EN39 minTutorial
How to Disclose AI Use in Your Thesis or Research Paper
Professor Benita Olivier shows how to declare AI use at each stage of a real research workflow in SciSpace.
Responsible AI in Research: Integrity, Disclosure and Trust
Taught by Prof. Benita Olivier, Dr. Lyndon Walker +13 experts
15experts19tutorials3languages
Using AI in research is now normal; using it responsibly is what protects your reputation.
- Know what to delegate to AI and what to verify
- Write an AI disclosure statement for a paper or thesis
- Avoid hallucinated citations and integrity red flags
Try this on SciSpace
Responsible AI tutorials from expert researchers
Showing 19 tutorials
- EN39 min
- ENTutorial
Disclose, Don't Disguise: AI Transparency in Research Publishing
Why openly disclosing AI use protects your credibility, and how to stay accountable for every claim when AI supports your research.
EN45 minTutorialUsing AI in Grants and Papers Without Raising Reviewer Red Flags
Learn which AI writing patterns raise red flags with grant and journal reviewers, and how to use AI while keeping your own voice.
EN35 minTutorialResponsible AI in Research: What to Delegate, Verify and Disclose
Dr. Hélène Nguemgaing explains how to use AI across the research process while keeping verification, disclosure and accountability in place.
EN48 minTutorialAI in Manuscript Writing: Journal Policies and Disclosure Statements
Learn where AI fits in manuscript drafting, how ICMJE, COPE and major publishers differ on disclosure, and how to write your statement.
EN40 minTutorialAI in the Writing Classroom: Assessment, Disclosure and Trust
Christopher Ostro shares how he adapted his writing course to AI through transparency, AI literacy and trust rather than policing.
EN43 minTutorialHow to Disclose AI Use in Academic Research at Every Stage
When, where and how to disclose AI use across the research lifecycle, with guidance on writing clear statements and avoiding common mistakes.
EN59 minTutorialResearcher-Led, AI-Assisted Research: Using SciSpace Responsibly
Dr. Ethan James Gantana shows which research tasks AI can speed up, which need scrutiny and which always need independent verification.
EN35 minTutorialBeyond AI Hallucinations: Building a Reliable AI Research Workflow
Dr. Joanne Donoghue shows how to reduce fabricated citations and wrong answers by building a verifiable AI-assisted research workflow.
EN44 minTutorialUsing AI Responsibly in Research: Trust, Evidence and SciSpace
Dr Sasha Nikolic explains how to assess AI output, verify citations and disclose AI use to protect academic integrity.
EN34 minTutorialAI and Research Integrity: Navigating Global AI Rules in 2026
Professor Sid Dobrin explains how emerging AI regulations and journal policies affect disclosure, authorship and transparency in research.
EN44 minTutorialUsing AI Responsibly in Research: Risks, Policies and Best Practices
Dr. Faheem Ullah explains how to use AI in research without risking hallucinations, fabricated citations, over-reliance or loss of credibility.
EN34 minTutorialAI That Supports Judgement: A Researcher-Led Workflow in SciSpace
Jason Gulya shows how to use SciSpace so AI informs your research thinking instead of replacing it, from scoping to critical evaluation.
EN44 minTutorialCan You Trust AI with Your Research Data? SciSpace Privacy Explained
Find out what happens to documents you upload to SciSpace and the practical habits that keep sensitive research data safe.
EN57 minTutorialHow to Use AI in Research Without Compromising Integrity
Dr. Ali Hindi explains how to tell ethical from unethical AI use and align AI-assisted research with university and journal rules.
EN3 minTutorialHow to Use an AI Detector for Academic Writing: Limits and Best Practices
Use SciSpace AI Detector as a screening signal, not proof of authorship or misconduct. Review flagged passages in context, compare them with drafts, sources, and citation patterns, consider false positives for formulaic or multilingual academic prose, and rely on transparent institutional procedures rather than a single detector score.
- EN36 minTutorial
How to Detect Fake AI Citations: A Researcher’s Verification Checklist
When SciSpace or another AI system suggests a reference, confirm that the source exists and supports the claim before using it. Resolve the title, authors, venue, year, pages, and DOI in trusted records; open the source; check the relevant passage; and remove or correct any citation that is fabricated, mismatched, or irrelevant.
ES52 minTutorialCómo usar la IA de forma responsable en la investigación con SciSpace
Jefferson Alexander Moreno Guaicha presenta un marco para usar la IA en investigación con criterio, ética y transparencia en SciSpace.
PT44 minTutorialRevisão de literatura com IA: ética, integridade e responsabilidade
A Dra. Polyana Silva discute como usar IA na revisão de literatura sem comprometer originalidade, integridade acadêmica ou qualidade científica.
Learning path
Responsible AI in Research in 6 LessonsEverything you need to use AI without risking your integrity: trust and evidence, hallucinated citations, AI detection, regulations, rigour and disclosure.About this use case
Using AI in research is now normal; using it responsibly is what protects your reputation. That means verifying outputs, never citing sources you have not checked, protecting participant data, and disclosing AI use the way your institution and publisher expect.
This hub brings together SciSpace Academy's tutorials on research integrity: how to disclose AI use across every stage of a project, how to avoid hallucinations and fake citations, what grant and journal reviewers notice, how global regulations are changing in 2026, and how to keep the researcher in charge of the work. These are among our most attended tutorials, delivered by editors, librarians, statisticians and researchers.
Frequently asked questions
Do I have to disclose that I used AI in my research?
Most major publishers and many universities now require disclosure when AI tools materially contribute to a manuscript, analysis or images. Policies differ, so check your journal and institution. A short statement naming the tool, the version and what it was used for is usually expected.
What are AI hallucinations in research?
A hallucination is confident output that is not true, such as a fabricated reference, a misquoted finding or an invented statistic. Reduce the risk by working from real sources, asking AI to quote the passage it relies on, and checking every claim against the original paper.