車両・機器清掃作業員
輸送・資材運搬AI露出度
- データ出典: BLS公表時点: 2026-08
低い· 相対
低い4段階の相対区分非常に高い職業群単位の値
尺度・母数・出典
4段階の相対区分（低い / 中程度 / 高い / 非常に高い）
BLS雇用見通し表の詳細職業831件が母数。値は NEM(全国雇用マトリクス)コード単位で付与されるため、同じ NEM コードの職業は同じバンドになります
- データ出典: Anthropic公表時点: 2026-03
0.000
0.000ここに掲載された値の範囲0.745尺度・母数・出典
- データ出典: ILO公表時点: 2025
0.09
0.09ここに掲載された値の範囲0.70職業群単位の値
尺度・母数・出典
生成AI露出度指数、公開されたまま0–1
ISCO-08の職業小分類単位 — 同じコードの職業はすべて同じ値
当サイトの算出であり、ILOが公表した数値ではありません。当サイトがILOデータセットに結び付けた職業1,012件のうち、この値以上のものは100%です。
この出典がどのような性格の値か
BLSの区分は絶対水準ではなく相対順位であり、一次測定でもありません。複数の既存研究が付けた職業別パーセンタイル順位を4段階にまとめた値です。雇用や賃金の予測でもなく、導入確率でもなく、自動化と増強を区別しません。
Task-level exposure
露出のある作業のみ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. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Maintain inventories of supplies.O*NET Task ID 5005 | 1.0 |
Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations.O*NET Task ID 4992 | 0.5 |
Scrub, scrape, or spray machine parts, equipment, or vehicles, using scrapers, brushes, clothes, cleaners, disinfectants, insecticides, acid, abrasives, vacuums, or hoses.O*NET Task ID 4993 | 0.0 |
Mix cleaning solutions, abrasive compositions, or other compounds, according to formulas.O*NET Task ID 4994 | 0.0 |
Press buttons to activate cleaning equipment or machines.O*NET Task ID 4995 | 0.0 |
Clean and polish vehicle windows.O*NET Task ID 4996 | 0.0 |
Rinse objects and place them on drying racks or use cloth, squeegees, or air compressors to dry surfaces.O*NET Task ID 4997 | 0.0 |
Drive vehicles to or from workshops or customers' workplaces or homes.O*NET Task ID 4998 | 0.0 |
Turn valves or handles on equipment to regulate pressure or flow of water, air, steam, or abrasives from sprayer nozzles.O*NET Task ID 4999 | 0.0 |
Pre-soak or rinse machine parts, equipment, or vehicles by immersing objects in cleaning solutions or water, manually or using hoists.O*NET Task ID 5000 | 0.0 |
Lubricate machinery, vehicles, or equipment or perform minor repairs or adjustments, using hand tools.O*NET Task ID 5001 | 0.0 |
Monitor operation of cleaning machines and stop machines or notify supervisors when malfunctions occur.O*NET Task ID 5002 | 0.0 |
Disassemble and reassemble machines or equipment or remove and reattach vehicle parts or trim, using hand tools.O*NET Task ID 5003 | 0.0 |
Connect hoses or lines to pumps or other equipment.O*NET Task ID 5004 | 0.0 |
Apply paints, dyes, polishes, reconditioners, waxes, or masking materials to vehicles to preserve, protect, or restore color or condition.O*NET Task ID 5006 | 0.0 |
Turn valves or disconnect hoses to eliminate water, cleaning solutions, or vapors from machinery or tanks.O*NET Task ID 5007 | 0.0 |
Sweep, shovel, or vacuum loose debris or salvageable scrap into containers and remove containers from work areas.O*NET Task ID 5008 | 0.0 |
Transport materials, equipment, or supplies to or from work areas, using carts or hoists.O*NET Task ID 5009 | 0.0 |
Collect and test samples of cleaning solutions or vapors.O*NET Task ID 5010 | 0.0 |
Clean the plastic work inside cars, using paintbrushes.O*NET Task ID 5011 | 0.0 |
Fit boot spoilers, side skirts, or mud flaps to cars.O*NET Task ID 5012 | 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