软件QA分析师
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
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
0.519
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
0.53
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 14%。
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 18 项工作| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Identify, analyze, and document problems with program function, output, online screen, or content.15-1253 | 0.910071.1 | 1.620068.6 |
Modify existing software to correct errors, allow it to adapt to new hardware, or to improve its performance.15-1253 | 0.190014.8 | 0.340014.4 |
Provide feedback and recommendations to developers on software usability and functionality.15-1253 | 0.07005.5 | 0.02000.8 |
Collaborate with field staff or customers to evaluate or diagnose problems and recommend possible solutions.15-1253 | 0.04003.1 | 0.01000.4 |
Monitor program performance to ensure efficient and problem-free operations.15-1253 | 0.03002.3 | 0.20008.5 |
Identify program deviance from standards, and suggest modifications to ensure compliance.15-1253 | 0.02001.6 | 0.03001.3 |
Perform initial debugging procedures by reviewing configuration files, logs, or code pieces to determine breakdown source.15-1253 | 0.01000.8 | 0.07003.0 |
Store, retrieve, and manipulate data for analysis of system capabilities and requirements.15-1253 | 0.01000.8 | 0.02000.8 |
Test system modifications to prepare for implementation.15-1253 | 0.00000.0 | 0.02000.8 |
Document software defects, using a bug tracking system, and report defects to software developers.15-1253 | 0.00000.0 | 0.01000.4 |
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 |
|---|---|
Design test plans, scenarios, scripts, or procedures.O*NET Task ID 14638 | 1.0 |
Test system modifications to prepare for implementation.O*NET Task ID 14639 | 1.0 |
Develop testing programs that address areas such as database impacts, software scenarios, regression testing, negative testing, error or bug retests, or usability.O*NET Task ID 14640 | 1.0 |
Document software defects, using a bug tracking system, and report defects to software developers.O*NET Task ID 14641 | 1.0 |
Identify, analyze, and document problems with program function, output, online screen, or content.O*NET Task ID 14642 | 1.0 |
Monitor bug resolution efforts and track successes.O*NET Task ID 14643 | 1.0 |
Create or maintain databases of known test defects.O*NET Task ID 14644 | 1.0 |
Plan test schedules or strategies in accordance with project scope or delivery dates.O*NET Task ID 14645 | 1.0 |
Review software documentation to ensure technical accuracy, compliance, or completeness, or to mitigate risks.O*NET Task ID 14647 | 1.0 |
Document test procedures to ensure replicability and compliance with standards.O*NET Task ID 14648 | 1.0 |
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