ArticleAI and ethics2025
The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool.
Article in AI and ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
47 citing papers in PubMed.
- Moving towards acceleration with accountability: a conceptual framework for AI-assisted systematic reviews.Global epidemiology · 2026Article
- The Evolving Role of Large Language Models in Health Care Research and Scientific Communication.Mayo Clinic proceedings · 2026Article
- Hallucinated citations produced by generative artificial intelligence may constitute research misconduct when citations function as data in scholarly papers.Accountability in research · 2026Article
- Large language models vs. conventional search in identifying delirium guidelines for a scoping review.BMC medical research methodology · 2026Article
- Guidelines needed for the use of AI in the preparation or review of IRB, IBC, and IACUC applications.Accountability in research · 2026Article
- The Challenges of Web Scraping and AI for Research Ethics in Canada: A Survey of University REBs.Journal of empirical research on human research ethics : JERHRE · 2026Article
- AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Linguistic shifts in dental scientific writing in the large language model era.Research integrity and peer review · 2026Article
- Will the widespread use of large language models in scientific writing undermine scientists' critical thinking?PLoS biology · 2026Article
- Article
- Pitfalls and risks of generative AI in machine learning.Patterns (New York, N.Y.) · 2026Review
- Concerns of AI use in evidence synthesis based practices: collective views from the community.BMC medical research methodology · 2026Article
- Generative AI adoption and ethical perceptions: a comparative study of medical and non-medical researchers in Chinese universities.BMC medical ethics · 2026Article
- The Influence of Principlism on the Field of Research Integrity.The American journal of bioethics : AJOB · 2026Article
- Development and Evaluation of a Generative AI Chatbot for Database Searching in Systematic Review.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2026Article
- A function-based framework for AI-amplified, data-driven healthcare simulation research.Advances in simulation (London, England) · 2026Article
- Autonomous artificial intelligence, scientific research, and human values.AI and ethics · 2026Article
- Disclosing artificial intelligence use in scientific research and publication: When should disclosure be mandatory, optional, or unnecessary?Accountability in research · 2026Article
- A structured framework for effective and responsible generative artificial intelligence chatbot prompt engineering throughout the scientific process: a comprehensive guide for the health and medical researcher.Frontiers in artificial intelligence · 2026Review
- Comparative Performance of ChatGPT-5 and Gemini 2.5 on the Official Clinical Diabetology Specialty Examination.Cureus · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Using artificial intelligence (AI) in research offers many important benefits for science and society but also creates novel and complex ethical issues. While these ethical issues do not necessitate changing established ethical norms of science, they require the scientific community to develop new guidance for the appropriate use of AI. In this article, we briefly introduce AI and explain how it can be used in research, examine some of the ethical issues raised when using it, and offer nine recommendations for responsible use, including: (1) Researchers are responsible for identifying, describing, reducing, and controlling AI-related biases and random errors; (2) Researchers should disclose, describe, and explain their use of AI in research, including its limitations, in language that can be understood by non-experts; (3) Researchers should engage with impacted communities, populations, and other stakeholders concerning the use of AI in research to obtain their advice and assistance and address their interests and concerns, such as issues related to bias; (4) Researchers who use synthetic data should (a) indicate which parts of the data are synthetic; (b) clearly label the synthetic data; (c) describe how the data were generated; and (d) explain how and why the data were used; (5) AI systems should not be named as authors, inventors, or copyright holders but their contributions to research should be disclosed and described; (6) Education and mentoring in responsible conduct of research should include discussion of ethical use of AI.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.