AI exposure: Metal-Refining Furnace Operators and Tenders
Operate or tend furnaces, such as gas, oil, coal, electric-arc or electric induction, open-hearth, or oxygen furnaces, to melt and refine metal before casting or to produce specified types of steel.
Reading this score
computedAt 16.1% of weighted task load, Metal-Refining Furnace Operators and Tenders sits at the 26th percentile, below the point where a job's centre of gravity has moved. 73.6% 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 15 tasks it averages 2.52 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 production data, and maintain production logs, at 73.3%. The least is Scrape accumulations of metal oxides from floors, molds, and crucibles, and sift and store them..., 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 less exposed than the median of 16.2% across the group's 107 roles, with 54 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 15 tasks, 3 are currently banded exposed, 1 assisted and 11 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 | 0.99 | 0-4 |
| Embodiment | 2.52 | 0-3 |
| Presence | 0.57 | 0-3 |
| Accountability | 0.64 | 0-3 |
| Context | 1.19 | 0-3 |
| Verification cost | 1.21 | 0-3 |
Task by task
15 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Record production data, and maintain production logs. | 73.3% | 26.7% | 0.0% | 4.51 | exposed |
| Observe air and temperature gauges or metal color and fluidity, and turn fuel valves or adjust controls to maintain required temperatures. | 35.0% | 23.3% | 41.7% | 4.49 | exposed |
| Observe operations inside furnaces, using television screens, to ensure that problems do not occur. | 26.7% | 23.3% | 50.0% | 4.26 | exposed |
| Regulate supplies of fuel and air, or control flow of electric current and water coolant to heat furnaces and adjust temperatures. | 23.2% | 18.5% | 58.3% | 4.62 | untouched |
| Draw smelted metal samples from furnaces or kettles for analysis, and calculate types and amounts of materials needed to ensure that materials meet specifications. | 22.5% | 15.0% | 62.5% | 4.60 | untouched |
| Direct work crews in the cleaning and repair of furnace walls and flooring. | 20.0% | 30.0% | 50.0% | 4.00 | assisted |
| Inspect furnaces and equipment to locate defects and wear. | 13.3% | 11.7% | 75.0% | 4.40 | untouched |
| Kindle fires, and shovel fuel and other materials into furnaces or onto conveyors by hand, with hoists, or by directing crane operators. | 4.8% | 3.5% | 91.7% | 4.27 | untouched |
| Weigh materials to be charged into furnaces, using scales. | 0.0% | 0.0% | 100.0% | 4.54 | untouched |
| Operate controls to move or discharge metal workpieces from furnaces. | 0.0% | 0.0% | 100.0% | 4.48 | untouched |
| Drain, transfer, or remove molten metal from furnaces, and place it into molds, using hoists, pumps, or ladles. | 0.0% | 0.0% | 100.0% | 4.37 | untouched |
| Prepare material to load into furnaces, including cleaning, crushing, or applying chemicals, by using crushing machines, shovels, rakes, or sprayers. | 0.0% | 0.0% | 100.0% | 4.55 | untouched |
| Remove impurities from the surface of molten metal, using strainers. | 0.0% | 0.0% | 100.0% | 4.35 | untouched |
| Sprinkle chemicals over molten metal to bring impurities to the surface. | 0.0% | 0.0% | 100.0% | 4.24 | untouched |
| Scrape accumulations of metal oxides from floors, molds, and crucibles, and sift and store them for reclamation. | 0.0% | 0.0% | 100.0% | 3.72 | 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.