高速道路保守作業員
建設・メンテナンス・修理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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Inspect markers to verify accurate installation.O*NET Task ID 4883 | 0.5 |
Flag motorists to warn them of obstacles or repair work ahead.O*NET Task ID 4871 | 0.0 |
Set out signs and cones around work areas to divert traffic.O*NET Task ID 4872 | 0.0 |
Dump, spread, and tamp asphalt, using pneumatic tampers, to repair joints and patch broken pavement.O*NET Task ID 4874 | 0.0 |
Drive trucks to transport crews and equipment to work sites.O*NET Task ID 4875 | 0.0 |
Inspect, clean, and repair drainage systems, bridges, tunnels, and other structures.O*NET Task ID 4876 | 0.0 |
Haul and spread sand, gravel, and clay to fill washouts and repair road shoulders.O*NET Task ID 4877 | 0.0 |
Erect, install, or repair guardrails, road shoulders, berms, highway markers, warning signals, and highway lighting, using hand tools and power tools.O*NET Task ID 4878 | 0.0 |
Remove litter and debris from roadways, including debris from rock and mud slides.O*NET Task ID 4879 | 0.0 |
Clean and clear debris from culverts, catch basins, drop inlets, ditches, and other drain structures.O*NET Task ID 4880 | 0.0 |
Perform roadside landscaping work, such as clearing weeds and brush, and planting and trimming trees.O*NET Task ID 4881 | 0.0 |
Paint traffic control lines and place pavement traffic messages, by hand or using machines.O*NET Task ID 4882 | 0.0 |
Apply poisons along roadsides and in animal burrows to eliminate unwanted roadside vegetation and rodents.O*NET Task ID 4884 | 0.0 |
Measure and mark locations for installation of markers, using tape, string, or chalk.O*NET Task ID 4885 | 0.0 |
Apply oil to road surfaces, using sprayers.O*NET Task ID 4886 | 0.0 |
Blend compounds to form adhesive mixtures used for marker installation.O*NET Task ID 4887 | 0.0 |
Place and remove snow fences used to prevent the accumulation of drifting snow on highways.O*NET Task ID 4888 | 0.0 |
Perform preventative maintenance on vehicles and heavy equipment.O*NET Task ID 18783 | 0.0 |
Drive heavy equipment and vehicles with adjustable attachments to sweep debris from paved surfaces, mow grass and weeds, remove snow and ice, and spread salt and sand.O*NET Task ID 18784 | 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