COOKEDthe AI job-risk monitorSYSTEM LIVE
◀ scan anotherLOADING AND MOVING MACHINE OPERATORS, UNDERGROUND MININGshare ⧉
EXPOSURE TO AI
2%
RESILIENT
OBSERVED IN REAL USE · Anthropic 2026
0%
of this role’s work is already showing up in real Claude usage (Anthropic Economic Index).
Robots can’t hold a hand, a scalpel, or your nerve.

2% of this role’s O*NET tasks are within reach of today’s AI. That is the core-weighted exposure score from Eloundou et al. 2023 (“GPTs are GPTs”). It measures a capability ceiling, not a headcount forecast. Certified hard to automate. Today’s AI barely touches the core of this one.

WHAT AI CAN ALREADY DO
  • Maintain records of materials moved
WHAT IT STILL CAN’T
  • Handle high voltage sources and hang electrical cables
  • Drive loaded shuttle cars to ramps and move controls to discharge loads into mine cars or onto conveyors
  • Pry off loose material from roofs and move it into the paths of machines, using crowbars
  • Move trailing electrical cables clear of obstructions, using rubber safety gloves
  • Control conveyors that run the entire length of shuttle cars to distribute loads as loading progresses
THE HONEST PART. A percentage is not a pink slip. High exposure usually means a role shrinks and shifts toward judgment, direction and responsibility: the parts a model can’t sign its name to. Exposure ≠ displacement. Breathe.
SOURCES: O*NET 30.3 occupational tasks · Eloundou et al. 2023 (“GPTs are GPTs”,arXiv:2303.10130) · Anthropic Economic Index 2026 (CC-BY)  | how this is calculated  | last updated 2026-07-16