EXPOSED
The work is physical — loading hoppers, adjusting feed rates and screen settings on crushers and mills, clearing jams, changing grinding wheels and liners, sampling product for particle size — and language AI does none of that. The real threat is conventional plant automation: sensor-driven feed control, automated screening, and vision-based quality checks already run mills with fewer tenders, and AI makes those control loops better. Monitoring gauges, logging output, and adjusting to spec are the parts most easily absorbed; no license protects the role and buyers of aggregate or ground pigment do not pay for a human relationship.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $37,560 → $48,540 +3.4% 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
-2.5% 28,700 → 27,900 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -2.5% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
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.
~2,700 openings a year on average, including replacing people who leave.
EdgerFacerBinmanHullerMillerPulperSifterBevelerChipperCrackerCrusherGrinderGritterGrooverSpouterStamperTumblerCalcinerHydratorOperatorPolisherSmootherRegrinderBed Rubber
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier At 13 the split is real: PLC loops and belt scales already handle feed rate, amperage trending, and screen deck monitoring on modern crushing circuits, but nobody has automated unbolting a worn jaw plate, chipping out a bridged rock in a cone crusher, or re-dressing a grinding wheel on an older mill, which keeps this above the low end rather than at 8.
Hands-on in uncontrolled environments 15 reflects a shift spent in dust, noise, and vibration walking crusher decks and mill floors — lockout/tagout before entering a chute, sledging jams free, hauling liner segments and screen cloth, hosing down fines — in environments where the material itself is unpredictable and the plant layout is not a controlled cell.
No licence, no signature requirement 2 is nearly the floor because no state licenses a crusher operator; MSHA Part 46/48 or OSHA hazard training is required of the employer, not credentialed to you personally, so a plant can put a new hire on the same panel after a week of training.
Executes defined procedures on defined inputs 6 sits at the top of the procedural band because the calls you make — tightening the closed-side setting when the gradation drifts coarse, slowing the feeder before the mill chokes, pulling a sample for sieve analysis — are real decisions but measured against a written spec and a QC lab that overrides you.
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 (2/20) is whether the law requires a licensed human to sign. Trust premium (3/20) is whether buyers specifically pay for a person. Judgment and accountability (6/20) 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 11 of this occupation's 39 points (28%).
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 56/100, still EXPOSED.
No rule change needed: the residual work concentrates in the parts automation has not touched — entering crusher chambers to change jaw plates and mill liners, breaking bridged material out of hoppers, rigging and torquing grinding wheels. If lockout/tagout and confined-space entry practice continues to require a physical human inside de-energized equipment (and no liner-change robot reaches aggregate-plant price points), the surviving job is more physical than today's, not less
Genuine two-tier structure: gauge-watching, feed-rate trim, and output logging are the automatable tier; setup for a new feedstock or spec, diagnosing why a mill is packing or a screen blinding, and wear-driven judgment about when a liner is done are the judgment tier. If plants continue merging tender duties into a maintenance/millwright-hybrid role — a pattern already visible in aggregate and cement consolidation — the remaining day is disproportionately the diagnostic tier
MSHA's 2024 final rule on respirable crystalline silica (30 CFR 60) requires mine operators to designate a person to conduct exposure sampling and implement corrective actions; if state or federal rules go further and require a named, certified 'competent person' physically present to authorize crusher/mill restart after a jam, guard removal, or liner change — the way MSHA already requires certified persons for pre-shift examinations in underground mines — the tender role acquires a nameable, personally citable designation rather than an anonymous one
If a plant assigns a single named operator authority to reject a batch or stop the line on out-of-spec gradation — as ASTM C33 aggregate certification programs and DOT-approved source certification schemes push toward with a designated certified aggregate technician (e.g. state DOT aggregate technician certification in Indiana, Ohio, Pennsylvania) — the call becomes owned rather than advisory
In pharmaceutical, food, and pigment milling under FDA 21 CFR 211 cGMP, batch records for particle-size and blend-uniformity steps require a trained, identified operator signature; if FDA data-integrity guidance is extended to bar automated systems from self-certifying particle-size release without a human recorded as performing the verification, the grinding operator becomes a required signer on the batch record
The limit. No plausible route to trust_premium: buyers of crushed stone, cement clinker, or ground pigment purchase on spec sheet and price, and there is no customer-facing relationship to charge for. Even with every lever above landing, this stays a small, capital-substitutable occupation — plant automation, not language models, sets the headcount, and the levers change the character of the surviving jobs more than the number of them.
| New York-Newark-Jersey City, NY-NJ | 830 | $50,400 +4% |
| Los Angeles-Long Beach-Anaheim, CA | 580 | $43,820 -10% |
| Chicago-Naperville-Elgin, IL-IN | 450 | $49,860 +3% |
| Riverside-San Bernardino-Ontario, CA | 390 | $44,500 -8% |
| Atlanta-Sandy Springs-Roswell, GA | 370 | $47,080 -3% |
| Cleveland, OH | 370 | $39,670 -18% |
| Cincinnati, OH-KY-IN | 360 | $40,850 -16% |
| Cedar Rapids, IA | 340 | $64,670 +33% |
| Duluth, MN-WI | 60 | $84,310 +74% |
| Lafayette-West Lafayette, IN | 70 | $66,800 +38% |
| Corpus Christi, TX | 40 | $66,540 +37% |
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 39. 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.