  How good a research scientist is ChatGPT? We systematically probed the
capabilities of GPT-3.5 and GPT-4 across four central components of the
scientific process: as a Research Librarian, Research Ethicist, Data Generator,
and Novel Data Predictor, using psychological science as a testing field. In
Study 1 (Research Librarian), unlike human researchers, GPT-3.5 and GPT-4
hallucinated, authoritatively generating fictional references 36.0% and 5.4% of
the time, respectively, although GPT-4 exhibited an evolving capacity to
acknowledge its fictions. In Study 2 (Research Ethicist), GPT-4 (though not
GPT-3.5) proved capable of detecting violations like p-hacking in fictional
research protocols, correcting 88.6% of blatantly presented issues, and 72.6%
of subtly presented issues. In Study 3 (Data Generator), both models
consistently replicated patterns of cultural bias previously discovered in
large language corpora, indicating that ChatGPT can simulate known results, an
antecedent to usefulness for both data generation and skills like hypothesis
generation. Contrastingly, in Study 4 (Novel Data Predictor), neither model was
successful at predicting new results absent in their training data, and neither
appeared to leverage substantially new information when predicting more versus
less novel outcomes. Together, these results suggest that GPT is a flawed but
rapidly improving librarian, a decent research ethicist already, capable of
data generation in simple domains with known characteristics but poor at
predicting novel patterns of empirical data to aid future experimentation.
