- AI Tools in Research
Key Point
Use AI tools to support your research only when you do so ethically and responsibly — always follow institutional rules, relevant policies and guidelines, applicable regulations and laws, and publisher requirements. Think critically: AI results may be biased or unreliable, so always check and verify content.
Examples
✅ Use AI to help categorize articles in a literature review.
✅ Use summarization tools to identify papers for deeper reading and understanding of a topic.
✅ Confirm that AI use aligns with institutional, national, and EU research regulations and publisher restrictions.
✅ Use bias detection tools (e.g. AI Fairness 360, Fairlearn, Perspective API), peer review and your own critical review to assess AI-supported content.
✅ Keep a log of prompts, tools used, and output version of any AI-generated content.
❌ Don’t assume all AI tools are approved or secure for academic use.
❌ Don’t rely only on AI summaries without reviewing the original sources.
❌ Don’t treat AI outputs as verified facts without cross-checking.
❌ Don’t rely on AI to make ethical decisions or interpret participant data.
Excerpt from the Official Guidelines
AI tools can be used effectively in conducting research. Novice researchers must learn the essentials for appropriate and ethical use of AI technology as defined by the University of Cyprus and European and international guidelines and laws as well as publishers of books and scientific journals.
Researchers should apply critical judgement when using AI tools in research due to the lack of transparency regarding the datasets used to train these tools4. The training datasets may include both unintentionally biased and inaccurate content, as well as data polluted with malicious intent. Even non-malicious data can reflect societal biases or outdated information, potentially compromising the reliability and ethical soundness of AI-generated outputs.
Last Updated on 31 July, 2025
