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Will AI replace Social Science Research Assistants?

Assist social scientists in laboratory, survey, and other social science research. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 19-4061.00 · modeled exposure, not guaranteed job loss
LOW TASK EXPOSURE
29%
Estimated share of representative tasks exposed to current AI capabilities.
Last updatedAugust 20, 2026
Evidence confidenceMedium
Browse this risk tierLower exposure jobs →
Task automation shareⓘ
29%Automatable
Automatable29%
Augmentable39%
Hard to automate32%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Healthcare
Clinical & Care
Modeled pay midpoint$
$67,100/yr
Directional estimate — verify locally
Time until impact⌁
6–10+ years
Earliest 2032 · widespread 2036+
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Design and create special programs for tasks such as statistical analysis and data entry and cleaning.39%
⚙Provide assistance with the preparation of project-related reports, manuscripts, and presentations.27%
✦Clinical accountability and hands-on care24%
✦Patient trust and complex diagnosis20%
▥Prepare tables, graphs, fact sheets, and written reports summarizing research results.14%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2032Next2036+
Light supportAI provides limited help with design and create special programs for tasks such as statistical analysis and data entry and cleaning..
AugmentationTools improve productivity without owning outcomes.
Human-ledCore work stays anchored in clinical accountability and hands-on care.
6–10+ yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by Social Science Research Assistants.
02>AI can help with: Design and create special programs for tasks such as statistical analysis and data entry and cleaning.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: Clinical accountability and hands-on care.
05>Likely result: AI mostly acts as a helper while the core job stays human-led.
06>Important: 29% is estimated task exposure—not a 29% chance of losing the job.
What AI can do
Design and create special programs for tasks such as statistical analysis and data entry and cleaning.LOW MATCH
Provide assistance with the preparation of project-related reports, manuscripts, and presentations.LOW MATCH
Prepare tables, graphs, fact sheets, and written reports summarizing research results.LOW MATCH
How estimates work →
Your human moat
◆

Clinical accountability and hands-on care

HIGH MOAT

Combined with patient trust and complex diagnosis, this keeps a human in the loop.

Strength8.7
Similar-role comparison
RoleRisk
Social Science Research Assistants29%
Forensic Science Technicians28%
Veterinary Assistants and Laboratory Animal Caretakers28%
Dental Assistants27%
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Why this score?

✓The model evaluates 3 representative core tasks.
✓The core work depends on presence, dexterity, or accountability.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is clinical accountability and hands-on care.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
Data: O*NET 30.3 · Model framework: ILO 2025O*NET 19-4061.00Share report
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Sources for this report

Official occupation tasks; timeline remains uncertain Scores are directional estimates and sources do not endorse this site’s exact percentage.

O*NET 19-4061.00 occupation profile ↗ILO Generative AI and Jobs 2025 ↗Scoring methodology →

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