{ "source": "Cooked Index — occupational AI risk register", "page": "https://cookedindex.com/jobs/social-science-research-assistants/", "methodology": "https://cookedindex.com/methodology", "notice": "Verdicts are re-examined as evidence accumulates. Re-fetch before relying on this; the page above always carries the current score.", "scored_at": "2026-08-11", "model": "claude-opus-5", "occupation": { "title": "Social Science Research Assistants", "soc_code": "19-4061", "category": "Science", "us_employment": 30640, "median_annual_wage": 61990 }, "verdict": "COOKED", "risk_resistance": 22, "contested": false, "near_boundary": false, "dimensions": { "task_resistance": 6, "embodiment": 6, "liability_shield": 1, "trust_premium": 4, "judgment_accountability": 5 }, "reasoning": { "task_resistance": "Coding open-ended survey responses to a codebook, running descriptives and OLS in Stata, formatting tables to APA, and chasing down citations are the tasks an LLM does in one pass — the 6 rather than 2 reflects the residual that isn't text: intercept surveys in the field, escorting participants through consent and debriefing in a lab session, and calling non-responders for a phone follow-up.", "embodiment": "Most weeks are a laptop and a shared drive, but the 6 accounts for real in-person duties — setting up eye-tracking or physiological equipment in a behavioral lab, running focus groups, door-knocking or mall-intercept recruitment, and handling paper consent forms and locked file cabinets for identifiable data.", "liability_shield": "There is no credential to hold: RA postings ask for a BA and Stata familiarity, IRB human-subjects training (CITI) is a two-hour online module anyone can pass, and the protocol is approved in the PI's name — the 1 rather than 0 is only because your CITI certificate is a documented condition of touching subject data.", "trust_premium": "Participants are consenting to the study and the PI's institution, not to you, and your outputs — cleaned datafiles, code, memos — travel upward anonymously into someone else's manuscript; the 4 covers the one relationship that is genuinely yours, the repeat contact with a longitudinal cohort or a community partner who will only return your calls.", "judgment_accountability": "You make choices daily — how to handle a straddling response, whether an outlier is a data-entry error, whether an interview segment fits code 3 or code 7 — but they run back to a codebook, a pre-registration, or the PI's decision by Friday's meeting, which is why this sits at 5 rather than in the discretion band." }, "rationale": "The daily work — literature searches and annotated bibliographies, transcribing and coding interviews, cleaning survey datasets, running standard regressions in Stata or R, and drafting methods sections and tables — is exactly the text-and-spreadsheet work current models do at usable quality and near-zero marginal cost. What resists is the physical and interpersonal layer: recruiting and consenting human subjects, running in-person lab sessions or field surveys, and the IRB and data-integrity legwork a named person must actually do. There is no licensure and no signature requirement here, and the principal investigator — not the RA — owns the findings, so no accountability moat exists.", "outlook": "By the mid-2030s most coding, transcription, and routine analysis RA hours will be absorbed by AI, leaving a smaller cohort focused on human-subject fieldwork, restricted-data stewardship, and reproducibility oversight.", "what_would_raise_it": { "levers": [ { "dimension": "liability_shield", "change": "Federal research-integrity and human-subjects rules (Common Rule 45 CFR 46 revisions, or NIH/NSF data-management policy) requiring a named human study-team member to attest to consent administration and to certify that AI tools were not used to generate or impute human-subject data — the way FDA 21 CFR Part 11 already requires named signers for clinical data. Journals (ICMJE, COPE) already bar AI authorship; extending that to a named human attestor of dataset provenance would attach a person to each file.", "plausibility": "plausible", "would_add": 5 }, { "dimension": "embodiment", "change": "Funder or IRB requirements that consent, sensitive-population interviews, and field survey administration be conducted in person by a trained human — already the norm for prisoner, minor, and clinical populations under 45 CFR 46 Subparts B-D — and enforced against remote/synthetic-panel substitutes. If IRBs formally bar AI-mediated consent, the surviving RA job concentrates in the field-contact layer.", "plausibility": "plausible", "would_add": 4 }, { "dimension": "task_resistance", "change": "Genuine two-tier structure: if coding, cleaning, and literature search collapse to model output, the residual is adjudicating ambiguous qualitative codes, detecting fraudulent survey respondents and bot panels (a live crisis for Prolific/MTurk data since 2023), and reconstructing what actually happened in the field. Watch for RA postings that specify data-quality auditing and respondent-fraud screening rather than coding.", "plausibility": "already happening", "would_add": 4 }, { "dimension": "judgment_accountability", "change": "Replication-crisis infrastructure putting names on analytic decisions: preregistration platforms (OSF, AsPredicted) and journal policies requiring a named analyst to document each deviation from the preregistered plan, plus retraction-era demands that a specific person can reconstruct the analysis pipeline under challenge.", "plausibility": "plausible", "would_add": 3 } ], "ceiling_note": "No realistic route to a trust premium — the buyer is a PI or funder who never sees the RA, and grant budgets reward cost, not human provenance. Even with every lever, the routine tier is gone and headcount falls; these raise the score of the surviving job, not the number of jobs." }, "adjudication": { "method": "two independent runs agreed on the verdict", "outcome": "corroborated", "run_totals": [ 22, 23 ], "run_verdicts": [ "COOKED", "COOKED" ] }, "employment_history": { "points": [ { "y": 2017, "emp": 31500, "wage": 46000 }, { "y": 2018, "emp": 34550, "wage": 46640 }, { "y": 2019, "emp": 35580, "wage": 47510 }, { "y": 2020, "emp": 35330, "wage": 49210 }, { "y": 2021, "emp": 28690, "wage": 49720 }, { "y": 2022, "emp": 28720, "wage": 50470 }, { "y": 2023, "emp": 30890, "wage": 56400 }, { "y": 2024, "emp": 32940, "wage": 58040 }, { "y": 2025, "emp": 30640, "wage": 61990 } ], "from": 2017, "to": 2025, "change_pct": -2.7, "comparable_from": 2019, "spans_soc_revision": true }, "pivots": [ { "slug": "data-scientists", "title": "Data Scientists", "verdict": "EXPOSED", "risk_resistance": 37, "median_wage": 120230, "overlap": 71, "skills_to_close": [ "Active Learning", "Speaking", "Monitoring", "Service Orientation" ] }, { "slug": "mathematical-science-teachers-postsecondary", "title": "Mathematical Science Teachers, Postsecondary", "verdict": "EXPOSED", "risk_resistance": 48, "median_wage": 79940, "overlap": 59, "skills_to_close": [ "Instructing", "Mathematics", "Monitoring", "Learning Strategies" ] } ], "license": "https://cookedindex.com/terms" }