大气科学家
生命、物理与社会科学AI暴露度
- 数据来源: BLS发布时间: 2026-08
很高· 相对
低四级相对区间很高职业群单位数值
尺度 · 母数 · 来源
四级相对类别(低 / 中等 / 高 / 很高)
以BLS就业预测表中831个细分职业为基数。取值按 NEM(全国就业矩阵)代码给定,因此共用同一 NEM 代码的职业得到相同分档
- 数据来源: Anthropic发布时间: 2026-03
0.038
0.000此处所载数值的范围0.745尺度 · 母数 · 来源
- 数据来源: ILO发布时间: 2025
0.54
0.09此处所载数值的范围0.70职业群单位数值
尺度 · 母数 · 来源
生成式AI暴露度指数,按发布原值0–1
ISCO-08职业小类单位 — 共用同一代码的职业取值相同
本站计算,并非国际劳工组织发布的数值。在本站与 ILO 数据集相连的 1,012 个职业中,达到或高于此值的占 13%。
该来源发布的是什么性质的数值
BLS的类别是相对排位而非绝对水平,也不是一手测量:它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测,不是采用概率,也不区分自动化与增强。
Task-level exposure
仅显示有暴露的工作| Task | Claude.aiRaw / share % | APIRaw / 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 | 0.020735.0 | —0 |
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 | 0.012120.4 | 0.004466.7 |
Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate.19-2021 | 0.007412.5 | 0.002233.3 |
Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.19-2021 | 0.00508.4 | —0 |
Prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics.19-2021 | 0.00447.4 | —0 |
Prepare scientific atmospheric or climate reports, articles, or texts.19-2021 | 0.00427.1 | —0 |
Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information.19-2021 | 0.00203.4 | —0 |
Consult with other offices, agencies, professionals, or researchers regarding the use and interpretation of climatological information for weather predictions and warnings.19-2021 | 0.00183.0 | —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.19-2021 | 0.00162.7 | —0 |
| Not observed on any surface — 15 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. | ||
Prepare forecasts or briefings to meet the needs of industry, business, government, or other groups. | —0 | —0 |
Measure wind, temperature, and humidity in the upper atmosphere, using weather balloons. | —0 | —0 |
Direct forecasting services at weather stations or at radio or television broadcasting facilities. | —0 | —0 |
Conduct numerical simulations of climate conditions to understand and predict global or regional weather patterns. | —0 | —0 |
Analyze climate data sets, using techniques such as geophysical fluid dynamics, data assimilation, or numerical modeling. | —0 | —0 |
Perform managerial duties, such as creating work schedules, creating or implementing staff training, matching staff expertise to situations, or analyzing performance of offices. | —0 | —0 |
Analyze historical climate information, such as precipitation or temperature records, to help predict future weather or climate trends. | —0 | —0 |
Apply meteorological knowledge to issues such as global warming, pollution control, or ozone depletion. | —0 | —0 |
Develop or use mathematical or computer models for weather forecasting. | —0 | —0 |
Research the impact of industrial projects or pollution on climate, air quality, or weather phenomena. | —0 | —0 |
Collect air samples from planes or ships over land or sea to study atmospheric composition. | —0 | —0 |
Conduct wind assessment, integration, or validation studies. | —0 | —0 |
Create visualizations to illustrate historical or future changes in the Earth's climate, using paleoclimate or climate geographic information systems (GIS) databases. | —0 | —0 |
Estimate or predict the effects of global warming over time for specific geographic regions. | —0 | —0 |
Teach college-level courses on topics such as atmospheric and space science, meteorology, or global climate change. | —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 |
|---|---|
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 |
Measure wind, temperature, and humidity in the upper atmosphere, using weather balloons.O*NET Task ID 9074 | 0.0 |
Collect air samples from planes or ships over land or sea to study atmospheric composition.O*NET Task ID 9078 | 0.0 |
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