AI Research & Fact-Checking Without Getting Fooled
Deep research modes, fabricated and misrepresented citations, a ten-minute verification routine, and judging sources on an AI-written web.
AI research output is dangerous precisely because it is well written. Fluent prose with citation-shaped references reads like diligence, and people have been professionally sanctioned for trusting it. This course makes you the person who uses these tools at speed and can still be relied on. You will learn the four failure patterns (fabrication, misrepresentation, confident staleness, laundered consensus), what search-grounded and deep research modes do and do not fix, the prompt instructions that make output checkable, a triage-based verification routine that fits in ten minutes, and how to rank sources on a web increasingly written by AI. Accountability never transfers to the tool.
What you'll learn
- Recognise fabricated, misrepresented, stale and circular AI research claims
- Know the real limits of search-grounded and deep research modes
- Prompt so that every factual claim comes back verifiable
- Run a ten-minute triage and verification routine on load-bearing claims
- Rank sources properly, from primary documents down to content marketing
- Use AI research honestly, with disclosure and accountability intact
Course content
- 1. Why AI research feels right and is often wrong (15 min)
- 2. Search-grounded modes and their limits (15 min)
- 3. Prompting for verifiable research (15 min)
- 4. A verification routine that fits in ten minutes (15 min)
- 5. Judging sources in an AI-saturated web (15 min)
- 6. Using AI research honestly and defensibly (15 min)
Related courses
- AI Fluency Foundations: How LLMs Actually Work — No code, no maths: what a language model is really doing, why it hallucinates, where your data goes, and what it is genuinely good at.
- Prompting That Works: The Universal Framework — One reusable five-part brief that gets usable output from any model, plus the examples, reasoning checks and iteration habits that make it stick.
- Choosing Your AI Stack in 2026 — ChatGPT, Claude, Gemini, Copilot and open-weight models: how to choose on data handling, connections and fit rather than leaderboards.