The UK Will Scan Asylum-Seekers’ Faces for Age Checks—Despite Knowing the Tech Is Flawed

Age verification is consuming the internet. From social media bans in Australia to porn restrictions in half of US states, for many having to prove their age to access websites is becoming an everyday requirement. But one of the key technologies underpinning many of these age checks is about to seep into the offline world—with potentially life-changing consequences for people having their age predicted by AI.

Starting next year, the British government is planning to introduce facial age estimation—where AI scans your face and suggests how old you are—to help determine the age of asylum seekers arriving at the United Kingdom’s border. The move is believed to be the first time that a so-called facial age estimation (FAE) system has been used in this way. Many asylum seekers arriving in the UK will not have documents proving their age, and if children are incorrectly classed as adults, they can be stripped of some legal protections and placed in adult-only detention centers.

An investigation by WIRED and Lighthouse Reports, in collaboration with The Independent, has obtained an internal UK government report detailing its tests of FAE technologies. It shows how the systems regularly mistake children for adults and appear to contain serious bias problems, which directly impact the largest group of migrants subject to age assessments in 2025, according to data from the Home Office. The investigation raises questions about the effectiveness of the technology and whether it should be deployed in such high-stakes scenarios.

The findings also come as the second Trump administration and governments around the world increasingly adopt anti-migrant policies while spending billions on surveillance technology that is often deployed against vulnerable people who have little knowledge of its use, how it works, or ways they can challenge it.

The leaked Home Office document obtained by Lighthouse Reports largely details the “best” performing of seven facial age estimation algorithms that the department tested last year, although it does not directly name the companies behind them. The report found that the system performed significantly worse when it was used to estimate the ages of Sub-Saharan Africans compared to other groups. Sub-Sarahan Africans are the largest group of migrants entering the UK after crossing the English Channel in small boats in recent years and had more age assessments raised in 2025 than cohorts from other regions, according to Home Office data. For female Sub-Saharan Africans, the age that the system guessed was off by an average of 4.6 years, meaning that a 13.5-year-old girl could be assessed as an 18-year-old adult.

The investigation also found that the Home Office, which oversees UK immigration and policing, disbanded a scientific committee designed to advise it on broader age estimation methods while it was exploring the introduction of AI. “We were keen to highlight the inadequacies of facial age estimation, but this opportunity was not presented to us, and then the committee was shut down,” says Tim Cole, an emeritus professor of medical statistics at University College London’s Institute of Child Health and former committee member. Cole describes the face scans as “hideously inaccurate.”

In addition to the internal report and the scientific committee members’ concerns, years of test results from the US National Institute of Standards and Technology have shown that FAE systems’ accuracy often depends on the race of the person being analyzed and the quality of the photos taken of them.

“We have rigorous processes in place to verify an individual’s age and are working to modernize these through the testing of fast and effective facial age estimation technology,” a Home Office spokesperson says in response to the findings. The spokesperson adds that the committee was disbanded due to requiring “different fields of expertise.”

While the Home Office says face scanning is designed to be an “additional” tool for border officers and won’t “replace or overrule human judgment,” it did not answer questions about how it plans to use the technology in real-world environments. “In cases of uncertainty,” the spokesperson says, “individuals will always be treated as children until a further assessment is conducted.”

Expanding Estimates

The UK government first announced its plans to use face age estimation alongside border staff judgments to assess migrants in July 2025. Since then, the Home Office has delayed the rollout of the systems until 2027, saying it will use the “cutting-edge AI tech” to “crack down on fake claims” with the aim of stopping “adults attempting to game the system.”

Over the past five years, AI face scans have emerged as a key component of controversial online age verification programs, as lawmakers have mandated social media platforms, porn websites, and some retailers check their users’ ages. It has also been trialled at some bars and shops in the UK. Face age estimation works by analyzing the features of someone’s face—with the underlying systems trained on millions of age-labeled faces—to produce an estimated age. In controlled laboratory tests, the best algorithms can predict a person’s age to within around 2.5 years.

However, the results can vary wildly depending on the algorithm, a person’s gender, demographic details, and other factors. Poor-quality images, such as those with bad lighting, can drastically reduce the performance of the systems. (A case in point: People have tricked some systems using images of characters from video games.) The Home Office appears to have been aware of potential problems with the technology and still pushed ahead with its program.

The leaked Home Office report produced in April 2025, which was completed before the government purchased face-scanning technology, details the testing of seven FAE algorithms against more than 2.5 million images. However, the internal report says that the unnamed “best performing algorithm” had “substantial deviations” when tested on images of Sub-Saharan Africans. On average, that system also tended to predict that a 17-year-old would be over 18, and it performed worse on females.

Tens of thousands of people make asylum claims in the UK each year, with many arriving in the country after dangerous, physically demanding journeys in small boats crossing the English Channel. Currently, border staff who doubt the age of someone claiming to be under 18 can assess their physical appearance, answers to interview questions, and general demeanor, to make an initial decision about their age. These initial age estimations are made upon the “first encounter,” the Home Office says in guidance. Since 2010, 40 percent of people who have faced age assessments have been classed as adults, according to official statistics.

The leaked Home Office report says that its findings are based primarily on testing that uses high-quality images taken of documented people, and that may mean that the algorithms’ accuracy rates would be even worse in practice. The Home Office has indicated that FAE technology would help immigration officers who are making age assessments while working at the point of first encounter.

According to the internal report, the few photos included in the testing data that were taken at initial encounters were “routinely worse” than follow-up photos of the same people. The photo quality was apparently so bad that the report was unable to determine if that or the physical condition of asylum seekers at arrival had more of an impact on the algorithms’ age estimation results. NIST’s own testing has found that for many age estimation algorithms, lower-quality photos typically lead to larger errors. The internal report concluded that more needed to be done to study the impacts of stress that asylum seekers endure before arriving at their destination.

“Children seeking asylum have often suffered unimaginable trauma,” says Martha Dark, the co-executive dir