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Start by separating the footage from the claim
Write down the claim attached to the clip, then distinguish it from what is directly visible or audible. Note the alleged event, location, date, and people involved. A clip might genuinely show a crowd, for example, without establishing that it was filmed in the place or during the event named in the caption.
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This distinction keeps the investigation focused: ask both whether the file has signs of AI generation or editing and whether the video actually supports the claim being shared.
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Trace where the video came from
Find the earliest available upload
Look for the original post, publisher, or recording rather than relying on a repost. Check when the clip first appeared and whether the account that published it has a credible connection to the claimed event. Search distinctive frames or still images to find earlier uploads and related versions. The UK House of Commons Library’s guidance on verifying images and videos recommends checking source and context as part of verification.
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Treat reverse image search as a lead
A matching frame can reveal that footage appeared earlier or in a different context. It does not, by itself, prove that the video is authentic, identify the original recording, or establish whether the current caption is accurate. Compare the versions and follow the trail to the earliest credible source you can find. The House of Commons Library also discusses reverse image search and metadata.
Check whether the place, time, and event fit
Look for independent reporting, official statements, or other recordings that corroborate the event. Compare what appears in the clip with the claimed location and date: landmarks, signs, language, accents, weather, and other visible details can help test whether the context fits. The House of Commons Library advises considering language and writing, possible signs of manipulation, source, and context.
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Corroboration matters more as the stakes rise. A familiar-looking scene or a confident caption is not independent confirmation; seek evidence from sources that do not simply repeat the same post.
Inspect the best available file and its provenance
When possible, examine the original video file rather than a screenshot or a copy downloaded from a social platform. Re-uploads and platform processing may recompress a video or remove information. Metadata can offer clues about a file’s history, but missing metadata is not proof of fabrication.
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C2PA Content Credentials can provide tamper-evident provenance information about a digital asset when that information is present. Provenance may help show where a file came from or what edits were recorded; it does not establish that the depicted event happened as claimed. C2PA describes the technology as a complement to media literacy, fact-checking, and digital forensics, not a replacement for them.
Use AI checks as narrow evidence, not a verdict
Google Gemini: SynthID and Content Credentials
Google’s Gemini verification help describes checks for SynthID signals associated with Google AI tools and for C2PA Content Credentials on compatible files. A result may help identify signals from Google’s tools or provenance information, but Google’s documentation says that no SynthID result does not rule out AI generated by other systems. Content Credentials also do not establish that a file is definitely AI-generated.
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Google announced video verification in Gemini on December 18, 2025. The announcement said the check scans audio and visual tracks for SynthID and may identify segments where it detects material. At announcement, the stated upload limit was 100 MB and 90 seconds; those were product limits at that time, not a guarantee of current availability or limits. Check the current Gemini help page before relying on them.
OpenAI’s verification page: supported OpenAI signals
OpenAI’s content verification documentation describes checking supported provenance signals, including C2PA metadata and SynthID, for supported OpenAI-generated files. Its current page describes image and audio support and says the tool does not detect content generated by other companies’ models. It is not a general-purpose video deepfake detector.
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Read positive and negative results carefully
A detected provider-specific signal is evidence about that signal, not proof that a video’s caption is true or false. A missing signal means only that the check did not detect the relevant evidence. It cannot rule out other AI systems, ordinary editing, or misleading context.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep the conclusion proportional to the evidence
A real recording can be cropped, rearranged, dubbed, or shared with an inaccurate date or location. Evidence of editing does not automatically make every claim about the clip false. Record what you checked and distinguish confirmed facts from questions that remain open. The House of Commons Library notes that verification conclusions may change as knowledge improves.
- Established: what the source, independent corroboration, file history, or relevant signal actually supports.
- Unresolved: details that could not be confirmed, such as the original recording date or the identity of a person.
- Not established by one check alone: whether the entire clip is genuine, whether the scene happened as captioned, or whether no editing occurred.
What AI-video labeling rules do—and do not—tell you
The European Commission says the AI Act transparency obligations in Article 50 apply from August 2, 2026, addressing risks related to AI-generated content and deepfakes. This regulatory context concerns transparency and labeling; it does not authenticate any particular viral video. See the Commission’s Code of Practice on Transparency of AI-generated Content.
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