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Police watchdog finds facial recognition checks and custody image retention fall short

An HM Inspectorate of Constabulary and Fire & Rescue Services report on retrospective facial recognition warns that some officers treat matches as evidence, risking wrongful arrests, and that custody images that should have been deleted remain searchable.

2 outlets · 1L · 1C · 0R First reported Account updated
Image: The Guardian
Image: Evening Standard

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The story, neutrally told

Mixed · 2A report by His Majesty's Inspectorate of Constabulary and Fire and Rescue Services, published on Wednesday 11 November 2026, found that some police officers risk wrongly arresting people if they treat retrospective facial recognition (RFR) results as evidence. Mixed · 2The inspectors said that in a small number of cases officers relied too heavily on RFR results, which led to inappropriate investigative action, and that experienced investigators generally understood the limits of the technology while less experienced ones often did not. Left · 1The Guardian reports the inspectors found continuing bias in the algorithm, including a greater likelihood of wrongly flagging people from ethnic minorities, and that some users uploaded poor-quality probe images such as blurred pictures or images with multiple faces.

Mixed · 2Inspectors also found that custody images that should have been deleted under existing retention rules remained available for facial recognition searches, which they said risks undermining public confidence. Mixed · 2The report said legislation has not kept up with the technology and there is no comprehensive statutory framework governing police use of facial recognition, and that governance and oversight were not sufficiently consistent across policing. Centre · 1The report found some forces were not complying with national audit requirements: of forces in England and Wales, two audited the correct number of RFR files, seven had no auditor appointed and ten audited more than the 1% of records required.

Centre · 1Inspectors visited seven police forces (British Transport Police, the Metropolitan Police, Cheshire, Dorset, Gwent, Northumbria and Surrey) and the National Crime Agency in March and April this year, and recommended better national and local governance, clear national standards, and improved oversight and training. Left · 1His Majesty's Inspector of Constabulary Kathryn Stone said forces must show safeguards are in place, bias and data retention risks are managed and decisions remain subject to human judgment, and called for a clearer statutory framework and stronger national standards. Left · 1Jasleen Chaggar of Big Brother Watch called the findings alarming, said police were not logging their RFR use, and argued police should not continue using the algorithm with so few safeguards and at settings more likely to misidentify women, Asian and black people.

Left · 1Ben Russell, the National Police Chiefs' Council lead on facial recognition, said policing remains committed to ethical, proportionate and responsible use of RFR and was pleased the inspectorate recognised its possibilities. Left · 1Prof Pete Fussey of the University of Southampton, formerly a police adviser on facial recognition, said meaningful human scrutiny of AI systems is a legal requirement and that the report gives examples of investigators accepting the computer's suggestions without further checks. Centre · 1Earlier this month the Home Office pledged tougher laws on police use of live facial recognition, to be introduced under the Police Reform Bill so it is intelligence-led and proportionate, and a new algorithm is being trialled after 2024 concerns that minority ethnic people, women and those in their 20s were more likely to appear in search results.

Every sentence links to the reporting it rests on. The pill in front of each says where its sources sit: Left, Centre or Right when one side supplies at least half of them, Mixed when they are evenly split. The number is how many outlets it cites.

Left1 outlet

Framing
Leads on the risk of wrongful arrest, especially of ethnic minorities, from errors and bias in the technology.
Emphasis
Algorithmic bias, poor-quality probe images, and critical voices (Big Brother Watch, Prof Pete Fussey) alongside the inspector and police chiefs.
Leaves out or plays down
Does not give the NPCC audit compliance figures or the list of forces inspected.
Charged language
“alarming”“bona fide evidence”
For example
“Police officers risk arresting innocent people, especially from ethnic minorities, if they treat inaccurate facial recognition data as evidence, an official report has found.” — The Guardian

Centre1 outlet

Framing
Leads on custody photos that should have been deleted still being usable in facial recognition searches.
Emphasis
Inconsistent oversight, audit compliance figures, training gaps among junior officers, and the Home Office's planned legislation.
Leaves out or plays down
Does not report the report's findings on bias against ethnic minorities or include comment from campaigners or police chiefs.
For example
“Custody photographs that ought to have been deleted are being wrongly retained and can still be picked up in facial recognition searches, a watchdog has warned.” — Evening Standard

Right0 outlets

No right outlet in our sources has covered this story yet.

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