The Government will use AI to carry out age assessments on migrants after some adults pretended to be children. A report by the independent immigration inspector revealed that children were also being wrongly identified as adults, making it harder for them to apply to stay in Britain. Last year, 56% of migrants who claimed to be children were eventually found to be adults, either through further assessments or after admitting it themselves.
Inspectors also studied a sample of 100 case files, 38 of which had initially been assessed as an adult by the Home Office. However, after further assessment by a local authority, this number went down to 22. It is understood that the new age assessments will involve existing technology used by online retailers that sell age-restricted products.
Facial Age Estimation, as it will be known, presents a much quicker and cheaper option to determine someone’s age than bone X-rays or MRI scans, and does not require a physical medical procedure or accompanying medical supervision.
Currently, age assessments are based on the guesswork of immigration officials and social workers, but the Home Office and independent immigration inspector both noted how “challenging” this is.
David Bolt, the Independent Chief Inspector of Borders and Immigration, conceded that it’s “inevitable that some age assessments will be wrong” as there is no “foolproof test”.
He highlightes the case of a male who claimed to be 17 after arriving in a small boat, but was later assessed to be 22 by the Home Office due to his “deep voice”, “fully developed facial structure”, and “thick black stubble”.
The Government will begin trialling the technology before it’s rolled out in 2026, and an offer for providers of the AI technology will be launched in August.
Border Security and Asylum Minister Angela Eagle said the AI is “able to produce an age estimate with a known degree of accuracy for an individual whose age is unknown or disputed”.
She said in a statement on Monday: “We have concluded that the most cost-effective option to pursue is likely to be Facial Age Estimation, whereby AI technology – trained on millions of images where an individual’s age is verifiable– is able to produce an age estimate with a known degree of accuracy for an individual whose age is unknown or disputed.
“In a situation where those involved in the age assessment process are unsure whether an individual is aged over or under 18, or do not accept the age an individual is claiming to be, Facial Age Estimation offers a potentially rapid and simple means to test their judgements against the estimates produced by the technology.”