← Risk register SOC 19-3093 · reviewed 2026-08-11

Historians

3,450 US workers · median $76,750/yr · Science

EXPOSED

The bulk of a historian's paid day is reading, summarizing, synthesizing secondary literature, drafting narrative text, and preparing exhibit copy, reports, or background briefs — exactly the work large language models already do at usable quality and enormous speed. What resists is physical archival work: locating and handling uncatalogued manuscripts, reading damaged or handwritten primary sources in context, authenticating provenance, and standing behind an interpretive claim under professional or legal scrutiny. There is no license, no signature requirement, and a tiny national headcount (about 3,450), so most employed historians work in government, consulting, museums, or historic preservation rather than pure scholarship — and those roles pay for defensible judgment, not prose volume.

10-year outlook: By 2035 the writing-and-synthesis half of the job is largely machine-assisted, and the paid roles concentrate in compliance history, provenance, and litigation support where a named human must defend the finding.

Score — 36/100 resistance

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 8 + 6 + 4 + 8 + 10 = 36.

Task resistance 8/20

Mixed — a routine tier and a judgment tier. How much of the day-to-day work current AI already does at usable quality.

Embodiment 6/20

Some physical or field component. Physical work in unpredictable environments. Robotics lags language models badly.

Liability shield 4/20

No licence, no signature requirement. Is a licensed human legally required to sign, and personally liable if it goes wrong?

Trust premium 8/20

Some relationship component. Do buyers specifically pay for a human — presence, care, accountability?

Judgment & accountability 10/20

Meaningful discretion. Does the role own consequential calls made with incomplete information?

This verdict was revised after a second scoring. Two independent runs of the same rubric returned 32/100 and 40/100. The score above is their average, and the change of label held whichever way the rounding went — so it reflects the two runs genuinely disagreeing with the first published number, not a rounding artefact.

Confidence: medium · reviewed 2026-08-11 · how scoring works

Tasks already automatable

What survives

Active moats: judgment, embodiment

How to future-proof this job

Training paths for your skill gaps: Systems analysis & design partner link

Escape hatches — adjacent fields with better verdicts

Computed from U.S. Dept. of Labor O*NET skill profiles: high overlap with what you already do, materially higher resistance score.

Anthropologists and Archeologists EXPOSED · 51/100 · you already have ~79% of the skill profile

Skills to close: Mathematics, Systems Analysis, Systems Evaluation, Management of Personnel Resources

Anthropology and Archeology Teachers, Postsecondary EXPOSED · 51/100 · you already have ~78% of the skill profile

Skills to close: Instructing, Learning Strategies, Science, Monitoring

History Teachers, Postsecondary EXPOSED · 47/100 · you already have ~78% of the skill profile

Skills to close: Instructing, Learning Strategies, Time Management, Systems Analysis

Field report — do you do this job?

Has AI actually changed your work?

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

From people who do this job

Nobody has filed one yet. If you do this work, you know things the rubric can't see.

What has actually changed in your work?

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.