Gerentes de Jogos
GestãoExposição à IA
- Fonte dos dados: BLSPublicado: 2026-08
Alto· relativa
BaixoQuatro faixas relativasMuito altoValor por grupo ocupacional
Escala, base e fonte
Quatro faixas relativas (Baixo / Moderado / Alto / Muito alto)
831 ocupações detalhadas da tabela de projeções de emprego do BLS. O valor é atribuído por código da National Employment Matrix (NEM), pelo que as ocupações que partilham um código NEM recebem a mesma banda
- Fonte dos dados: AnthropicPublicado: 2026-03
0.000
0.000Intervalo dos valores aqui apresentados0.745Escala, base e fonte
Índice de exposição observada, 0–1 tal como publicado
Mapeado sobre tarefas O*NET
- Fonte dos dados: ILOPublicado: 2025
0.32
0.09Intervalo dos valores aqui apresentados0.70Valor por grupo ocupacional
Escala, base e fonte
Índice de exposição à IA generativa, 0–1 tal como publicado
Grupo de base CITP-08 — todas as ocupações com o mesmo código recebem este valor
Calculado por este site, não publicado pela OIT: das 1.012 ocupações que este site liga ao conjunto de dados da OIT, 64% atingem ou superam este valor.
Que tipo de valor esta fonte publica
A categoria de BLS é uma posição relativa, não um nível absoluto, e também não é uma medição de primeira mão: agrupa em quatro faixas as posições percentis da ocupação em vários estudos publicados. Não é uma previsão de emprego ou de salários, não é uma probabilidade de adoção e não distingue automação de aumento.
Task-level exposure
Apenas tarefas expostas| 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