Gaming-Manager
ManagementKI-Exposition
- Datenquelle: BLSVeröffentlicht: 2026-08
Hoch· relativ
NiedrigVier relative BänderSehr hochWert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)
831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band
- Datenquelle: AnthropicVeröffentlicht: 2026-03
0.000
0.000Spannweite der hier geführten Werte0.745Skala, Bezugsmenge und Quelle
Index der beobachteten Exposition, 0–1 wie veröffentlicht
Auf O*NET-Aufgaben abgebildet
- Datenquelle: ILOVeröffentlicht: 2025
0.32
0.09Spannweite der hier geführten Werte0.70Wert auf Berufsgruppenebene
Skala, Bezugsmenge und Quelle
Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht
ISCO-08-Berufsgattung — alle Berufe mit demselben Code erhalten diesen Wert
Von dieser Website berechnet, nicht von der IAO veröffentlicht: Von den 1.012 Berufen, die diese Website mit dem IAO-Datensatz verknüpft, erreichen oder übertreffen 64% diesen Wert.
Welche Art von Wert diese Quelle veröffentlicht
Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.
Task-level exposure
Nur exponierte Aufgaben| Task | APIRaw / share % |
|---|---|
Resolve customer complaints regarding problems such as payout errors.11-9071 | 0.010684.0 |
Market or promote the casino to bring in business.11-9071 | 0.002016.0 |
| Not observed on any surface — 17 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 |
Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games. | —0 |
Train new workers or evaluate their performance. | —0 |
Circulate among gaming tables to ensure that operations are conducted properly, that dealers follow house rules, or that players are not cheating. | —0 |
Explain and interpret house rules, such as game rules or betting limits. | —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 |
Interview and hire workers. | —0 |
Prepare work schedules and station arrangements and keep attendance records. | —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 |
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 |
Track supplies of money to tables and perform any required paperwork. | —0 |
Set and maintain a bank and table limit for each game. | —0 |
Review operational expenses, budget estimates, betting accounts, or collection reports for accuracy. | —0 |
Monitor credit extended to players. | —0 |
Record, collect, or pay off bets, issuing receipts as necessary. | —0 |
Direct the compilation of summary sheets that show wager amounts and payoffs for races or events. | —0 |
Notify board attendants of table vacancies so that waiting patrons can play. | —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