openings a year on average, including replacing people who leave.
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Holding it up: trust premium . Weakest point: judgment & accountability .
Mixed — a routine tier and a judgment tier A 13 reflects the split you live: the generative half of your prep — leveled passages, exit tickets, IEP-adjacent accommodation language, standards-aligned unit maps, Friday newsletters — is genuinely being drafted by a model now, while teaching a child to decode CVC words, running a small group where one kid is crying and another is under the table, and reading the room during a fire drill do not decompose into prompts.
Hands-on in uncontrolled environments 15 puts you above nurses' aides in a controlled ward and below a lineman: the room is uncontrolled — playground duty, lunchroom, bathroom escorts, a vomit incident before 9am, physically redirecting a bolting student — but it's still an indoor space you know, with a floor plan and a door.
Licensed human required and personally liable 13 is state licensure plus mandated-reporter statute plus in loco parentis custody, which legally requires a certified adult present for the instructional day; it's not 18 because the liability mostly runs through the district's insurance and your union contract rather than landing on you personally the way it does on a physician's malpractice policy.
Meaningful discretion 13 sits where it does because you make consequential unscripted calls daily — whether that bruise is a DCF call, whether to hold a child at Tier 2 or refer for evaluation, how to seat and pair a class — but curriculum pacing, adopted reading programs, and state testing windows are handed to you, so the frame is set by someone else.
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 (18/20) 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 44 of this occupation's 72 points (61%).
Embodiment (15/20) 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 84/100, still SAFE.
Post-pandemic expansion of teacher role in threat assessment, child-welfare referral, and retention/promotion decisions under state third-grade reading-gate laws (Mississippi, Michigan, Tennessee) where the classroom teacher's documented judgment is the exception pathway
Union contract language (NEA/AFT locals, e.g. the AFT-Microsoft/OpenAI training academy paired with bargaining demands) that bars AI-generated grades or discipline records from being entered without a named licensed employee accepting responsibility, plus mandated-reporter duty explicitly non-delegable to software
Task-mix shift: if worksheet generation, differentiation, and report-card comments are fully automated, the residual day is behavior de-escalation, live diagnosis of why a child is stuck, and family conflict — the judgment tier already dominant here, so the shift is small but real
State legislatures or boards codifying that AI cannot serve as the adult supervising minors and that a certified teacher of record must personally sign off on IEP-adjacent instructional decisions, grades, and AI-generated student data used in placement — e.g. extending the pattern in state AI-in-education guidance (Ohio, Tennessee 'teacher of record' language, California AB 2876) into binding staffing ratios rather than advisory guidance
Parental backlash codified as choice: districts offering explicit 'human-taught, low-screen' classrooms as an enrollment option after state phone/screen-time restrictions, making the human adult the advertised product rather than the default
The limit. trust_premium at 18 and embodiment at 15 are near their practical ceilings; supervision of minors in a room is already the whole moat. The realistic downside risk is not automation but headcount — larger class sizes with AI tutoring aides, or paraprofessional substitution, which cuts the number of jobs without changing any dimension score.
| New York-Newark-Jersey City, NY-NJ | 98,900 | $96,900 +51% |
| Chicago-Naperville-Elgin, IL-IN | 45,840 | $78,390 +23% |
| Los Angeles-Long Beach-Anaheim, CA | 44,790 | $101,860 +59% |
| Houston-Pasadena-The Woodlands, TX | 30,980 | $64,500 +1% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 30,940 | $79,470 +24% |
| Dallas-Fort Worth-Arlington, TX | 27,350 | $65,070 +2% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 23,380 | $78,570 +23% |
| Atlanta-Sandy Springs-Roswell, GA | 23,370 | $76,570 +20% |
| Olympia-Lacey-Tumwater, WA | 950 | $104,650 +64% |
| Sacramento-Roseville-Folsom, CA | 10,480 | $103,390 +62% |
| Walla Walla, WA | 220 | $102,980 +61% |
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 72. 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.