気候科学者
生命・物理・社会科学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
0.038
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
0.54
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13%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 14 件を表示| Task | Claude.aiRaw / share % |
|---|---|
Interpret data, reports, maps, photographs, or charts to predict long- or short-range weather conditions, using computer models and knowledge of climate theory, physics, and mathematics.19-2021 | 0.070858.5 |
Prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics.19-2021 | 0.016613.8 |
Gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts.19-2021 | 0.00766.3 |
Prepare scientific atmospheric or climate reports, articles, or texts.19-2021 | 0.00746.1 |
Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate.19-2021 | 0.00705.8 |
Apply meteorological knowledge to issues such as global warming, pollution control, or ozone depletion.19-2021 | 0.00332.7 |
Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.19-2021 | 0.00272.2 |
Estimate or predict the effects of global warming over time for specific geographic regions.19-2021 | 0.00221.8 |
Create visualizations to illustrate historical or future changes in the Earth's climate, using paleoclimate or climate geographic information systems (GIS) databases.19-2021 | 0.00171.4 |
Analyze historical climate information, such as precipitation or temperature records, to help predict future weather or climate trends.19-2021 | 0.00171.4 |
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 |
|---|---|
Develop or use mathematical or computer models for weather forecasting.O*NET Task ID 20208 | 1.0 |
Prepare scientific atmospheric or climate reports, articles, or texts.O*NET Task ID 20211 | 1.0 |
Speak to the public to discuss weather topics or answer questions.O*NET Task ID 21103 | 1.0 |
Develop computer programs to collect meteorological data or to present meteorological information.O*NET Task ID 21104 | 1.0 |
Broadcast weather conditions, forecasts, or severe weather warnings to the public via television, radio, or the Internet or provide this information to the news media.O*NET Task ID 9068 | 0.5 |
Gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts.O*NET Task ID 9069 | 0.5 |
Prepare forecasts or briefings to meet the needs of industry, business, government, or other groups.O*NET Task ID 9070 | 0.5 |
Direct forecasting services at weather stations or at radio or television broadcasting facilities.O*NET Task ID 9076 | 0.5 |
Conduct numerical simulations of climate conditions to understand and predict global or regional weather patterns.O*NET Task ID 9079 | 0.5 |
Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.O*NET Task ID 9083 | 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