Photonics Engineers

Architecture and Engineering Occupations
Código O*NET-SOC
17-2199.07

Design technologies specializing in light information or light energy, such as laser or fiber optics technology.

Los nombres de las ocupaciones y las descripciones de tareas se muestran en inglés, tal como se publicaron. Las etiquetas, incluidos los tipos de tarea, están traducidas.

Exposición a la IA

  • Fuente de datos: BLSPublicado: 2026-08

    Muy alto· relativa

    BajoCuatro bandas relativasMuy alto

    Valor 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

    Conjunto de datos de origen (descarga XLSX)

  • Fuente de datos: AnthropicPublicado: 2026-03

    0.066

    0.000Rango de los valores aquí recogidos0.745

    Valor por grupo ocupacional

    Escala, base y fuente

    Índice de exposición observada, 0–1 tal como se publica

    Mapeado sobre tareas de O*NET

    Publicado por ocupación SOC 2018; toda ocupación O*NET con el mismo código SOC 2018 recibe este valor

    Conjunto de datos de origen (descarga CSV)

  • Fuente de datos: ILOPublicado: 2025

    0.30

    0.09Rango de los valores aquí recogidos0.70

    Valor por grupo ocupacional

    Escala, base y fuente

    Índice de exposición a la IA generativa, 0–1 tal como se publica

    Publicado por grupo primario ISCO-08. Vinculado a esta ocupación, total o parcialmente, aplicando tal como se publicaron las tablas de correspondencia de la U.S. Bureau of Labor Statistics (ISCO-08 a SOC 2010, SOC 2010 a SOC 2018)

    Conjunto de datos de origen (descarga PDF)

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.

Exposición a la IA (rúbrica de OpenAI)

26 tareas evaluadas · 20 tareas con β ≥ 0,5 (76.9%)

β = exposición directa (E1) + 0,5 × exposición con herramientas disponibles (E2), según la definición del repositorio de origen.

  • Unidad de origen: tareas de O*NET 27.2 → código de ocupación de O*NET 31.0
  • Todas las tareas puntuadas figuran en la lista de tareas de O*NET 31.0.
Fuente
OpenAI "GPTs are GPTs" exposure rubric
Versión
gh-main-0471612
Licencia
MIT License, Copyright (c) 2024 OpenAI

Tareas

Descripciones de tareas de la O*NET® 31.0 Database, primero las tareas principales.

TareaTipoβ (OpenAI)
Analyze, fabricate, or test fiber-optic links.Principal0
Design electro-optical sensing or imaging systems.Principal0,5
Determine commercial, industrial, scientific, or other uses for electro-optical applications or devices.Principal0,5
Conduct research on new photonics technologies.Principal0,5
Design, integrate, or test photonics systems or components.Principal0
Analyze system performance or operational requirements.Principal0,5
Conduct testing to determine functionality or optimization or to establish limits of photonics systems or components.Principal0,5
Design gas lasers, solid state lasers, infrared, or other light emitting or light sensitive devices.Principal0,5
Determine applications of photonics appropriate to meet product objectives or features.Principal0,5
Develop or test photonic prototypes or models.Principal0
Develop optical or imaging systems, such as optical imaging products, optical components, image processes, signal process technologies, or optical systems.Principal0,5
Assist in the transition of photonic prototypes to production.Principal0,5
Create or maintain photonic design histories.Principal1
Oversee or provide expertise on manufacturing, assembly, or fabrication processes.Principal0
Read current literature, talk with colleagues, continue education, or participate in professional organizations or conferences to keep abreast of developments in the field.Principal0,5
Train operators, engineers, or other personnel.Principal0
Design photonics products, such as light sources, displays, or photovoltaics, to achieve increased energy efficiency.Principal0,5
Write reports or proposals related to photonics research or development projects.Principal1
Document photonics system or component design processes, including objectives, issues, or outcomes.Principal1
Select, purchase, set up, operate, or troubleshoot state-of-the-art laser cutting equipment.Complementaria0
Design laser machining equipment for purposes such as high-speed ablation.Complementaria1
Develop laser-processed designs, such as laser-cut medical devices.Complementaria0,5
Design or develop new crystals for photonics applications.Complementaria1
Design or redesign optical fibers to minimize energy loss.Complementaria1
Design solar energy photonics or other materials or devices to generate energy.Complementaria0,5
Develop photonics sensing or manufacturing technologies to improve the efficiency of manufacturing or related processes.Complementaria0,5

Información ocupacional

Fuentes y atribución

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 17-2199.07 Photonics Engineers

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

Atribución y licencias completas