# Human Factors Engineers and Ergonomists

> 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.

- **SOC code:** 17-2112.01
- **Canonical URL:** https://singulariki.com/roles/role-17-2112-01
- **Also known as:** Engineer, Ergonomist, Human Factors Engineer, Occupational Ergonomist, Board Certified Ergonomist, Certified Professional Ergonomist, Cognitive Engineer, Ergonomic Consultant
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Collect data through direct observation of work activities or witnessing the conduct of tests.
- Conduct interviews or surveys of users or customers to collect information on topics, such as requirements, needs, fatigue, ergonomics, or interfaces.
- Advocate for end users in collaboration with other professionals, including engineers, designers, managers, or customers.
- Inspect work sites to identify physical hazards.
- Prepare reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities, such as testing, investigation, or validation.
- Recommend workplace changes to improve health and safety, using knowledge of potentially harmful factors, such as heavy loads or repetitive motions.
- Perform functional, task, or anthropometric analysis, using tools, such as checklists, surveys, videotaping, or force measurement.
- 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.
- Assess the user-interface or usability characteristics of products.
- Establish system operating or training requirements to ensure optimized human-machine interfaces.
- Integrate human factors requirements into operational hardware.
- Review health, safety, accident, or worker compensation records to evaluate safety program effectiveness or to identify jobs with high incidence of injury.

**Emerging tasks** (O*NET):
- Assess systems to identify and quantify risk factors.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Psychology _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Speaking _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Complex Problem Solving _(transferable_skill)_
- English Language _(knowledge)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_

**Skills in demand:**
- Psychology _(Specialized Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- English Language _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Listening _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Active Learning _(Common Skill)_
- Mathematics _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Adobe Creative Cloud software _(hot technology)_
- Adobe Illustrator _(hot technology)_
- Adobe InDesign _(hot technology)_
- Adobe Photoshop _(hot technology)_
- AJAX _(hot technology)_
- Apple Safari _(hot technology)_
- Atlassian JIRA _(hot technology)_
- Autodesk AutoCAD _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 81st percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 80th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 75th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 81st percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 18th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 11.0% growth (Growing fast); 25.2k annual openings; 351.1k → 389.6k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $101,140; 350,230 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 10% automation, 57% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Investigate theoretical or conceptual issues, such as the human design considerations of lunar landers or habitats. _(1.5% of measured AI use; learning)_
- Operate testing equipment, such as heat stress meters, octave band analyzers, motion analysis equipment, inclinometers, light meters, velometers, sling psychrometers, or colormetric detection tubes. _(0.6% of measured AI use; learning)_
- Analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation. _(0.3% of measured AI use)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me investigate theoretical or conceptual issues, such as the human design considerations of lunar landers or habitats.
- Help me operate testing equipment, such as heat stress meters, octave band analyzers, motion analysis equipment, inclinometers, light meters, velometers, sling psychrometers, or colormetric detection tubes.
- Help me analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-17-2112-01_