刑事・捜査官
保護サービスAI露出度
- データ出典: BLS公表時点: 2026-08
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
0.037
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
0.23
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80%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 79 件を表示| Task | Claude.aiRaw / share % |
|---|---|
Examine immigration applications, visas, and passports and interview persons to determine eligibility for admission, residence, and travel in the U.S.33-3021 | 0.033726.9 |
Prepare comprehensive written reports, presentations, maps, or charts based on research, collection, and analysis of intelligence data.33-3021 | 0.026321.0 |
Validate known intelligence with data from other sources.33-3021 | 0.018815.0 |
Design, use, or maintain databases and software applications, such as geographic information systems (GIS) mapping and artificial intelligence tools.33-3021 | 0.00947.5 |
Collaborate with representatives from other government and intelligence organizations to share information or coordinate intelligence activities.33-3021 | 0.00584.6 |
Prepare reports that detail investigation findings.33-3021 | 0.00352.8 |
Identify case issues and evidence needed, based on analysis of charges, complaints, or allegations of law violations.33-3021 | 0.00332.6 |
Gather intelligence information by field observation, confidential information sources, or public records.33-3021 | 0.00322.5 |
Coordinate or conduct instructional classes or in-services, such as citizen police academy classes and crime scene training for other officers.33-3021 | 0.00292.3 |
Gather, analyze, correlate, or evaluate information from a variety of resources, such as law enforcement databases.33-3021 | 0.00282.2 |
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 |
|---|---|
Record progress of investigation, maintain informational files on suspects, and submit reports to commanding officer or magistrate to authorize warrants.O*NET Task ID 23024 | 1.0 |
Prepare reports that detail investigation findings.O*NET Task ID 23029 | 1.0 |
Notify, or request notification of, medical examiner or district attorney representative.O*NET Task ID 23044 | 1.0 |
Obtain facts or statements from complainants, witnesses, and accused persons and record interviews, using recording device.O*NET Task ID 23022 | 0.5 |
Prepare charges or responses to charges, or information for court cases, according to formalized procedures.O*NET Task ID 23025 | 0.5 |
Preserve, process, and analyze items of evidence obtained from crime scenes and suspects, placing them in proper containers and destroying evidence no longer needed.O*NET Task ID 23026 | 0.5 |
Note, mark, and photograph location of objects found, such as footprints, tire tracks, bullets and bloodstains, and take measurements of the scene.O*NET Task ID 23028 | 0.5 |
Examine records and governmental agency files to find identifying data about suspects.O*NET Task ID 23030 | 0.5 |
Provide information to lab personnel concerning the source of an item of evidence and tests to be performed.O*NET Task ID 23032 | 0.5 |
Analyze completed police reports to determine what additional information and investigative work is needed.O*NET Task ID 23033 | 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