Gerentes de Operaciones de Emergencia
GerenciaExposición a la IA
- Fuente de datos: BLSPublicado: 2026-08
Alto· 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
0.38
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 48% 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
Ver 22 tareas ocultas| Task | Claude.aiRaw / share % |
|---|---|
Prepare plans that outline operating procedures to be used in response to disasters or emergencies, such as hurricanes, nuclear accidents, and terrorist attacks, and in recovery from these events.11-9161 | 0.0017100.0 |
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 |
|---|---|
Keep informed of activities or changes that could affect the likelihood of an emergency, response efforts, or plan implementation.O*NET Task ID 7253 | 0.5 |
Prepare plans that outline operating procedures to be used in response to disasters or emergencies, such as hurricanes, nuclear accidents, and terrorist attacks, and in recovery from these events.O*NET Task ID 7254 | 0.5 |
Propose alteration of emergency response procedures, based on regulatory changes, technological changes, or knowledge gained from outcomes of previous emergency situations.O*NET Task ID 7255 | 0.5 |
Maintain and update all resource materials associated with emergency preparedness plans.O*NET Task ID 7256 | 0.5 |
Coordinate disaster response or crisis management activities, such as ordering evacuations, opening public shelters, and implementing special needs plans and programs.O*NET Task ID 7257 | 0.5 |
Keep informed of federal, state, and local regulations affecting emergency plans, and ensure that plans adhere to those regulations.O*NET Task ID 7259 | 0.5 |
Prepare emergency situation status reports that describe response and recovery efforts, needs, and preliminary damage assessments.O*NET Task ID 7260 | 0.5 |
Design and administer emergency or disaster preparedness training courses that teach people how to effectively respond to major emergencies and disasters.O*NET Task ID 7261 | 0.5 |
Consult with officials of local and area governments, schools, hospitals, and other institutions to determine their needs and capabilities in the event of a natural disaster or other emergency.O*NET Task ID 7263 | 0.5 |
Develop and perform tests and evaluations of emergency management plans in accordance with state and federal regulations.O*NET Task ID 7264 | 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