Prisons trial AI to forecast conflict and self‑harm risk
Scanning millions of phone messages enables detection of hidden threats, such as gang coordination or escape planning.
UK Justice Secretary Shabana Mahmood has rolled out an AI-driven violence prediction tool across prisons and probation services. One system evaluates inmates’ profiles, factoring in age, past behaviour, and gang ties, to flag those likely to become violent. Matching prisoners to tighter supervision or relocation aims to reduce attacks on staff and fellow inmates.
Another feature actively scans content from seized mobile phones. AI algorithms sift through over 33,000 devices and 8.6 million messages, detecting coded language tied to contraband, violence, or escape plans. When suspicious content is flagged, staff receive alerts for preventive action.
Rising prison violence and self-harm underscore the urgency of such interventions. Assaults on staff recently reached over 10,500 a year, the highest on record, while self-harm incidents reached nearly 78,000. Overcrowding and drug infiltration have intensified operational challenges.
Analysts compare the approach to ‘pre‑crime’ models, drawing parallels with sci-fi narratives, raising concerns around civil liberties. Without robust governance, predictive tools may replicate biases or punish potential rather than actual behaviour. Transparency, independent audit, and appeals processes are essential to uphold inmate rights.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!