गेमिंग प्रबंधक
प्रबंधनAI एक्सपोजर
- डेटा स्रोत: BLSप्रकाशन: 2026-08
उच्च· 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
0.32
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 64% 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 % |
|---|---|---|
Explain and interpret house rules, such as game rules or betting limits.11-9071 | 0.004368.3 | —0 |
Market or promote the casino to bring in business.11-9071 | 0.002031.7 | 0.003648.0 |
Resolve customer complaints regarding problems such as payout errors. | —0 | 0.003952.0 |
| Not observed on any surface — 16 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. | ||
Remove suspected cheaters, such as card counters or other players who may have systems that shift the odds of winning to their favor. | —0 | —0 |
Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games. | —0 | —0 |
Train new workers or evaluate their performance. | —0 | —0 |
Circulate among gaming tables to ensure that operations are conducted properly, that dealers follow house rules, or that players are not cheating. | —0 | —0 |
Monitor staffing levels to ensure that games and tables are adequately staffed for each shift, arranging for staff rotations and breaks and locating substitute employees as necessary. | —0 | —0 |
Interview and hire workers. | —0 | —0 |
Prepare work schedules and station arrangements and keep attendance records. | —0 | —0 |
Direct the distribution of complimentary hotel rooms, meals, or other discounts or free items given to players, based on their length of play and betting totals. | —0 | —0 |
Establish policies on issues such as the type of gambling offered and the odds, the extension of credit, or the serving of food and beverages. | —0 | —0 |
Track supplies of money to tables and perform any required paperwork. | —0 | —0 |
Set and maintain a bank and table limit for each game. | —0 | —0 |
Review operational expenses, budget estimates, betting accounts, or collection reports for accuracy. | —0 | —0 |
Monitor credit extended to players. | —0 | —0 |
Record, collect, or pay off bets, issuing receipts as necessary. | —0 | —0 |
Direct the compilation of summary sheets that show wager amounts and payoffs for races or events. | —0 | —0 |
Notify board attendants of table vacancies so that waiting patrons can play. | —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 |
|---|---|
Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games.O*NET Task ID 7187 | 1.0 |
Explain and interpret house rules, such as game rules or betting limits.O*NET Task ID 7190 | 1.0 |
Prepare work schedules and station arrangements and keep attendance records.O*NET Task ID 7193 | 1.0 |
Track supplies of money to tables and perform any required paperwork.O*NET Task ID 7196 | 1.0 |
Set and maintain a bank and table limit for each game.O*NET Task ID 7197 | 1.0 |
Direct the compilation of summary sheets that show wager amounts and payoffs for races or events.O*NET Task ID 7201 | 1.0 |
Resolve customer complaints regarding problems, such as payout errors.O*NET Task ID 7185 | 0.5 |
Train new workers or evaluate their performance.O*NET Task ID 7188 | 0.5 |
Monitor staffing levels to ensure that games and tables are adequately staffed for each shift, arranging for staff rotations and breaks and locating substitute employees as necessary.O*NET Task ID 7191 | 0.5 |
Interview and hire workers.O*NET Task ID 7192 | 0.5 |
Remove suspected cheaters, such as card counters or other players who may have systems that shift the odds of winning to their favor.O*NET Task ID 7186 | 0.0 |
Circulate among gaming tables to ensure that operations are conducted properly, that dealers follow house rules, or that players are not cheating.O*NET Task ID 7189 | 0.0 |
Record, collect, or pay off bets, issuing receipts as necessary.O*NET Task ID 7200 | 0.0 |
Notify board attendants of table vacancies so that waiting patrons can play.O*NET Task ID 7202 | 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