डाइनिंग रूम परिचारक
खाद्य तैयारी और सेवाAI एक्सपोजर
- डेटा स्रोत: BLSप्रकाशन: 2026-08
कम· सापेक्ष
कमचार सापेक्ष श्रेणियाँबहुत उच्चव्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
चार सापेक्ष बैंड (कम / मध्यम / उच्च / बहुत उच्च)
BLS रोज़गार पूर्वानुमान तालिका के 831 विस्तृत व्यवसायों के आधार पर। मान NEM (नेशनल एम्प्लॉयमेंट मैट्रिक्स) कोड के स्तर पर दिया जाता है, इसलिए एक ही NEM कोड वाले व्यवसायों को वही बैंड मिलता है
- डेटा स्रोत: Anthropicप्रकाशन: 2026-03
0.000
0.000यहाँ दिए गए मानों की सीमा0.745मापक्रम, आधार और स्रोत
- डेटा स्रोत: ILOप्रकाशन: 2025
0.24
0.09यहाँ दिए गए मानों की सीमा0.70व्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
जेनरेटिव AI एक्सपोजर सूचकांक, प्रकाशित रूप में 0–1
ISCO-08 यूनिट समूह — समान कोड वाले सभी व्यवसायों को यही मान मिलता है
यह इस साइट की गणना है, ILO द्वारा प्रकाशित आँकड़ा नहीं: इस साइट द्वारा ILO डेटासेट से जोड़े गए 1,012 व्यवसायों में से 79% इस मान के बराबर या उससे अधिक हैं।
यह स्रोत किस प्रकार का आँकड़ा प्रकाशित करता है
BLS की श्रेणी सापेक्ष रैंक है, निरपेक्ष स्तर नहीं, और यह प्रथम-हस्त माप भी नहीं है: यह कई प्रकाशित अध्ययनों में व्यवसाय की पर्सेंटाइल रैंकों को चार बैंडों में बांटती है। यह रोज़गार या वेतन का पूर्वानुमान नहीं है, न अपनाए जाने की संभावना, और यह स्वचालन और संवर्धन में अंतर नहीं करती।
Task-level exposure
केवल एक्सपोज़र वाले कार्य| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Locate items requested by customers.35-9011 | 0.0200100.0 | 0.0100100.0 |
| Not observed on any surface — 22 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. | ||
Wipe tables or seats with dampened cloths or replace dirty tablecloths. | —0 | —0 |
Set tables with clean linens, condiments, or other supplies. | —0 | —0 |
Scrape and stack dirty dishes and carry dishes and other tableware to kitchens for cleaning. | —0 | —0 |
Clean up spilled food or drink or broken dishes and remove empty bottles and trash. | —0 | —0 |
Perform serving, cleaning, or stocking duties in establishments, such as cafeterias or dining rooms, to facilitate customer service. | —0 | —0 |
Maintain adequate supplies of items, such as clean linens, silverware, glassware, dishes, or trays. | —0 | —0 |
Serve ice water, coffee, rolls, or butter to patrons. | —0 | —0 |
Fill beverage or ice dispensers. | —0 | —0 |
Stock cabinets or serving areas with condiments and refill condiment containers. | —0 | —0 |
Carry food, dishes, trays, or silverware from kitchens or supply departments to serving counters. | —0 | —0 |
Serve food to customers when waiters or waitresses need assistance. | —0 | —0 |
Clean and polish counters, shelves, walls, furniture, or equipment in food service areas or other areas of restaurants and mop or vacuum floors. | —0 | —0 |
Carry trays from food counters to tables for cafeteria patrons. | —0 | —0 |
Run cash registers. | —0 | —0 |
Greet and seat customers. | —0 | —0 |
Replenish supplies of food or equipment at steam tables or service bars. | —0 | —0 |
Wash glasses or other serving equipment at bars. | —0 | —0 |
Garnish foods and position them on tables to make them visible and accessible. | —0 | —0 |
Carry linens to or from laundry areas. | —0 | —0 |
Stock refrigerating units with wines or bottled beer or replace empty beer kegs. | —0 | —0 |
Mix and prepare flavors for mixed drinks. | —0 | —0 |
Slice and pit fruit used to garnish drinks. | —0 | —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 |
|---|---|
Wipe tables or seats with dampened cloths or replace dirty tablecloths.O*NET Task ID 11163 | 0.0 |
Set tables with clean linens, condiments, or other supplies.O*NET Task ID 11164 | 0.0 |
Scrape and stack dirty dishes and carry dishes and other tableware to kitchens for cleaning.O*NET Task ID 11165 | 0.0 |
Clean up spilled food or drink or broken dishes and remove empty bottles and trash.O*NET Task ID 11166 | 0.0 |
Perform serving, cleaning, or stocking duties in establishments, such as cafeterias or dining rooms, to facilitate customer service.O*NET Task ID 11167 | 0.0 |
Maintain adequate supplies of items, such as clean linens, silverware, glassware, dishes, or trays.O*NET Task ID 11168 | 0.0 |
Serve ice water, coffee, rolls, or butter to patrons.O*NET Task ID 11169 | 0.0 |
Fill beverage or ice dispensers.O*NET Task ID 11170 | 0.0 |
Stock cabinets or serving areas with condiments and refill condiment containers.O*NET Task ID 11171 | 0.0 |
Locate items requested by customers.O*NET Task ID 11172 | 0.0 |
Carry food, dishes, trays, or silverware from kitchens or supply departments to serving counters.O*NET Task ID 11173 | 0.0 |
Serve food to customers when waiters or waitresses need assistance.O*NET Task ID 11174 | 0.0 |
Clean and polish counters, shelves, walls, furniture, or equipment in food service areas or other areas of restaurants and mop or vacuum floors.O*NET Task ID 11175 | 0.0 |
Carry trays from food counters to tables for cafeteria patrons.O*NET Task ID 11176 | 0.0 |
Replenish supplies of food or equipment at steam tables or service bars.O*NET Task ID 11177 | 0.0 |
Run cash registers.O*NET Task ID 11178 | 0.0 |
Wash glasses or other serving equipment at bars.O*NET Task ID 11179 | 0.0 |
Garnish foods and position them on tables to make them visible and accessible.O*NET Task ID 11180 | 0.0 |
Carry linens to or from laundry areas.O*NET Task ID 11181 | 0.0 |
Stock refrigerating units with wines or bottled beer or replace empty beer kegs.O*NET Task ID 11182 | 0.0 |
Mix and prepare flavors for mixed drinks.O*NET Task ID 11183 | 0.0 |
Slice and pit fruit used to garnish drinks.O*NET Task ID 11184 | 0.0 |
Stock vending machines with food.O*NET Task ID 11185 | 0.0 |
Greet and seat customers.O*NET Task ID 23929 | 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