交通警察
保護サービスAI露出度
- データ出典: BLS公表時点: 2026-08
中程度· 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
0.14
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95%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
| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare reports documenting investigation activities and results.33-3052 | 0.00000.0 | —0 |
Examine credentials of unauthorized persons attempting to enter secured areas. | —0 | 0.00000.0 |
| Not observed on any surface — 10 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Patrol railroad yards, cars, stations, or other facilities to protect company property or shipments and to maintain order. | —0 | —0 |
Apprehend or remove trespassers or thieves from railroad property or coordinate with law enforcement agencies in apprehensions and removals. | —0 | —0 |
Investigate or direct investigations of freight theft, suspicious damage or loss of passengers' valuables, or other crimes on railroad property. | —0 | —0 |
Direct security activities at derailments, fires, floods, or strikes involving railroad property. | —0 | —0 |
Plan or implement special safety or preventive programs, such as fire or accident prevention. | —0 | —0 |
Monitor transit areas and conduct security checks to protect railroad properties, patrons, and employees. | —0 | —0 |
Enforce traffic laws regarding the transit system and reprimand individuals who violate them. | —0 | —0 |
Provide training to the public or law enforcement personnel in railroad safety or security. | —0 | —0 |
Direct or coordinate the daily activities or training of security staff. | —0 | —0 |
Interview neighbors, associates, or former employers of job applicants to verify personal references or to obtain work history data. | —0 | —0 |
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 |
|---|---|
Prepare reports documenting investigation activities and results.O*NET Task ID 9478 | 1.0 |
Examine credentials of unauthorized persons attempting to enter secured areas.O*NET Task ID 9476 | 0.5 |
Investigate or direct investigations of freight theft, suspicious damage or loss of passengers' valuables, or other crimes on railroad property.O*NET Task ID 9479 | 0.5 |
Interview neighbors, associates, or former employers of job applicants to verify personal references or to obtain work history data.O*NET Task ID 9482 | 0.5 |
Record and verify seal numbers from boxcars containing frequently pilfered items, such as cigarettes or liquor, to detect tampering.O*NET Task ID 9483 | 0.5 |
Plan or implement special safety or preventive programs, such as fire or accident prevention.O*NET Task ID 9484 | 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