London: The UK government is under fire for developing a controversial “murder prediction” program aimed at using personal data to identify individuals most likely to commit serious violent crimes. Originally dubbed the “homicide prediction project,” the initiative has since been rebranded as “sharing data to improve risk assessment.”
Documents uncovered by the civil liberties group Statewatch through Freedom of Information (FOI) requests reveal the Ministry of Justice (MoJ) is collaborating with police and probation services to analyze data of thousands of individuals, including personal health records and contact history with law enforcement.
According to Statewatch, this includes data from people not convicted of any crimes, such as those who reported domestic violence or self-harm. Sensitive information like mental health status, addiction, and disability has also been listed under “special categories of personal data.” However, the MoJ insists that only data on individuals with at least one criminal conviction is being used.
The project, commissioned during Rishi Sunak’s tenure as Prime Minister, uses historical data from Greater Manchester Police (pre-2015) and the Probation Service to identify “offender characteristics” that may increase homicide risks. The government claims the program remains at a research stage and is intended to enhance public safety by improving current risk assessment tools.
A spokesperson from the MoJ said, “This project is being conducted for research purposes only. It has been designed using existing data on convicted offenders to understand the risk of serious violence. A report will be published in due course.”
Despite these assurances, campaigners have slammed the initiative as “chilling and dystopian.” Sofia Lyall, a researcher at Statewatch, warned, “This is the latest example of the government’s dangerous push to build so-called crime prediction systems. These tools are flawed, and by relying on data from historically discriminatory institutions, they risk further targeting racialized and low-income communities.”
Critics argue that integrating health and vulnerability data into predictive systems not only violates privacy but also amplifies existing structural biases. They fear the system will unfairly label vulnerable individuals as potential threats based on profiling rather than proven behavior.
The debate continues over the ethical boundaries of predictive policing, with many calling for transparency and accountability in how such sensitive data is used. As the government pushes forward, concerns over privacy, discrimination, and algorithmic justice remain front and center.
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