Check Before You Trust: Fact-Checking AI Output

Build a repeatable method to check claims and citations in AI output.

Looking for step-by-step tutorials for individual AI tools?

Course overview

A beginner pathway for treating AI-generated claims as items to investigate rather than facts to repeat. Four rights-checked videos address hallucinations, a verification demonstration, human review, and practical ways of identifying faulty output. Learners practise separating claims, locating independent evidence, and clearly marking what remains uncertain.

Explain why fluent AI output may include inaccurate claims or references. Break an answer into checkable claims and test them against independent sources. Revise or withhold unsupported material and document what remains unverified.

No technical background required. Bring a non-sensitive example and access to reliable sources; do not rely on another AI answer as the sole evidence.

Beginners who want a clear, guided introduction without unnecessary jargon

People who learn best through examples, guided lessons, and hands-on practice

Professionals, creators, and independent builders looking for a repeatable workflow

Lesson 1 is free

4 lessons · Beginner · Full course.

Open-license course content · CC BY licensed · license verified

This course uses CC BY licensed material attributed to its content provider or uploader. Lesson playback is available only through authenticated access after publication and licensing checks pass.