Ethical Use of AI in Research

AI use follows institutional, journal, conference, and supervisor rules.

The researcher remains responsible for ideas, data, analysis, writing, and claims.

AI output is verified rather than copied blindly.

AI assistance is disclosed when policy requires it.

AI is not used to fabricate sources, data, authorship, analysis, or results.

Check the latest university, department, course, and supervisor AI-use rules.

Identify whether AI is allowed for brainstorming, editing, coding, translation, or analysis support.

Check whether disclosure forms or acknowledgements are required.

Ask for clarification before using AI in high-stakes or unclear contexts.

Keep records of policy guidance and supervisor approvals.

Brainstorming research directions before you evaluate and choose your own topic.

Improving clarity, grammar, organization, or readability of your own writing where allowed.

Generating study questions, checklists, or revision plans for your own review.

Getting coding or debugging suggestions that you test and understand.

Summarizing your own notes for planning, while verifying all details.

Using AI to draft large sections that could obscure authorship.

Asking AI to interpret data without understanding the method.

Using AI-generated literature summaries without reading the sources.

Using AI to translate or rewrite specialized claims that require expert accuracy.

Using confidential or unpublished material in tools without privacy clearance.

Submitting AI-generated work as if it were your own original work.

Creating fake data, fake references, fake quotations, or fake results.

Using AI to bypass an assessment that requires unaided work.

Uploading confidential participant data, unpublished manuscripts, or private institutional material without permission.

Using AI to impersonate a student, researcher, author, or reviewer.

Record the tool name, version if available, date, purpose, and type of assistance.

Describe whether AI was used for language editing, coding help, brainstorming, analysis support, or formatting.

Place the disclosure in the section required by the institution or journal.

Do not over-disclose in a way that suggests AI performed work it did not perform.

Do not under-disclose where policy requires transparency.

Check whether AI tools should be cited, acknowledged, or disclosed separately.

Do not cite AI as evidence for factual or scholarly claims.

Use scholarly sources for literature, theory, data, and methodological claims.

Keep prompts and outputs if your institution requires an audit trail.

Follow journal or style-guide rules for AI acknowledgements.

Verify every factual claim against primary or credible sources.

Check calculations, code, tables, and analysis steps manually.

Test code suggestions in your own environment and understand them.

Review grammar edits to ensure meaning has not changed.

Reject any output you cannot verify or explain.

Search every suggested source in library databases, publisher sites, or trusted indexes.

Verify title, author, year, journal, volume, issue, pages, and DOI.

Do not include references you have not checked and read sufficiently.

Use reference managers and database exports rather than AI-generated reference lists.

Remove any source that cannot be verified.

Do not upload identifiable participant data unless policy and consent allow it.

Avoid sharing unpublished manuscripts, reviewer comments, proprietary code, or institutional files with public tools.

Anonymize data only when anonymization is reliable and approved.

Check tool data-retention and training policies.

Use approved institutional tools for sensitive workflows where available.

Use AI suggestions as input for your own thinking, not as a replacement for it.

Keep drafts, notes, data, analysis files, and revision history.

Ensure you can explain every argument, method, result, and citation.

Do not allow AI to create unsupported conclusions.

Review all final text for accuracy, originality, and policy compliance.

Check supervisor expectations before using AI in dissertation or thesis work.

Check journal or conference AI policies before manuscript submission.

Align disclosure language with the strictest relevant rule.

Ask co-authors to confirm and approve AI-use disclosure.

Update disclosure if AI use changes during revision.

I know which policy applies to this work.

I recorded how AI was used and what I verified.

I did not use AI to fabricate data, sources, results, or authorship.

I can explain every final claim, citation, method, and result.

I have included disclosure or acknowledgement where required.