London Metropolitan Police's head of digital forensics says it will use AI to scan for child abuse images on suspects' devices within two or three years
Artificial intelligence will take on the gruelling task of scanning for images of child abuse on suspects' phones and computers …
Context & Ripple Effects
In late 2017 the Met's head of digital forensics committed the force to AI triage of seized devices within two to three years — an answer to examiners manually viewing graphic material at a volume that scales with every phone seized.
The years since validated both halves of the bet: the UK has since planned a wider rollout of police AI including biometric and facial-recognition systems, while the Internet Watch Foundation's warning that generative AI was producing unlawful abuse imagery hardened into hard numbers — 8,029 AI-generated images and videos identified in 2025 alone. The scanner the Met proposed now faces a target that machine generation keeps enlarging.
First-order effects
- Met forensic examiners shift from viewing every image by hand to reviewing classifier-flagged material, cutting exposure to traumatic content and shortening how long seized devices sit unexamined.
- Vendors of image-classification systems gain a flagship law-enforcement reference customer whose requirements — evidentiary accuracy, auditability — set the technical bar for the category.
Second-order effects
- Other UK forces are positioned to follow the Met's template, consistent with the national push toward expanded police AI deployment rather than force-by-force experimentation.
- Detection pipelines must now classify synthetic as well as photographic abuse material, forcing classifier vendors to retrain against AI-generated imagery precisely as the IWF's growth figures show that supply accelerating.
Third-order effects
- Policing AI settles into a two-sided structure: the same generative capability that multiplies the contraband also powers the triage tooling, making forensic classifiers and synthetic-content detection a permanent procurement line for forces rather than a one-off project.
- Automated classification of criminal evidence pushes courts and regulators toward standards for how machine-flagged material enters prosecution — the same governance question raised by the UK's broader biometric-policing plans.
The trend: Law-enforcement AI is scaling on both sides of the same problem at once — forensic classifiers triage ever-larger device seizures while generative models multiply the synthetic abuse imagery those classifiers must catch.