AI exposure: Loading and Moving Machine Operators, Underground Mining
Operate underground loading or moving machine to load or move coal, ore, or rock using shuttle or mine car or conveyors. Equipment may include power shovels, hoisting engines equipped with cable-drawn scraper or scoop, or machines equipped with gathering arms and conveyor.
Reading this score
computedAt 10.9% of weighted task load, Loading and Moving Machine Operators, Underground Mining sits at the 16th percentile, below the point where a job's centre of gravity has moved. 82.3% 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 25 tasks it averages 2.66 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 Observe and record car numbers, carriers, customers, tonnages, and grades and conditions of..., at 73.3%. The least is Push or ride cars down slopes, or hook cars to cables and control cable drum brakes, to ease..., 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 construction and extraction occupations, this one is more exposed than most. The median across the 61 roles in the group is 5.0%, and only 12 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 25 tasks, 4 are currently banded exposed, 0 assisted and 21 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 | 0.81 | 0-4 |
| Embodiment | 2.66 | 0-3 |
| Presence | 0.65 | 0-3 |
| Accountability | 0.66 | 0-3 |
| Context | 1.08 | 0-3 |
| Verification cost | 1.23 | 0-3 |
Task by task
25 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Observe and record car numbers, carriers, customers, tonnages, and grades and conditions of material. | 73.3% | 26.7% | 0.0% | 3.87 | exposed |
| Maintain records of materials moved. | 73.3% | 26.7% | 0.0% | 3.58 | exposed |
| Read written instructions or confer with supervisors about schedules and materials to be moved. | 37.5% | 25.0% | 37.5% | 3.87 | exposed |
| Direct other workers to move stakes, place blocks, position anchors or cables, or move materials. | 30.0% | 20.0% | 50.0% | 3.56 | exposed |
| Measure, weigh, or verify levels of rock, gravel, or other excavated material to prevent equipment overloads. | 23.7% | 9.6% | 66.7% | 3.54 | untouched |
| Control conveyors that run the entire length of shuttle cars to distribute loads as loading progresses. | 16.7% | 8.3% | 75.0% | 4.29 | untouched |
| Operate levers to move conveyor booms or shovels so that mine contents such as coal, rock, and ore can be placed into cars or onto conveyors. | 16.7% | 8.3% | 75.0% | 4.20 | untouched |
| Advance machines to gather material and convey it into cars. | 16.7% | 8.3% | 75.0% | 4.15 | untouched |
| Drive loaded shuttle cars to ramps and move controls to discharge loads into mine cars or onto conveyors. | 11.7% | 13.3% | 75.0% | 4.46 | untouched |
| Monitor loading processes to ensure that materials are loaded according to specifications. | 10.0% | 15.0% | 75.0% | 3.85 | untouched |
| Clean, fuel, service, and perform safety checks on all equipment, and repair and replace parts as necessary. | 5.2% | 3.1% | 91.7% | 4.15 | untouched |
| Guide and stop cars by switching, applying brakes, or placing scotches, or wooden wedges, between wheels and rails. | 3.3% | 21.7% | 75.0% | 3.88 | untouched |
| Handle high voltage sources and hang electrical cables. | 0.0% | 0.0% | 100.0% | 4.57 | untouched |
| Pry off loose material from roofs and move it into the paths of machines, using crowbars. | 0.0% | 0.0% | 100.0% | 4.41 | untouched |
| Move trailing electrical cables clear of obstructions, using rubber safety gloves. | 0.0% | 0.0% | 100.0% | 4.40 | untouched |
| Observe hand signals, grade stakes, or other markings when operating machines. | 0.0% | 0.0% | 100.0% | 4.27 | untouched |
| Examine roadway and clear obstructions from the path of travel. | 0.0% | 0.0% | 100.0% | 4.27 | untouched |
| Drive machines into piles of material blasted from working faces. | 0.0% | 0.0% | 100.0% | 4.25 | untouched |
| Clean hoppers, and clean spillage from tracks, walks, driveways, and conveyor decking. | 0.0% | 0.0% | 100.0% | 4.07 | untouched |
| Oil, lubricate, and adjust conveyors, crushers, and other equipment, using hand tools and lubricating equipment. | 0.0% | 0.0% | 100.0% | 3.97 | untouched |
| Replace hydraulic hoses, headlight bulbs, and gathering-arm teeth. | 0.0% | 0.0% | 100.0% | 3.50 | untouched |
| Stop gathering arms when cars are full. | 0.0% | 0.0% | 100.0% | 4.39 | untouched |
| Move mine cars into position for loading and unloading, using pinchbars inserted under car wheels to position cars under loading spouts. | 0.0% | 0.0% | 100.0% | 4.18 | untouched |
| Signal workers to move loaded cars. | 0.0% | 0.0% | 100.0% | 4.01 | untouched |
| Push or ride cars down slopes, or hook cars to cables and control cable drum brakes, to ease cars down inclines. | 0.0% | 0.0% | 100.0% | 3.09 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean. 1 task(s) lacked a usable O*NET weight and are shown but excluded from the weighting.
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.