History

What the occupations pay

Median annual wage across the occupations this field of study leads to, from BLS OEWS (national, cross-industry, May 2024). The middle range is the 25th–75th percentile of those occupation medians — it describes the field, not any one job or graduate.

AI exposure of this field of study

Two published studies estimate how exposed each occupation is to today's AI. The OpenAI "GPTs are GPTs" study rates the share of an occupation's tasks a large language model (with tools) could speed up by half or more; averaged across the occupations this field of study leads to it is 43% — 45th percentile of all fields of study. The independent Felten/Raj/Seamans AI Occupational Exposure index averages 0.86 here.

Computed across the 9 of 9 occupations this field leads to that carry a published exposure score.

The most-exposed fields of study lead to knowledge, language and analytical work; the least-exposed lead to physical trades and hands-on production. Exposure measures where AI could assist tasks, not a prediction that these jobs will be automated; high exposure most often means augmentation. Bands are comparable across the cluster, education, job-zone and field-of-study tiers (same two studies, same percentile method).

Where this field of study leads

The largest occupations connected to this field by the CIP–SOC crosswalk, by employment. Wage and employment describe the occupation, not an individual.

Programs in this field

A sample of the detailed CIP programs within this family. The full family contains 9 programs.

• 54.0102 American History (United States)
• 54.0106 Asian History
• 54.0107 Canadian History
• 54.0103 European History
• 54.0104 History and Philosophy of Science and Technology
• 54.0101 History, General
• 54.0199 History, Other
• 54.0108 Military History
• 54.0105 Public/Applied History

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
• BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
• CIP-2020 2020 U.S. National Center for Education Statistics
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
• AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic

Data compiled June 3, 2026. Figures are estimates, not advice.

@misc{singulariki-history,
  title  = {History},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; CIP-2020 2020; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
  url    = {https://singulariki.com/programs/history}
}