Analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation.

“Analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation.” is a core task performed by Human Factors Engineers and Ergonomists. Among the occupation's 26 rated tasks, workers place it 5th by importance (#22 most important). About 85% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Research technology designs or applications. in Getting Information

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E2. Exposure with tools — software built on top of a language model (not the model alone) could cut the time by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 0.50. Automation potential label: T1.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.011% share of AI-use records mapped to this task
• 44% of that use is work-related
• Average autonomy of the AI: 3.7 (1–5; higher = more autonomous)
• 88% of interactions still needed a human in the loop

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Other tasks in this occupation

• Collect data through direct observation of work activities or witnessing the conduct of tests. · importance 4.7
• Conduct interviews or surveys of users or customers to collect information on topics, such as requirements, needs, fatigue, ergonomics, or interfaces. · importance 4.5
• Advocate for end users in collaboration with other professionals, including engineers, designers, managers, or customers. · importance 4.5
• Inspect work sites to identify physical hazards. · importance 4.5
• Prepare reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities, such as testing, investigation, or validation. · importance 4.4
• Recommend workplace changes to improve health and safety, using knowledge of potentially harmful factors, such as heavy loads or repetitive motions. · importance 4.4
• Perform functional, task, or anthropometric analysis, using tools, such as checklists, surveys, videotaping, or force measurement. · importance 4.3
• 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. · importance 4.3
• Assess the user-interface or usability characteristics of products. · importance 4.3
• Establish system operating or training requirements to ensure optimized human-machine interfaces. · importance 4.2
• Integrate human factors requirements into operational hardware. · importance 4.2
• Review health, safety, accident, or worker compensation records to evaluate safety program effectiveness or to identify jobs with high incidence of injury. · importance 4.2
• Design or evaluate human work systems, using human factors engineering and ergonomic principles to optimize usability, cost, quality, safety, or performance. · importance 4.2
• Write, review, or comment on documents, such as proposals, test plans, or procedures. · importance 4.2

See all tasks on the Human Factors Engineers and Ergonomists page.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-16395,
  title  = {Analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-16395}
}