Fact Or Fiction: AI, Images & Viral Video
Updated: Sep 5
Fact Or Fiction is our evidence hub for AI-generated images, edited video and viral clips that may not show what captions claim. Each entry starts with the claim as people are likely to encounter it, separates what is known from what is assumed, and links readers to the evidence used for the verdict.
Latest check — reviewed 4 September 2026
The viral niqab arrest clip was not a real British policing incident. Verdict: AI generated. The video was presented as though a Muslim woman had told police they could not arrest her, but the scene contained multiple synthetic-video failures and no verified real incident behind it. This is exactly the kind of fabricated ‘visual proof’ that can turn an existing prejudice into instant outrage before viewers have time to check it.
How we check claims
We identify the original source, check dates and context, look for primary evidence where possible, and distinguish a false statement from a true fact presented in a misleading way. When evidence is incomplete, the verdict should say so rather than forcing certainty.
What you will find here
Claims are updated as new evidence appears. Corrections are part of the process, not something to hide. Screenshots and viral clips can disappear, so we preserve enough context for readers to understand exactly what was checked.
Seeing is no longer believing
A photograph or video used to feel like stronger evidence than a written claim. Generative AI has broken that assumption. Synthetic faces, voices, crowds and conversations can now be produced cheaply, while ordinary editing can remove the seconds before or after a real clip that explain what actually happened.
This matters most when the content is designed to confirm an existing fear. A fake video of a Muslim woman defying police does not need to convince everyone. It only needs to look plausible enough for people already primed to believe that Muslims receive special treatment. By the time a correction arrives, the emotional message may already have travelled much further than the truth.
How we check visual claims
We look for the earliest available upload, original source, consistent landmarks, shadows, hands, text, reflections, audio and continuity. We compare the clip with reliable reporting and official statements, and where specialist verification exists we link it. A single visual glitch is not always proof of AI, just as a clean looking image is not proof that it is genuine.
Context can be manipulated without AI
Some of the most effective misinformation uses completely real footage. A video from another country is relabelled as Britain. An old protest is presented as happening today. A short clip removes the explanation that came moments later. Fact Or Fiction therefore checks provenance and context, not simply whether pixels were generated by a machine.
The political danger is the speed, not only the technology
TruthVsHate.com view on this story
A synthetic clip can be created in minutes, but the correction still has to identify the source, inspect the evidence and reach people after the emotional claim has already spread. That imbalance rewards whoever is willing to publish first and verify later. In divisive politics, the false image only has to reinforce a prejudice long enough to shape the conversation. The burden then falls on everyone else to prove that an event they never witnessed did not happen.
Start with reliable sources
Truth Vs Hate publishes the sources behind our reporting so readers can check the evidence, context and claims for themselves. Transparency matters because readers should be able to verify what we say rather than simply take our word for it.
Useful starting points include GOV.UK https://www.gov.uk/ , the Office for National Statistics https://www.ons.gov.uk/ , Full Fact https://fullfact.org/ , Ofcom https://www.ofcom.org.uk/ and the relevant regulator or public body for the claim.
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