经济学家
生命、物理与社会科学AI暴露度
- 数据来源: BLS发布时间: '26.08
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: '26.03
0.242
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: '25
0.55
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 12%。
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
显示隐藏的 19 项工作| Task | Claude.aiRaw / share % |
|---|---|
Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques.19-3011 | 0.119038.1 |
Provide advice and consultation on economic relationships to businesses, public and private agencies, and other employers.19-3011 | 0.053817.2 |
Write technical documents or academic articles to communicate study results or economic forecasts.19-3011 | 0.052916.9 |
Formulate recommendations, policies, or plans to solve economic problems or to interpret markets.19-3011 | 0.041313.2 |
Develop economic models, forecasts, or scenarios to predict future economic and environmental outcomes.19-3011 | 0.01414.5 |
Study economic and statistical data in area of specialization, such as finance, labor, or agriculture.19-3011 | 0.01254.0 |
Interpret indicators to ascertain the overall health of an environment.19-3011 | 0.00421.3 |
Conduct research on economic issues and disseminate research findings through technical reports or scientific articles in journals.19-3011 | 0.00421.3 |
Prepare and deliver presentations to communicate economic and environmental study results, to present policy recommendations, or to raise awareness of environmental consequences.19-3011 | 0.00351.1 |
Supervise research projects and students' study projects.19-3011 | 0.00260.8 |
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 |
|---|---|
Study economic and statistical data in area of specialization, such as finance, labor, or agriculture.O*NET Task ID 7536 | 0.5 |
Provide advice and consultation on economic relationships to businesses, public and private agencies, and other employers.O*NET Task ID 7537 | 0.5 |
Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques.O*NET Task ID 7538 | 0.5 |
Formulate recommendations, policies, or plans to solve economic problems or to interpret markets.O*NET Task ID 7539 | 0.5 |
Develop economic guidelines and standards, and prepare points of view used in forecasting trends and formulating economic policy.O*NET Task ID 7540 | 0.5 |
Testify at regulatory or legislative hearings concerning the estimated effects of changes in legislation or public policy, and present recommendations based on cost-benefit analyses.O*NET Task ID 7541 | 0.5 |
Supervise research projects and students' study projects.O*NET Task ID 7542 | 0.5 |
Forecast production and consumption of renewable resources and supply, consumption, and depletion of non-renewable resources.O*NET Task ID 7543 | 0.5 |
Teach theories, principles, and methods of economics.O*NET Task ID 7544 | 0.5 |
Provide litigation support, such as writing reports for expert testimony or testifying as an expert witness.O*NET Task ID 20051 | 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
Occupation information
与本职业相关的近期变化
2026年3月: New blog post: economists face 60% exposure, 36% risk.
[来源: ACW Blog]