数据科学家

计算机与数学

AI暴露度

  • 数据来源: BLS发布时间: '26.08

    很高· 相对

    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

    来源数据集(XLSX 文件下载)

  • 数据来源: Anthropic发布时间: '26.03

    0.461

    0.000此处所载数值的范围0.745
    尺度 · 母数 · 来源

    观测暴露度指数,按发布原值0–1

    以O*NET任务映射为基准

    来源数据集

  • 数据来源: ILO发布时间: '25

    0.57

    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 7%。

    来源数据集

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

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.

TaskβE1 + 0.5 × E2
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.

O*NET Task ID 21824

1.0
Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.

O*NET Task ID 21825

1.0
Clean and manipulate raw data using statistical software.

O*NET Task ID 21826

1.0
Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.

O*NET Task ID 21827

1.0
Design surveys, opinion polls, or other instruments to collect data.

O*NET Task ID 21830

1.0
Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.

O*NET Task ID 21834

1.0
Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.

O*NET Task ID 21837

1.0
Write new functions or applications in programming languages to conduct analyses.

O*NET Task ID 21838

1.0
Analyze, manipulate, or process large sets of data using statistical software.

O*NET Task ID 21823

0.5
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.

O*NET Task ID 21828

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®, 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4月: Bank of Korea research shows junior knowledge workers (≤5 years experience) face 4.0% work hour reduction from AI vs 2.9% for 21+ year veterans. Youth jobs in AI-exposed sectors declined 98.6% of 2.11M total losses (2022-2025).

[来源: Bank of Korea Employment Research (2025)]

2026年3月: BLS projects 36% growth in data scientist roles through 2034, highest among tech occupations

[来源: U.S. Bureau of Labor Statistics]

2026年3月: Dallas Fed: Data scientists classified as high AI-exposure occupation. Wage premiums rising as AI amplifies analytical productivity for experienced workers.

[来源: Dallas Fed (Feb 2026)]