抄表员
办公与行政支持AI暴露度
- 数据来源: BLS发布时间: 2026-08
中等· 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
0.000
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
0.38
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 48%。
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 | APIRaw / share % |
|---|---|
Answer customers' questions about services and charges, or direct them to customer service centers.43-5041 | 0.0100100.0 |
Verify readings in cases where consumption appears to be abnormal, and record possible reasons for fluctuations.43-5041 | 0.00000.0 |
| Not observed on any surface — 10 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. | |
Read electric, gas, water, or steam consumption meters and enter data in route books or hand-held computers. | —0 |
Walk or drive vehicles along established routes to take readings of meter dials. | —0 |
Upload into office computers all information collected on hand-held computers during meter rounds, or return route books or hand-held computers to business offices so that data can be compiled. | —0 |
Inspect meters for unauthorized connections, defects, and damage, such as broken seals. | —0 |
Report to service departments any problems, such as meter irregularities, damaged equipment, or impediments to meter access, including dogs. | —0 |
Update client address and meter location information. | —0 |
Leave messages to arrange different times to read meters in cases in which meters are not accessible. | —0 |
Connect and disconnect utility services at specific locations. | —0 |
Perform preventative maintenance or minor repairs on meters. | —0 |
Report lost or broken keys. | —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 |
|---|---|
Upload into office computers all information collected on hand-held computers during meter rounds, or return route books or hand-held computers to business offices so that data can be compiled.O*NET Task ID 11311 | 1.0 |
Answer customers' questions about services and charges, or direct them to customer service centers.O*NET Task ID 11315 | 1.0 |
Update client address and meter location information.O*NET Task ID 11316 | 1.0 |
Leave messages to arrange different times to read meters in cases in which meters are not accessible.O*NET Task ID 11317 | 1.0 |
Read electric, gas, water, or steam consumption meters and enter data in route books or hand-held computers.O*NET Task ID 11309 | 0.5 |
Verify readings in cases where consumption appears to be abnormal, and record possible reasons for fluctuations.O*NET Task ID 11312 | 0.5 |
Collect past-due bills.O*NET Task ID 11319 | 0.5 |
Walk or drive vehicles along established routes to take readings of meter dials.O*NET Task ID 11310 | 0.0 |
Inspect meters for unauthorized connections, defects, and damage, such as broken seals.O*NET Task ID 11313 | 0.0 |
Report to service departments any problems, such as meter irregularities, damaged equipment, or impediments to meter access, including dogs.O*NET Task ID 11314 | 0.0 |
Connect and disconnect utility services at specific locations.O*NET Task ID 11318 | 0.0 |
Report lost or broken keys.O*NET Task ID 11320 | 0.0 |
Perform preventative maintenance or minor repairs on meters.O*NET Task ID 20904 | 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