Maquilladores
Artes, Diseño, Entretenimiento y MediosExposición a la IA
- Fuente de datos: BLSPublicado: 2026-08
Moderado· relativa
BajoCuatro bandas relativasMuy altoValor por grupo ocupacional
Escala, base y fuente
Cuatro bandas relativas (Bajo / Moderado / Alto / Muy alto)
831 ocupaciones detalladas de la tabla de proyecciones de empleo de BLS. El valor se asigna por código de la National Employment Matrix (NEM), de modo que las ocupaciones que comparten un código NEM reciben la misma banda
- Fuente de datos: AnthropicPublicado: 2026-03
0.000
0.000Rango de los valores aquí recogidos0.745Escala, base y fuente
Índice de exposición observada, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
- Fuente de datos: ILOPublicado: 2025
0.18
0.09Rango de los valores aquí recogidos0.70Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición a la IA generativa, 0–1 tal como se publica
Grupo primario de la CIUO-08 — todas las ocupaciones con ese código reciben este valor
Calculado por este sitio, no publicado por la OIT: de las 1012 ocupaciones que este sitio vincula al conjunto de datos de la OIT, un 90% alcanza o supera este valor.
Qué tipo de cifra publica esta fuente
La categoría de BLS es un rango relativo, no un nivel absoluto, y tampoco es una medición de primera mano: agrupa en cuatro bandas los rangos percentiles de la ocupación en varios estudios publicados. No es una previsión de empleo ni de salarios, no es una probabilidad de adopción y no distingue entre automatización y aumento.
Task-level exposure
| Task | APIRaw / share % |
|---|---|
Confer with stage or motion picture officials and performers to determine desired effects.39-5091 | 0.00000.0 |
| Not observed on any surface — 21 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. | |
Duplicate work precisely to replicate characters' appearances on a daily basis. | —0 |
Establish budgets, and work within budgetary limits. | —0 |
Apply makeup to enhance or alter the appearance of people appearing in productions such as movies. | —0 |
Alter or maintain makeup during productions as necessary to compensate for lighting changes or to achieve continuity of effect. | —0 |
Select desired makeup shades from stock, or mix oil, grease, and coloring to achieve specific color effects. | —0 |
Cleanse and tone the skin to prepare it for makeup application. | —0 |
Assess performers' skin type to ensure that makeup will not cause break-outs or skin irritations. | —0 |
Analyze a script, noting events that affect each character's appearance, so that plans can be made for each scene. | —0 |
Requisition or acquire needed materials for special effects, including wigs, beards, and special cosmetics. | —0 |
Write makeup sheets and take photos to document specific looks and the products used to achieve the looks. | —0 |
Examine sketches, photographs, and plaster models to obtain desired character image depiction. | —0 |
Attach prostheses to performers and apply makeup to create special features or effects, such as scars, aging, or illness. | —0 |
Evaluate environmental characteristics, such as venue size and lighting plans, to determine makeup requirements. | —0 |
Design rubber or plastic prostheses that can be used to change performers' appearances. | —0 |
Create character drawings or models, based upon independent research, to augment period production files. | —0 |
Study production information, such as character descriptions, period settings, and situations, to determine makeup requirements. | —0 |
Provide performers with makeup removal assistance after performances have been completed. | —0 |
Demonstrate products to clients, and provide instruction in makeup application. | —0 |
Clean supplies such as makeup brushes. | —0 |
Advise hairdressers on the hairstyles required for character parts. | —0 |
Wash and reset wigs. | —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 |
|---|---|
Study production information, such as character descriptions, period settings, and situations, to determine makeup requirements.O*NET Task ID 14814 | 1.0 |
Duplicate work precisely to replicate characters' appearances on a daily basis.O*NET Task ID 14798 | 0.5 |
Establish budgets, and work within budgetary limits.O*NET Task ID 14799 | 0.5 |
Apply makeup to enhance or alter the appearance of people appearing in productions such as movies.O*NET Task ID 14800 | 0.5 |
Alter or maintain makeup during productions as necessary to compensate for lighting changes or to achieve continuity of effect.O*NET Task ID 14801 | 0.5 |
Analyze a script, noting events that affect each character's appearance, so that plans can be made for each scene.O*NET Task ID 14805 | 0.5 |
Write makeup sheets and take photos to document specific looks and the products used to achieve the looks.O*NET Task ID 14807 | 0.5 |
Examine sketches, photographs, and plaster models to obtain desired character image depiction.O*NET Task ID 14808 | 0.5 |
Attach prostheses to performers and apply makeup to create special features or effects, such as scars, aging, or illness.O*NET Task ID 14809 | 0.5 |
Evaluate environmental characteristics, such as venue size and lighting plans, to determine makeup requirements.O*NET Task ID 14810 | 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page