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DOIs, PMIDs, ISBNs, ISSNs, and ORCID iDs all identify different things. Learn which identifiers help you find, verify, distinguish, and manage research sources without treating them as interchangeable.
Read Guide →AI-assisted research uses artificial intelligence to support one or more research tasks while researchers retain responsibility for the study and its scholarly decisions. The important question is not merely whether AI was used, but what it assisted with and how its contribution was evaluated.
Read Guide →Using generative AI does not automatically make research less scientific or rigorous. Rigor depends on how the research question, evidence, methods, validation, interpretation, transparency, and conclusions are handled.
Read Guide →Generative AI can potentially improve research quality when it helps researchers detect errors, consider alternatives, test ideas, improve reproducibility, or communicate evidence more clearly. Faster production and more polished writing, however, should not be mistaken for better research.
Read Guide →Generative AI can perform useful forms of scientific reasoning, but its reliability varies by model, task, evidence, and context. Researchers should evaluate the reasoning chain and underlying evidence rather than assume that a persuasive conclusion is scientifically sound.
Read Guide →AI hallucinations can be difficult to detect because language models are capable of producing fluent, coherent, contextually appropriate language even when individual claims are wrong. For researchers, confidence, detail, and academic tone should never substitute for evidence.
Read Guide →Researchers remain responsible for factual claims they use, but that does not mean every AI-generated sentence requires identical verification effort. The sensible approach is risk-based: verify consequential claims rigorously and do not publish unsupported claims merely because AI supplied them.
Read Guide →A plausible scientific claim from AI is not evidence. Verify it by defining exactly what the claim asserts, locating appropriate scientific sources, and checking whether the evidence actually supports that specific conclusion.
Read Guide →The best AI tool for research depends on what you need it to do and what could go wrong if it fails. Choose by task fit, verifiability, privacy, transparency, and research risk rather than popularity or headline capabilities.
Read Guide →AI use in research is rarely governed by a single policy. Researchers may need to comply simultaneously with laws, university rules, ethics approvals, funder conditions, journal policies, and research-team agreements.
Read Guide →Your university may permit an AI tool while a journal restricts how it can be used in submitted work. Institutional permission and publication requirements govern different parts of the research process.
Read Guide →University and journal AI policies can impose different requirements, but not every difference is a true conflict. Learn how to identify which rules apply and what to do when both cannot be satisfied as written.
Read Guide →Unpublished research is not automatically confidential, but entering it into a public AI tool can create disclosure, privacy, ownership, and policy concerns. Check what the material contains and whether you are authorized to submit it before doing so.
Read Guide →Do not assume that a confidential research proposal can be uploaded to an AI tool simply because you wrote it. Proposal content may be governed by confidentiality, institutional, funder, collaborator, intellectual-property, and data-handling requirements.
Read Guide →An unpublished manuscript is not automatically prohibited from AI use, but uploading the complete document can expose far more information than a writing task requires. Check confidentiality, co-author rights, research data, publisher rules, and the AI service before submitting it.
Read Guide →Whether reviewer comments can be entered into an AI tool depends partly on who is using them and what they contain. Authors working on their own revision face a different confidentiality situation from reviewers handling material entrusted to them during peer review.
Read Guide →A confidential grant application entrusted to you for review is not ordinary research material. Some major funders expressly prohibit reviewers from uploading applications, proposal content, critiques, or related review information to unapproved generative AI systems.
Read Guide →Having access to a collaborator's unpublished work does not automatically give you authority to submit it to an AI provider. Permission, confidentiality, ownership, research agreements, and the nature of the information all matter.
Read Guide →The safest default is simple: do not put confidential, sensitive, restricted, or third-party unpublished research into an unapproved AI tool. Use it only after you can establish authorization, appropriate safeguards, and a genuine need to disclose the information.
Read Guide →De-identification can reduce privacy risk, but ethical research involves more than preventing someone from attaching a name to a record. AI use may still raise questions about consent, secondary use, group harms, fairness, confidentiality, and whether participants could reasonably have expected their data to be used this way.
Read Guide →Generative AI can help researchers interrogate why a research question might matter, compare possible contributions, and expose weak rationales. It cannot independently determine scientific importance without reliable evidence and disciplinary context.
Read Guide →Generative AI can help researchers identify feasibility constraints and stress-test a proposed study. Its assessment is only as reliable as the project-specific information it receives about methods, access, resources, ethics, expertise, and time.
Read Guide →Generative AI can be used as an adversarial research-planning partner that deliberately searches for weaknesses in a proposed study. Its criticisms can sharpen reasoning, but they must themselves be checked rather than treated as expert verdicts.
Read Guide →Asking generative AI to recommend research papers may help you discover useful studies, but it does not necessarily constitute a literature search. The difference lies in how publications are retrieved, selected, verified, and documented.
Read Guide →Generative AI can help researchers convert research questions into Boolean search strings by organizing concepts, synonyms, and search operators. However, AI-generated queries must be checked for conceptual accuracy, database compatibility, and retrieval performance before they are used in a literature review.
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