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World desk6 min

How to Check Whether an Image or Video Was Generated by AI

No single detector can verify every image or video. Combine provenance checks, provider-specific watermark tools and independent context, while treating missing signals and visual flaws cautiously.
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No single consumer tool can reliably determine whether any image or video was made with AI. Check the original file’s provenance, use a watermark or credential checker that supports the relevant signals, and corroborate the image’s source and context. A positive result can be meaningful within a tool’s scope; a negative result is not proof that the media is genuine.

Use several kinds of evidence, not one detector verdict

AI checks look for particular signals, not an all-purpose mark of “AI.” A watermark tool may recognize one provider’s content, while Content Credentials can record information about origin and edits. Neither approach settles every case, and visual clues are weaker still. The most useful assessment combines provenance, provider-specific checks and independent context.

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  • AI-generated means a model created the media. AI-edited means AI changed some or all of it. A detected provider watermark may indicate either, depending on the tool’s result.
  • Watermark detection checks for an embedded signal supported by that service. It does not necessarily detect media from other providers.
  • Content Credentials are machine-readable provenance records. They can help show origin and editing history, but do not certify that a file is definitely AI-generated.
  • Visual inspection can suggest questions to investigate; it cannot reliably prove how a file was made.

Check an image or video: a practical sequence

  1. Preserve the best available copy. Prefer the original file over a screenshot or a copy downloaded from a social platform, which may have been resized, converted or recompressed. Note where it first appeared and whether the original poster identifies its creator. Metadata and provenance signals may be lost when a file is edited or shared.
  2. Inspect Content Credentials, if available. Open the file in a viewer that supports its credential format and version. Review the issuer, creation information and edit history. A valid signed history can support a provenance account; absent, unsupported, malformed or invalid credentials leave the origin unresolved. Google’s Gemini help page says Gemini supports compatible Content Credentials, including version 2.2 and later from products on the C2PA Conforming Products List. Credentials are used for AI and non-AI media alike.
  3. Run a provider-specific watermark check. For suspected Google AI media, upload the file to Gemini and ask whether Google AI created or edited it. For supported OpenAI-origin images or audio, use OpenAI’s Verify page. Read the result as evidence about the signals that service supports—not as clearance from every other AI system.
  4. Trace the source and context. Reverse-search an image to look for an earlier appearance or a different context. Check the alleged event against reputable reporting, event organizers or original witnesses. An older copy or inconsistent caption can reveal that a real image is being presented misleadingly, even when the image itself is not synthetic.
  5. Inspect visible details as clues. Garbled text, errors in small details or backgrounds, inconsistent lighting and shadows, or unnaturally repeated patterns may warrant further checking. They are not verdicts: generated media can have no obvious flaws, and authentic media can contain visual artifacts.
  6. Describe what the checks establish—and what they do not. Report a detected provider watermark or a verified credential history precisely. If signals are missing or conflict, say so; do not call the media authentic just because a tool reports no detection.

What Gemini can check—and its limits

Google says a detected SynthID watermark means all or part of an image or video was created or edited by Google AI. SynthID is an invisible mark embedded in content generated by Google’s models. Google says it can remain detectable after resizing, recoloring or compression, but alterations can defeat detection. Its recognition covers content created with Google AI tools; a negative result does not rule out another provider’s AI.

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Gemini’s current help documentation requires a signed-in personal or eligible Workspace account and says uploads must be one file at a time, no larger than 100 MB. Videos must be under 90 seconds; audio must be under one hour. Availability depends on supported countries and languages. The documented rolling 24-hour allowance is approximately 10 image checks, 10 video checks (up to five minutes total), and 10 audio checks (up to three hours total); quotas may constrain use even when a file meets the size and duration limits. Check Google’s current Gemini Apps Help for supported upload types and availability.

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For video, Gemini may identify segments where it detected SynthID. That does not mean the watermark was found in every frame or throughout the entire segment. Treat the result as a location for a supported signal, not a frame-by-frame authenticity judgment.

What OpenAI’s verification result means

OpenAI documents checks for C2PA credentials in images and SynthID in supported images and audio. Its not_detected result is not a general finding that media is human-made: a mark may be absent, stripped, degraded, unsupported or associated with a legacy model. OpenAI explicitly says its tool does not detect content generated by every other AI company. See OpenAI’s Verify documentation for its supported signals.

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How to read Content Credentials

C2PA credentials provide machine-readable, tamper-evident provenance information. Inspect who issued the record and what the signed history says about creation and edits; do not treat the mere presence of a badge or credential as an AI label. Google warns credentials may be invalid if signed history is changed without an appropriate update, incompatible with the verifier, malformed, or stored remotely in a way the verifier cannot support. A missing credential also says little by itself: the file may never have had one, or it may have been removed or become unreadable.

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For more on the standard, see the C2PA overview. Provenance records are useful evidence, not a universal truth label or a guarantee that the depicted scene is accurately captioned.

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When tools disagree, compare their scope

Different results are not necessarily a contradiction. Before weighing them, ask what each tool can actually recognize and whether it examined the original file.

  • Signal: Is the result about a signed provenance record, an embedded watermark, or a visual heuristic?
  • Coverage: Which provider, media type and credential version does the checker support?
  • File quality: Was the original available, or might conversion, editing or platform sharing have stripped or degraded a signal?
  • Independent corroboration: Does a reliable source support the claimed origin, date and event?

A supported watermark match, valid credential history and independent source corroboration together make a stronger case than a single visual clue or detector result. Microsoft Research describes provenance, watermarking and fingerprinting as complementary approaches and cautions that implementation and display shape how people interpret them. It presents connecting secure provenance with an imperceptible watermark as a promising direction, not a universal consumer test: Microsoft Research.

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Why visual tells and accuracy claims need caution

There is no accuracy percentage established here that can be applied across AI detectors, providers, file types and real-world sharing conditions. In 2024, the Associated Press quoted Latent Space Advisory founder Henry Ajder warning that easy access to detection tools can create false confidence and encourage people to outsource critical thinking. Treat a tool as one source of evidence, not an authority on the whole file or its context. See the Associated Press report.

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EU disclosure rules are not a detector guarantee

The European Commission says transparency obligations under Article 50 of the EU AI Act apply from 2 August 2026. They include requirements related to marking and detecting generated content and labelling deepfakes and certain AI-generated publications. This is EU policy context, not a worldwide labeling rule, and it does not make a consumer tool’s result proof about an individual file. The Commission describes its Code of Practice as voluntary while Article 50 obligations are legal requirements. Its AI Act policy page sets out the Commission’s account.

On 8 May 2026, the Commission listed three technical studies on marking and detecting generated content, including one focused on AI-generated images and video. The listing says the studies assess effectiveness, limitations and practical applicability; it does not provide a universal accuracy figure. See the Commission’s studies listing.

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