航空貨物コーディネーター
輸送・資材運搬AI露出度
- データ出典: BLS公表時点: 2026-08
非常に高い· 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
0.017
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
0.44
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28%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
非表示の作業 41 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Inform clients of factors such as shipping options, timelines, transfers, or regulations affecting shipments.43-5011 | 0.005618.7 | 0.00489.0 |
Determine efficient and cost-effective methods of moving goods from one location to another.43-5011 | 0.005117.0 | 0.00285.2 |
Prepare shipping documentation, such as including bills of lading, packing lists, dock receipts, or certificates of origin.43-5011 | 0.004113.7 | 0.012723.7 |
Assist clients in obtaining insurance reimbursements.43-5011 | 0.003411.3 | —0 |
Advise clients on transportation and payment methods.43-5011 | 0.00289.3 | —0 |
Complete customs paperwork.43-5011 | 0.00279.0 | —0 |
Provide detailed port information to importers or exporters.43-5011 | 0.00258.3 | —0 |
Check import or export documentation to determine cargo contents and use tariff coding system to classify goods according to fee or tariff group.43-5011 | 0.00217.0 | 0.00346.3 |
Refer exporters to experts in areas such as trade financing, international marketing, government export requirements, international banking, or marine insurance.43-5011 | 0.00175.7 | —0 |
Prepare invoices or cost quotations for freight transportation. | —0 | 0.008115.1 |
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 |
|---|---|
Calculate weight, volume, or cost of goods to be moved.O*NET Task ID 17686 | 1.0 |
Prepare shipping documentation, such as bills of lading, packing lists, dock receipts, or certificates of origin.O*NET Task ID 17687 | 1.0 |
Keep records of goods dispatched or received.O*NET Task ID 17690 | 1.0 |
Prepare invoices or cost quotations for freight transportation.O*NET Task ID 17696 | 1.0 |
Complete customs paperwork.O*NET Task ID 17701 | 1.0 |
Select shipment routes, based on nature of goods shipped, transit times, or security needs.O*NET Task ID 17680 | 0.5 |
Determine efficient and cost-effective methods of moving goods from one location to another.O*NET Task ID 17681 | 0.5 |
Reserve necessary space on ships, aircraft, trains, or trucks.O*NET Task ID 17682 | 0.5 |
Arrange delivery or storage of goods at destinations.O*NET Task ID 17683 | 0.5 |
Arrange for special transport of sensitive cargoes, such as livestock, food, or medical supplies.O*NET Task ID 17684 | 0.5 |
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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page