食品安全専門家
食品調理・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
0.204
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
0.26
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76%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 31 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Compute moisture or salt content, percentages of ingredients, formulas, or other product factors, using mathematical and chemical procedures.19-4011 | 0.043942.5 | 0.009026.3 |
Respond to general inquiries or requests from the public.19-4011 | 0.035134.0 | 0.014041.1 |
Examine chemical or biological samples to identify cell structures or to locate bacteria or extraneous material, using a microscope.19-4011 | 0.00504.8 | 0.007522.1 |
Provide assistance to food scientists or technologists in research and development, production technology, or quality control.19-4011 | 0.00474.5 | 0.003610.6 |
Prepare data summaries, reports, or analyses that include results, charts, or graphs to document research findings and results.19-4011 | 0.00363.5 | —0 |
Examine animals or crop specimens to determine the presence of diseases or other problems.19-4011 | 0.00323.1 | —0 |
Prepare or present agricultural demonstrations.19-4011 | 0.00201.9 | —0 |
Conduct standardized tests on food, beverages, additives, or preservatives to ensure compliance with standards and regulations regarding factors such as color, texture, or nutrients.19-4011 | 0.00201.9 | —0 |
Monitor and control temperature of products.19-4011 | 0.00201.9 | —0 |
Mix, blend, or cultivate ingredients to make reagents or to manufacture food or beverage products.19-4011 | 0.00181.7 | —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 |
|---|---|
Compute moisture or salt content, percentages of ingredients, formulas, or other product factors, using mathematical and chemical procedures.O*NET Task ID 7578 | 1.0 |
Record or compile test results or prepare graphs, charts, or reports.O*NET Task ID 7579 | 1.0 |
Analyze test results to classify products or compare results with standard tables.O*NET Task ID 7581 | 1.0 |
Maintain records of testing results or other documents as required by state or other governing agencies.O*NET Task ID 20394 | 1.0 |
Provide assistance to food scientists or technologists in research and development, production technology, or quality control.O*NET Task ID 7577 | 0.5 |
Examine chemical or biological samples to identify cell structures or to locate bacteria or extraneous material, using a microscope.O*NET Task ID 7583 | 0.5 |
Order supplies needed to maintain inventories in laboratories or in storage facilities of food or beverage processing plants.O*NET Task ID 7587 | 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