GoKawiilThe Think Family Database holds records on close to half a million people who live in the city of Bristol, England. For many years, few of them knew anything about it.
Launched in 2016 by the Bristol City Council and the regional Avon and Somerset Police, the database has stored all manner of sensitive information—police intelligence reports, housing status, mental health records, teenage pregnancies, enrollment in parenting courses, free school meals. On top of this sensitive data, officials built machine-learning models to assign scores to thousands of adults and children. They hoped to build what they called a “picture of threat, harm, and risk” in the region. At an event in early 2022 to help officials tackle child exploitation crimes, one police data scientist described part of the approach this way: “I essentially dump all that data in a big bucket and stir it with a data-science spatula, and we come out with a lovely risk score for everybody.”
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This risk scoring inside the Think Family Database was just one part of Avon and Somerset Police’s sprawling predictive analytics program. Among at least 23 separate models the force created were algorithms to identify the risk that people would commit burglary, fail to turn up in court, go missing, or become a victim of domestic abuse. One senior officer described creating a “league table” of the area’s most dangerous criminals—an apparent reference to the Offender Management App, which was designed to hold data on around 300,000 people in the region.
John Pegram says he wants police to scrap the Offender Management App. Photograph: Alice Zoo
How the police have developed and used their predictive tools hasn’t always been clear to the public. John Pegram, the leader of a local police accountability group in Bristol, says he didn’t hear about the Offender Management App until 2023, years after it had been created. When he did learn about it, he began to suspect he might be included. “I think I knew I was on the app,” Pegram says.
In early 2024, Pegram filed a request to find out how the police were using his data. The police refused to say. Months later, after Pegram had hired solicitors to work on his case, the police confirmed he was on the app but declined to elaborate further. Like others across Bristol, the UK, and, increasingly, around the world, Pegram didn’t know whether he had been scored by an algorithm, what that score might be, or how it could affect his interactions with the authorities.
WIRED, working in partnership with the nonprofit newsroom Liberty Investigates, plus the Bristol Cable and Lighthouse Reports, obtained hundreds of pages of documentation from public records requests to build the most comprehensive picture to date of Avon and Somerset’s regional experiment with data collection and predictive analytics. (Liberty, the parent organization of Liberty Investigates, had some early involvement in a potential legal challenge to the program and continues to support Pegram’s litigation.)
The investigation reveals that at least two of these risk-scoring models were quietly abandoned after Bristol City Council staff deemed they could no longer trust them. Previously unreported documents show government inspectors and independent reviewers highlighting a startling lack of transparency about some elements of the program and warning that the systems could undermine public trust. Police data disclosed to WIRED—comprising more than 36,000 model performance scores—appear in some cases to show “genuinely poor predictive performance,” according to an independent analyst who reviewed the data for WIRED.