Assist social scientists in laboratory, survey, and other social science research. May help prepare findings for publication and assist in laboratory analysis, quality control, or data management.
U.S. Workers
32,940
Median Salary
$58,040
10-Year Growth
+4.4%
Annual Openings
5,200
Typical entry: Bachelor's degree
23 of 23 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Prepare, manipulate, and manage extensive databases.
AI: Fully automatable - AI and automation tooling in 2025 can fully prepare, transform, maintain, and manage large databases, including ETL, cleaning, and indexing tasks.
Provide assistance with the preparation of project-related reports, manuscripts, and presentations.
AI: Fully automatable - AI can fully assist in drafting, formatting, and producing reports, manuscripts, and presentations from project materials and data with minimal human input.
Perform descriptive and multivariate statistical analyses of data, using computer software.
AI: Fully automatable - By 2025 AI and statistical software can fully perform descriptive and multivariate analyses, including model fitting, diagnostics, and automated reporting given appropriate data and instructions.
Prepare tables, graphs, fact sheets, and written reports summarizing research results.
AI: Fully automatable - AI tools can generate tables, graphs, fact sheets, and draft written reports from data and templates end-to-end with minimal human intervention.
Administer standardized tests to research subjects, or interview them to collect research data.
AI: Fully automatable - Scripted standardized test administration and many interview protocols can be fully automated via digital platforms and conversational agents while preserving standardization and timing.
Conduct internet-based and library research.
AI: Fully automatable - AI systems by 2025 can conduct comprehensive internet and library research, retrieve and summarize literature, and prioritize sources given proper access and prompts.
Recruit and schedule research participants.
AI: Fully automatable - Recruitment outreach, eligibility pre-screening, and calendar scheduling are readily automatable using targeted ads, chatbots, and integrated scheduling systems.
Perform data entry and other clerical work as required for project completion.
AI: Fully automatable - Data entry and routine clerical tasks are highly automatable with OCR, RPA, and scripts that by 2025 can perform these tasks reliably at scale.
Code data in preparation for computer entry.
AI: Fully automatable - Automated ETL tools and NLP/regex models in 2025 can reliably transform and code data for computer entry with minimal human intervention for most datasets.
Provide assistance in the design of survey instruments such as questionnaires.
AI: Fully automatable - Generative models and survey-design toolchains can draft, optimize, and validate questionnaires, provide sampling and question-wording advice, and run cognitive-testing simulations end-to-end.
Track research participants, and perform any necessary follow-up tasks.
AI: Fully automatable - Participant tracking, reminders, automated follow-ups, and retention workflows can be fully handled by CRM-like systems and automated communication agents for most studies.
Track laboratory supplies, and expenses such as participant reimbursement.
AI: Fully automatable - Inventory management, expense tracking, and reimbursement processing are routine transactional tasks that automated systems and AI can fully manage and reconcile.
Obtain informed consent of research subjects or their guardians.
AI: Partial - AI can facilitate and automate parts of the informed-consent process (scripts, e-consent, translations, comprehension checks) but cannot fully replace human judgment, capacity assessment, and ethical/legal sign-off in many settings.
Verify the accuracy and validity of data entered in databases, correcting any errors.
AI: Partial - Automated validation, anomaly detection, and cleaning tools can handle most accuracy checks and corrections, but complex or context-dependent errors still require human review.
Edit and submit protocols and other required research documentation.
AI: Partial - AI can draft and edit protocols and prepare submission materials and even automate portal interactions, but final approvals, institutional signatures, and regulatory responsibility typically require humans.
Develop and implement research quality control procedures.
AI: Partial - AI can design and implement many quality-control routines and monitoring systems, but setting QC strategy, ethical tradeoffs, and context-specific standards usually needs human expertise.
Screen potential subjects to determine their suitability as study participants.
AI: Partial - AI can screen candidates against explicit inclusion/exclusion criteria and flag suitability but complex clinical, legal, or nuanced eligibility judgments still require human review.
Present research findings to groups of people.
AI: Partial - AI can generate and deliver presentations (slides, scripts, synthesized speech) and handle many Q&A patterns, but live interactive presentation with nuanced audience engagement and responsibility is not fully automatable.
Design and create special programs for tasks such as statistical analysis and data entry and cleaning.
AI: Partial - AI can generate, prototype, and even produce sophisticated scripts and programs for analysis and cleaning, but full lifecycle design, architecture, testing, and integration typically require human software-engineering oversight.
Allocate and manage laboratory space and resources.
AI: Partial - AI can optimize scheduling and resource allocation proposals but real-world lab-space allocation involves safety, compliance, and ad hoc coordination that still need human managers.
Supervise the work of survey interviewers.
AI: Partial - AI can monitor interviewer performance, flag quality issues, and provide feedback, but full supervision including personnel management and complex judgment remains human-led.
Perform needs assessments or consult with clients to determine the types of research and information required.
AI: Partial - AI can assist with structured needs assessments and generate research proposals, but nuanced client consultation and relationship-driven scoping still require human expertise.
Collect specimens such as blood samples, as required by research projects.
AI: Partial - AI cannot reliably perform physical specimen collection itself by 2025, though it can guide humans, process sample metadata, and assist robotic systems in controlled settings.