Riggers
Construction, Maintenance & RepairAI exposure
- Data source: BLSPublished: 2026-08
Moderate· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.13
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 97% score at or above this value.
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime.
| Task | βE1 + 0.5 × E2 |
|---|---|
Signal or verbally direct workers engaged in hoisting and moving loads to ensure safety of workers and materials.O*NET Task ID 13892 | 0.0 |
Test rigging to ensure safety and reliability.O*NET Task ID 13893 | 0.0 |
Attach loads to rigging to provide support or prepare them for moving, using hand and power tools.O*NET Task ID 13894 | 0.0 |
Select gear, such as cables, pulleys, and winches, according to load weights and sizes, facilities, and work schedules.O*NET Task ID 13895 | 0.0 |
Control movement of heavy equipment through narrow openings or confined spaces, using chainfalls, gin poles, gallows frames, and other equipment.O*NET Task ID 13896 | 0.0 |
Tilt, dip, and turn suspended loads to maneuver over, under, or around obstacles, using multi-point suspension techniques.O*NET Task ID 13897 | 0.0 |
Align, level, and anchor machinery.O*NET Task ID 13898 | 0.0 |
Fabricate, set up, and repair rigging, supporting structures, hoists, and pulling gear, using hand and power tools.O*NET Task ID 13899 | 0.0 |
Manipulate rigging lines, hoists, and pulling gear to move or support materials, such as heavy equipment, ships, or theatrical sets.O*NET Task ID 13900 | 0.0 |
Attach pulleys and blocks to fixed overhead structures, such as beams, ceilings, and gin pole booms, using bolts and clamps.O*NET Task ID 13901 | 0.0 |
Dismantle and store rigging equipment after use.O*NET Task ID 13902 | 0.0 |
Install ground rigging for yarding lines, attaching chokers to logs and to the lines.O*NET Task ID 13903 | 0.0 |
Clean and dress machine surfaces and component parts.O*NET Task ID 13904 | 0.0 |
Load machines onto trucks to prepare for transportation.O*NET Task ID 21206 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page