AI exposure: Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders
Set up, operate, or tend machines to crush, grind, or polish materials, such as coal, glass, grain, stone, food, or rubber.
Reading this score
computedAt 18.7% of weighted task load, Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders sits at the 32th percentile, below the point where a job's centre of gravity has moved. 70.5% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.
What holds the line here is embodiment. Across this occupation's 21 tasks it averages 2.62 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Record data from operations, testing, and production on specified forms, at 73.3%. The least is Load materials into machinery and equipment, at 0.0%. A gap of 73.3% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within production occupations, this one is more exposed than most. The median across the 107 roles in the group is 16.1%, and only 39 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.
What would move this score. Of 21 tasks, 6 are currently banded exposed, 0 assisted and 15 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 1.07 | 0-4 |
| Embodiment | 2.62 | 0-3 |
| Presence | 0.45 | 0-3 |
| Accountability | 0.65 | 0-3 |
| Context | 1.06 | 0-3 |
| Verification cost | 0.98 | 0-3 |
Task by task
21 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Record data from operations, testing, and production on specified forms. | 73.3% | 26.7% | 0.0% | 3.77 | exposed |
| Read work orders to determine production specifications and information. | 55.0% | 20.0% | 25.0% | 3.54 | exposed |
| Notify supervisors of needed repairs. | 45.0% | 30.0% | 25.0% | 4.04 | exposed |
| Tend accessory equipment, such as pumps and conveyors, to move materials or ingredients through production processes. | 33.3% | 16.7% | 50.0% | 4.09 | exposed |
| Turn valves to regulate the moisture contents of materials. | 33.3% | 16.7% | 50.0% | 3.69 | exposed |
| Observe operation of equipment to ensure continuity of flow, safety, and efficient operation, and to detect malfunctions. | 30.0% | 20.0% | 50.0% | 4.35 | exposed |
| Move controls to start, stop, or adjust machinery and equipment that crushes, grinds, polishes, or blends materials. | 15.0% | 10.0% | 75.0% | 4.05 | untouched |
| Set mill gauges to specified fineness of grind. | 15.0% | 10.0% | 75.0% | 3.61 | untouched |
| Inspect chains, belts, or scrolls for signs of wear. | 13.3% | 11.7% | 75.0% | 3.74 | untouched |
| Reject defective products and readjust equipment to eliminate problems. | 11.7% | 13.3% | 75.0% | 3.76 | untouched |
| Examine materials, ingredients, or products, visually or with hands, to ensure conformance to established standards. | 11.7% | 13.3% | 75.0% | 3.64 | untouched |
| Test samples of materials or products to ensure compliance with specifications, using test equipment. | 11.7% | 13.3% | 75.0% | 3.92 | untouched |
| Clean, adjust, and maintain equipment, using hand tools. | 6.7% | 5.8% | 87.5% | 4.12 | untouched |
| Weigh or measure materials, ingredients, or products at specified intervals to ensure conformance to requirements. | 0.0% | 0.0% | 100.0% | 4.03 | untouched |
| Clean work areas. | 0.0% | 0.0% | 100.0% | 3.74 | untouched |
| Dislodge and clear jammed materials or other items from machinery and equipment, using hand tools. | 0.0% | 0.0% | 100.0% | 3.44 | untouched |
| Mark bins as to types of mixtures stored. | 0.0% | 0.0% | 100.0% | 3.86 | untouched |
| Transfer materials, supplies, and products between work areas, using moving equipment and hand tools. | 0.0% | 0.0% | 100.0% | 3.84 | untouched |
| Add or mix chemicals and ingredients for processing, using hand tools or other devices. | 0.0% | 0.0% | 100.0% | 3.78 | untouched |
| Collect samples of materials or products for laboratory testing. | 0.0% | 0.0% | 100.0% | 3.77 | untouched |
| Load materials into machinery and equipment, using hand tools. | 0.0% | 0.0% | 100.0% | 3.69 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.