200 Practical Uses with Ethical Aspects

Core rule

AI can support research, but it must not replace the researcher’s judgment, responsibility, ethical approval, critical thinking, or scientific accountability. AI tools cannot be listed as authors, and AI use should be disclosed when required by the journal. (publicationethics.org)

200 AI Uses in Research + Ethical Aspect

  1. Generate research ideas — Ethical aspect: verify novelty with real literature.
  2. Identify research gaps — Ethical aspect: do not rely only on AI summaries.
  3. Refine a research question — Ethical aspect: ensure clinical/scientific relevance.
  4. Convert ideas into PICO — Ethical aspect: keep the question unbiased.
  5. Develop hypotheses — Ethical aspect: avoid data-driven fake hypotheses.
  6. Suggest study designs — Ethical aspect: final design must be chosen by experts.
  7. Compare study designs — Ethical aspect: avoid selecting the easiest but weakest design.
  8. Prepare a research protocol outline — Ethical aspect: protocol must be human-reviewed.
  9. Draft study objectives — Ethical aspect: objectives must match methods and outcomes.
  10. Define primary outcomes — Ethical aspect: avoid changing outcomes after seeing results.
  11. Define secondary outcomes — Ethical aspect: clearly separate them from primary outcomes.
  12. Suggest inclusion criteria — Ethical aspect: avoid unfair exclusion of populations.
  13. Suggest exclusion criteria — Ethical aspect: justify exclusions scientifically.
  14. Improve eligibility criteria wording — Ethical aspect: keep criteria transparent.
  15. Plan recruitment strategies — Ethical aspect: avoid coercion or pressure.
  16. Draft participant information sheets — Ethical aspect: ensure plain language and consent clarity.