酒店前台接待员
食品准备与服务AI暴露度
- 数据来源: BLS发布时间: 2026-08
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: 2026-03
0.172
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
0.51
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 17%。
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 4 项工作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 |
|---|---|
Post charges, such as those for rooms, food, liquor, or telephone calls, to ledgers, manually or by using computers.O*NET Task ID 2617 | 1.0 |
Transmit and receive messages, using telephones or telephone switchboards.O*NET Task ID 2618 | 1.0 |
Record guest comments or complaints, referring customers to managers as necessary.O*NET Task ID 2622 | 1.0 |
Date-stamp, sort, and rack incoming mail and messages.O*NET Task ID 2626 | 1.0 |
Greet, register, and assign rooms to guests of hotels or motels.O*NET Task ID 2610 | 0.5 |
Verify customers' credit, and establish how the customer will pay for the accommodation.O*NET Task ID 2611 | 0.5 |
Keep records of room availability and guests' accounts, manually or using computers.O*NET Task ID 2612 | 0.5 |
Compute bills, collect payments, and make change for guests.O*NET Task ID 2613 | 0.5 |
Review accounts and charges with guests during the check out process.O*NET Task ID 2616 | 0.5 |
Contact housekeeping or maintenance staff when guests report problems.O*NET Task ID 2619 | 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