Science · SOC 19-4061
Most of this role's core tasks — data cleaning, statistical analysis, and report drafting — are directly in AI's current wheelhouse.
Core tasks are highly automatable — expect major disruption.
Timeline: This is one of the higher-risk research-support roles — LLMs already perform most of the data tasks well, and the transition to AI-augmented workflows will likely reshape this job significantly within 3 years.
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AI job-risk card
Social Science Research Assistants is high risk on AIFear. Core tasks are highly automatable — expect major disruption.
AIFear.com
Our AI Fear Score for Social Science Research Assistants is 80/100 (High risk). Core tasks are highly automatable — expect major disruption.
80 out of 100, based on an AI-model review of this occupation's O*NET tasks against what current AI can actually do.
Most exposed: Performing statistical analyses using software, Preparing tables, graphs, and written report summaries, Verifying and cleaning database entries, Designing data entry and analysis programs, Developing quality control procedures for data. Harder to automate: Conducting fieldwork and in-person interviews, Exercising judgment on research ethics and design, Building respondent trust in sensitive research.
Lean into Advanced statistical analysis, AI-assisted survey design, Research methodology, Data visualization, Research ethics and IRB processes. Consider roles such as Social science data scientist or UX researcher or Policy research analyst.
Tasks, skills and AI-exposure for this role were reviewed by an AI model against its O*NET task profile (curated roles use published research anchors). Pay and employment, where shown, are U.S. BLS OEWS (May 2024) figures. This is an estimate, not a prediction about any individual's job. Compare all occupations.