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Online services use a combination of known-file matching, AI-assisted flagging, trained human review and reporting or removal processes to address AI-generated child sexual abuse material (CSAM). No single step catches every new image: a hash can recognize a file already known to a service, while unfamiliar material may need to be flagged by a classifier and assessed by specialists.
How detection and removal work
Detection, assessment, removal and referral are separate steps. A platform may flag content; a specialist organization or its reviewers may assess it; a service or hotline may pursue removal; and a report may be referred to an appropriate authority. The precise route depends on the service and jurisdiction.
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1. Match files already known to be CSAM
Specialist organizations or platforms can create digital fingerprints, or hashes, for files that have already been assessed as CSAM. Participating services compare uploaded or hosted files with those known signatures. A match can help recognize the same or closely similar known material without requiring a person to inspect every copy.
2. Flag unfamiliar material for assessment
Hash matching cannot identify a new synthetic image that has no matching entry. Google says it also uses AI to flag new material resembling patterns from confirmed CSAM. A model flag is a lead for review, not a final determination: classifiers can produce false positives, and unfamiliar material may not be flagged.
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3. Have trained people review potential matches
Google says trained specialists review imagery flagged by its AI before it is reported. The Internet Watch Foundation (IWF) says its analysts assess reports and relevant material against its classification threshold. These are descriptions of those organizations’ processes, not evidence of a universal procedure used by every service.
4. Take action and help prevent re-uploads
After material is assessed as CSAM, a hotline or service may pursue removal, alert a host or platform, add a URL to a blocking or alert list, or create a hash for participating services to recognize later. The IWF uses “actioned” for a report it has assessed as containing CSAM and for which it has taken active removal steps. An assessment or report alone does not mean the material has already been removed everywhere.
5. Report or refer the case
Google says that after its review it reports identified CSAM to the National Center for Missing & Exploited Children (NCMEC) as required by U.S. law; NCMEC can make reports available to appropriate law enforcement. UK government guidance describes platforms reviewing potential detections and then reporting to NCMEC, the Royal Canadian Mounted Police or other bodies through applicable mechanisms. The reporting duties and referral route depend on jurisdiction.
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| Approach | What it can do | What it cannot establish by itself |
|---|---|---|
| Hash matching | Recognize files that match known signatures and support efforts to prevent those files from being re-uploaded. | It cannot match a new synthetic file that has no corresponding known-file signature, or independently decide whether unfamiliar material is CSAM. |
| AI-assisted flagging | Prioritize unfamiliar material that resembles patterns associated with confirmed CSAM for further review. | A flag is not proof. Classifiers can make mistakes and need assessment; Google describes trained reviewer confirmation in its own process. |
| Human assessment | Apply an organization’s assessment criteria to a report or flagged material and inform decisions about further action. | Assessment does not itself guarantee removal from every copy or service, or determine what law enforcement will do. |
| Removal and referral processes | Enable services or hotlines to pursue removal, issue alerts, create hashes or refer reports, depending on their remit. | There is no single universal removal route or button that removes material from every location. |
Google describes its own approach as relying on “two equally important technologies”: hash matching and AI. That is a platform’s account of its process, not an independent audit or a head-to-head assessment of detection accuracy.
What published figures show—and what they do not
Published totals measure different things: reports, files, or assessments made under a particular organization’s definitions. They are not directly interchangeable or a single estimate of how much AI-generated CSAM exists online.
| Organization and period | Published figure | How to interpret it |
|---|---|---|
| NCMEC, 2023 | 4,700 CyberTipline reports involving generative AI. | These are reports involving generative AI, not a count of confirmed generated-CSAM files. |
| NCMEC, 2024 | 67,000 CyberTipline reports involving generative AI. | The figure is a report count under NCMEC’s stated scope, not a file count. |
| NCMEC, 2025 | More than 400,000 CyberTipline reports with an AI nexus. | NCMEC says these span five categories; more than 200,000 did not contain enough information to establish how AI was used. Do not describe this as 400,000 reports of generated CSAM. |
| NCMEC, January 2023–December 2025 | NCMEC staff categorized more than 158,000 submitted images and videos as AI-generated. Providers annotated just over 11,000 images and videos as AI-generated over the same period. | These are different actors’ labeling counts, not directly comparable prevalence estimates. |
| IWF, 2023 | 51 actionable reports of AI-generated child sexual abuse imagery. | “Actionable” refers to IWF’s assessment and removal activity, not to the number of individual files. |
| IWF, 2024 | 245 actionable reports, including 193 realistic-looking and 52 prohibited non-photographic reports; those reports contained 7,644 images and a small number of videos. | A report can contain many files. Report and image counts are not interchangeable. |
| IWF, 2025, reported in its 2026 report | 8,029 AI-generated images and videos assessed as showing realistic child sexual abuse; the report also records 3,443 AI-generated videos assessed in 2025. | These are IWF assessment counts and terminology, not the same measure as NCMEC CyberTipline reports or IWF actioned reports. |
How to report suspected AI-generated CSAM or seek removal
For people in the United States
- Report suspected exploitation: NCMEC’s CyberTipline accepts reports from the public as well as electronic service providers. NCMEC says it makes reports available to appropriate law enforcement after handling.
- Request removal of an explicit image of yourself from when you were a minor: NCMEC’s Take It Down lets a person anonymously request removal from participating platforms.
- Use the platform’s reporting tools too: Report the material to the service where it appears so that service can apply its own review and response process.
For people under 18 in the United Kingdom
The IWF’s 2026 report describes Report Remove as a confidential way for under-18s to report sexual content of themselves and seek removal. The IWF hotline also accepts public reports and pursues removal of confirmed criminal material. Eligibility and service scope can change; check the live IWF service information before submitting a report.
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If you operate a platform
UK government guidance describes monitoring hosted content with hash lists, acting on trusted-flagger reports and reviewing potential detections before reporting. Google says its Child Safety Toolkit gives partners access to processing and detection technology, and that its CSAI Match technology identifies known video CSAM. Partner access terms and availability should be confirmed directly with Google.
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- Do not download, forward, repost or otherwise circulate suspected material.
- Use the relevant hotline or platform reporting channel rather than sharing the file with others to seek confirmation.
- If a child may be in immediate danger, contact the appropriate emergency or law-enforcement service in your location.
Why synthetic material still matters
Synthetic does not mean harmless. NCMEC has noted harms to children depicted in manipulated images and the risk that such cases can impede identification of real victims. An image being AI-generated does not make it safe to circulate or automatically place it outside CSAM policies or legal restrictions.
Legal treatment depends on location
The IWF’s UK-specific explanation says realistic-looking AI-generated images are treated as real imagery under UK law, while non-photographic imagery is treated as prohibited imagery; it says both are criminal under UK law. This is not a worldwide rule. The IWF’s 2026 report notes that legislation varies internationally, so the UK explanation should not be applied to the United States, EU or another jurisdiction without checking current local law.
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