How to verify AI-written claims before publishing
AI models rarely invent things at random. They produce plausible things, and plausible errors are exactly the ones a quick read misses. Verification means turning “sounds right” into “I checked it”. Here is a method that scales from one article to a content team.
1. Find the checkable claims
Not every sentence needs checking. Mark the ones that assert something about the world:
- numbers, prices, percentages and dates
- names of people, organisations, products and places
- quotes and paraphrases attributed to someone
- rules, requirements, eligibility and legal statements
- comparisons and rankings (“faster than”, “the largest”)
- cause and effect (“X leads to Y”)
Opinions, advice framed as advice, and transitions don’t need a source. Anything a reader might act on does.
2. Trace each claim to a source
For each marked claim, find the source it came from. If the article has inline citations, open the linked page and search it for the specific fact. Check three things:
- Presence: the source actually says this.
- Context: it says it about the same thing, place, period and conditions.
- Authority: the source is in a position to know, ideally a primary source.
If there is no citation, find a primary source yourself or cut the claim.
3. Watch for the common failure patterns
| Pattern | Example | How to catch it |
|---|---|---|
| Stale data | Last year’s fares shown as current | Check the source’s date and your retrieval date |
| Scope drift | A rule for residents applied to visitors | Reread the source’s conditions and exceptions |
| Merged facts | Two true figures combined into a false comparison | Check that both figures come from the same source or period |
| Misattribution | A quote given to the wrong person or organisation | Search for the exact phrase in the cited source |
| Unit and currency errors | Totals mixing dollars and euros, or kilometres and miles | Recalculate anything derived |
| Invented precision | “Roughly 40%” becomes “41.7%” | Precision should never exceed the source’s |
| Confident absolutes | “Always”, “never”, “guaranteed” | Soften, or find a source that really says it |
4. Decide: keep, fix, qualify or cut
- Keep it if the source supports it as written.
- Fix it if the source supports a slightly different claim, and rewrite it to match.
- Qualify it if it is true but time-sensitive: add “as of [month year]” or “check current prices with the operator”.
- Cut it if you can’t find support quickly. An unsupported sentence adds more risk than value.
5. Record what you checked
For teams, keep a light record, such as a comment on the post or a line in your editorial tracker: who checked it, when, and anything qualified or cut. When a reader questions a claim months later, you’ll know where it came from.
Where tooling helps
Verification stays a human job, but tools can reduce the work:
- Source-first drafting means claims start out tied to evidence you chose. AI Blog Writer with Sources writes only from sources you supply and cites them inline.
- Retrieval dates on each source make stale data visible.
- Warnings about unsupported or deselected claims tell you where to look first.
Even with good tooling, a person should make the final call on anything a reader might act on.
Draft from your sources, inside WordPress
AI Blog Writer with Sources turns your brief and chosen URLs into a cited WordPress draft, using your own AI key. It never publishes automatically.