COOKED
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.
Core tasks are already automatable. 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.
Some physical or field component. 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.
No licence, no signature requirement. 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.
Anonymous artifact production. 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.
Executes defined procedures on defined inputs. 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.
Has AI actually changed your work?