Human Factors Engineers and Ergonomists
Architecture and Engineering Occupations- رمز O*NET-SOC
- 17-2112.01
Design objects, facilities, and environments to optimize human well-being and overall system performance, applying theory, principles, and data regarding the relationship between humans and respective technology. Investigate and analyze characteristics of human behavior and performance as it relates to the use of technology.
تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.
التعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
مرتفع جدًا· نسبي
منخفضأربع فئات نسبيةمرتفع جدًاقيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
أربع فئات نسبية (منخفض / متوسط / مرتفع / مرتفع جدًا)
831 مهنة تفصيلية في جدول توقعات التوظيف لدى BLS. وتُسند القيمة على مستوى رمز مصفوفة التوظيف الوطنية (NEM)، فالمهن التي تشترك في الرمز نفسه تأخذ النطاق نفسه
- مصدر البيانات: Anthropicتاريخ النشر: 2026-03
0.037
0.000نطاق القيم المعروضة هنا0.745قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض المرصود، 0–1 كما نُشر
مربوط بمهام O*NET
منشورة لكل مهنة في SOC 2018؛ وكل مهنة في O*NET تحمل رمز SOC 2018 نفسه تأخذ هذه القيمة
- مصدر البيانات: ILOتاريخ النشر: 2025
0.37
0.09نطاق القيم المعروضة هنا0.70قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر
قيمة منشورة على مستوى مجموعة الوحدة في ISCO-08. رُبطت بهذه المهنة بتطبيق جداول التناظر الرسمية لمكتب إحصاءات العمل الأمريكي (BLS) (من ISCO-08 إلى SOC 2010، ومن SOC 2010 إلى SOC 2018) كما نُشرت، والتناظر كلي أو جزئي
ما نوع القيمة التي ينشرها هذا المصدر
فئة BLS رتبة نسبية لا مستوى مطلق، وليست قياسًا مباشرًا: فهي تجمع الرتب المئينية للمهنة في عدة دراسات منشورة في أربع فئات. وهي ليست توقّعًا للتوظيف أو الأجور، ولا احتمالًا للتبني، ولا تفرّق بين الأتمتة والتعزيز.
التعرض للذكاء الاصطناعي (معيار OpenAI)
26 مهمة مقيَّمة · 23 مهمة بقيمة β ≥ 0.5 (88.5%)
β = التعرّض المباشر (E1) + 0.5 × التعرّض عند توفر الأدوات (E2)، وفق تعريف المستودع المصدري.
- وحدة المصدر: مهام O*NET 27.2 ← رمز المهنة في O*NET 31.0
- جميع المهام المقيَّمة موجودة في قائمة مهام O*NET 31.0.
- المصدر
- OpenAI "GPTs are GPTs" exposure rubric
- الإصدار
- gh-main-0471612
- الترخيص
- MIT License, Copyright (c) 2024 OpenAI
المهام
أوصاف المهام من O*NET® 31.0 Database، والمهام الأساسية أولًا.
| المهمة | النوع | β (OpenAI) |
|---|---|---|
| Write, review, or comment on documents, such as proposals, test plans, or procedures. | أساسية | 1 |
| Train users in task techniques or ergonomic principles. | أساسية | 0 |
| Review health, safety, accident, or worker compensation records to evaluate safety program effectiveness or to identify jobs with high incidence of injury. | أساسية | 0.5 |
| Provide human factors technical expertise on topics, such as advanced user-interface technology development or the role of human users in automated or autonomous sub-systems in advanced vehicle systems. | أساسية | 0.5 |
| Investigate theoretical or conceptual issues, such as the human design considerations of lunar landers or habitats. | أساسية | 0.5 |
| Estimate time or resource requirements for ergonomic or human factors research or development projects. | أساسية | 0.5 |
| Conduct interviews or surveys of users or customers to collect information on topics, such as requirements, needs, fatigue, ergonomics, or interfaces. | أساسية | 1 |
| Recommend workplace changes to improve health and safety, using knowledge of potentially harmful factors, such as heavy loads or repetitive motions. | أساسية | 0.5 |
| Provide technical support to clients through activities, such as rearranging workplace fixtures to reduce physical hazards or discomfort or modifying task sequences to reduce cycle time. | أساسية | 0.5 |
| Prepare reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities, such as testing, investigation, or validation. | أساسية | 1 |
| Perform statistical analyses, such as social network pattern analysis, network modeling, discrete event simulation, agent-based modeling, statistical natural language processing, computational sociology, mathematical optimization, or systems dynamics. | أساسية | 1 |
| Perform functional, task, or anthropometric analysis, using tools, such as checklists, surveys, videotaping, or force measurement. | أساسية | 0.5 |
| Operate testing equipment, such as heat stress meters, octave band analyzers, motion analysis equipment, inclinometers, light meters, thermoanemometers, sling psychrometers, or colorimetric detection tubes. | أساسية | 0 |
| Integrate human factors requirements into operational hardware. | أساسية | 0 |
| Establish system operating or training requirements to ensure optimized human-machine interfaces. | أساسية | 0.5 |
| Inspect work sites to identify physical hazards. | أساسية | 0.5 |
| Develop or implement human performance research, investigation, or analysis protocols. | أساسية | 0.5 |
| Develop or implement research methodologies or statistical analysis plans to test and evaluate developmental prototypes used in new products or processes, such as cockpit designs, user workstations, or computerized human models. | أساسية | 0.5 |
| Design cognitive aids, such as procedural storyboards or decision support systems. | أساسية | 0.5 |
| Conduct research to evaluate potential solutions related to changes in equipment design, procedures, manpower, personnel, or training. | أساسية | 0.5 |
| Assess the user-interface or usability characteristics of products. | أساسية | 0.5 |
| Collect data through direct observation of work activities or witnessing the conduct of tests. | أساسية | 0.5 |
| Apply modeling or quantitative analysis to forecast events, such as human decisions or behaviors, the structure or processes of organizations, or the attitudes or actions of human groups. | أساسية | 0.5 |
| Analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation. | أساسية | 0.5 |
| Advocate for end users in collaboration with other professionals, including engineers, designers, managers, or customers. | أساسية | 0.5 |
| Design or evaluate human work systems, using human factors engineering and ergonomic principles to optimize usability, cost, quality, safety, or performance. | أساسية | 0.5 |
معلومات مهنية
المصادر والإسناد
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: 17-2112.01 Human Factors Engineers and Ergonomists
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.