急诊医学医师
医疗保健AI暴露度
- 数据来源: BLS发布时间: 2026-08
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: ILO发布时间: 2025
0.27
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 74%。
- 数据来源: OpenAI发布时间: 2023
0.353
0.000此处所载数值的范围0.844尺度 · 母数 · 来源
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 205 项工作| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare comprehensive interpretive reports of findings.29-1069 | 0.027711.9 | 0.01516.3 |
Educate patients about diagnoses, prognoses, or treatments.29-1069 | 0.027411.7 | 0.00341.4 |
Diagnose diseases or study medical conditions using techniques such as gross pathology, histology, cytology, cytopathology, clinical chemistry, immunology, flow cytometry, and molecular biology.29-1069 | 0.02189.3 | 0.026110.8 |
Develop individualized treatment plans for patients, considering patient preferences, clinical data, or the risks and benefits of therapies.29-1069 | 0.02109.0 | 0.025710.6 |
Educate patients about maintenance and promotion of healthy vision.29-1069 | 0.02099.0 | —0 |
Interpret diagnostic test results to make appropriate differential diagnoses.29-1069 | 0.02038.7 | —0 |
Analyze and interpret results from tests such as microbial or parasite tests, urine analyses, hormonal assays, fine needle aspirations (FNAs), and polymerase chain reactions (PCRs).29-1069 | 0.01606.8 | 0.110645.8 |
Conduct research and present scientific findings.29-1069 | 0.01516.5 | 0.00552.3 |
Examine microscopic samples to identify diseases or other abnormalities.29-1069 | 0.01074.6 | 0.00763.2 |
Interpret imaging data and confer with other medical specialists to formulate diagnoses.29-1069 | 0.00522.2 | 0.00582.4 |
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 |
|---|---|
Collect and record patient information, such as medical history or examination results, in electronic or handwritten medical records.O*NET Task ID 22717 | 1.0 |
Analyze records, examination information, or test results to diagnose medical conditions.O*NET Task ID 22715 | 0.5 |
Assess patients' pain levels or sedation requirements.O*NET Task ID 22716 | 0.5 |
Communicate likely outcomes of medical diseases or traumatic conditions to patients or their representatives.O*NET Task ID 22718 | 0.5 |
Conduct primary patient assessments that include information from prior medical care.O*NET Task ID 22719 | 0.5 |
Consult with hospitalists and other professionals, such as social workers, regarding patients' hospital admission, continued observation, transition of care, or discharge.O*NET Task ID 22720 | 0.5 |
Direct and coordinate activities of nurses, assistants, specialists, residents, and other medical staff.O*NET Task ID 22721 | 0.5 |
Discuss patients' treatment plans with physicians and other medical professionals.O*NET Task ID 22722 | 0.5 |
Evaluate patients' vital signs or laboratory data to determine emergency intervention needs and priority of treatment.O*NET Task ID 22723 | 0.5 |
Identify factors that may affect patient management, such as age, gender, barriers to communication, and underlying disease.O*NET Task ID 22724 | 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