UK Age-Scan Tests Misclassify 13.5-Year-Olds as 18, Exposing Bias in Asylum Checks
Updated
Updated · WIRED · Jun 18
UK Age-Scan Tests Misclassify 13.5-Year-Olds as 18, Exposing Bias in Asylum Checks
1 articles · Updated · WIRED · Jun 18
Summary
An internal Home Office report found the UK’s planned facial age estimation for asylum seekers regularly over-ages children, with female Sub-Saharan Africans misestimated by 4.6 years on average.
The April 2025 tests covered seven algorithms and more than 2.5 million images, yet even the “best performing” system showed substantial deviations, often pushing 17-year-olds above 18 and performing worse on females.
Those results may understate the risk because the testing relied mainly on high-quality images, while photos taken at first border encounters were described as routinely worse and trauma or travel stress appeared to distort estimates further.
The Home Office still plans a 2027 rollout as an added tool for officers, says uncertain cases will be treated as children, and has commissioned an independent review after declining to explain operational safeguards.
The findings have intensified opposition from rights groups—62 organizations urged the government to scrap the plan—especially after the UK spent more than $400,000 on face-scanning technology from Cognitec in May.
With known racial biases, how will the UK's new AI border guard protect children of colour?
If experts call it 'hideously inaccurate', why is the UK using AI to judge child asylum seekers?
UK to Deploy AI Facial Age Estimation at Borders in 2027: Technology, Bias, and Safeguards
Overview
The UK plans to introduce AI-driven Facial Age Estimation (FAE) at its borders in 2027 to help staff identify adults posing as children among asylum seekers. The system analyzes photos using AI trained on millions of images to spot age-related facial patterns, aiming to replace invasive scans and speed up assessments. However, FAE is not fully reliable—it has a margin of error, especially for 16- to 18-year-olds, and can be biased against certain groups, like Sub-Saharan African girls. Because of these risks, final decisions will remain with trained human officials, who must apply the benefit of the doubt in complex cases.