How the Ministry of Justice used AI to compare prison reports
Learn how the Ministry of Justice (MoJ) used natural language processing to identify patterns across prison reports.
This guidance is part of a wider collection about using artificial intelligence (AI) in the public sector.
AI application used
- natural language processing (NLP)
Objective
MoJ needed to compare how various factors including geography, and incidents such as inmate conflict, affected different prisons.
Situation
MoJ had over 250,000 sentences of unstructured text in over 500 reports detailing their inspections of prisons and other institutions. These reports were from:
- HM Inspectorate of Prisons
- the Independent Monitoring Board
- the Prisons and Probation Ombudsman
- Ofsted reports into secure training centres
There were too many reports for staff to quickly access relevant information.
Action
MoJ trained a neural network on the prison reports to track how people use specific words in prison contexts. The algorithm groups words with similar meanings to form an ‘intelligent search’ tool. New reports are automatically added to the tool’s library so the data remains up-to-date. This means staff can rapidly uncover information buried in the reports and identify trends.
Impact
The tool helps MoJ:
- identify patterns of issues and incidents across prisons
- identify geographic patterns affecting prisons
- inform data-driven decisions about prison inspections and policy
Related guides
- Understanding artificial intelligence
- Assessing if artificial intelligence is the right solution
- Planning and preparing for artificial intelligence Implementation
- Managing your AI project
- Understanding artificial intelligence ethics and safety
- Examples of real-world artificial intelligence use
- National Cyber Security Centre guidance for assessing intelligent tools for cyber security
- The Data Ethics Framework
- The Technology Code of Practice