UK Law Enforcement Agencies Campaign to Employ Biased Face Scanning Systems

Police forces across the UK effectively campaigned to use a facial recognition system known to be biased against women, young people, and individuals from minority ethnic backgrounds, after complaining that a more accurate version produced a reduced number of potential suspects.

How the System Works

UK forces use the police national database (PND) to conduct searches using historical face recognition. This process entails matching a “probe image” of a suspect against a database of more than 19 million mugshots to identify potential matches.

Acknowledged Discrimination

The Home Office conceded last week that the system was flawed. This admission came after a review by the National Physical Laboratory (NPL) found it misidentified Black and Asian people and females at much greater frequency than white men. The ministry said it “took steps on the findings”.

“It prompts the issue of whether facial recognition only becomes useful if users tolerate biases in race and sex. Operational ease is a poor argument for overriding basic freedoms.”

Long-Standing Problem

Official papers reveal that this discriminatory flaw has been known about for over twelve months. Furthermore, police forces lobbied to reverse an initial decision that was designed to mitigate the problem.

Senior officers were notified of the system's bias in late 2024. The Home Office-commissioned laboratory study concluded the system was more likely to suggest false positives for photos of women, Black people, and those under 40 years old.

A Reversed Decision

In response, the national police leadership body mandated that the accuracy setting required for possible hits be raised to a point where the bias was significantly reduced.

However, this decision was reversed the next month after forces complained that the modified technology was generating a lower number of “investigative leads”. Internal records indicate the stricter setting cut the number of searches that yielded potential matches from 56% to a just under 15%.

Severe Disparities

Although the authorities declined to specify what threshold is now in operation, the latest NPL study found the system could produce incorrect matches for women of Black heritage nearly a hundred times more frequently than for Caucasian women at certain settings.

The ministry commented on these findings: “The testing found that in a specific scenarios the algorithm is has a greater tendency to wrongly flag some population segments in its match reports.”

Operational Effectiveness vs. Bias

Outlining the effect of the temporary raise to the system's confidence threshold, the NPCC documents state: “This adjustment significantly reduces the impact of discrimination across legally safeguarded attributes of race, generation and gender but had a significant negative impact on police efficiency”. The documents add that police units complained that “a previously useful tool returned outcomes of questionable value”.

Wider Implementation Proposals

Meanwhile, the UK administration has opened a ten-week public review on its plans to widen the use of facial recognition technology. The minister for police the relevant minister has described the tool as the “most significant advance since genetic fingerprinting”.

Criticism from Advisors and Monitors

The chair of a police oversight board, head of the independent scrutiny and oversight board for the national policing equality strategy, commented: “There was very little discussion through equality strategy sessions of the facial recognition rollout despite obvious cross-over with the plan’s concerns.

“These revelations demonstrate once again that the anti-racism commitments the police has undertaken via the equality initiative are failing to be integrated into wider practice. Independent assessments have warned that new technologies are being rolled out in a context where ethnic inequalities, inadequate oversight and faulty information gathering continue to exist.

“Any use of this technology must adhere to strict national standards, be subject to external review, and prove it reduces rather than compounds ethnic bias.”

Home Office Response

A Home Office spokesperson said: “We treat the conclusions of the study with utmost gravity and we have implemented changes. A new algorithm has been externally evaluated and acquired, which has demonstrated no measurable discrimination. It will be trialled in the coming months and will be subject to evaluation.

“Our priority is protecting the public. This revolutionary tool will assist police to put criminals and rapists behind bars. There is human involvement in each stage of the process and no arrest or charge would be taken without specialist personnel carefully reviewing the output.”

Larry Jackson
Larry Jackson

Elara is a systems engineer with over a decade of experience in performance analytics and monitoring technologies.