AI for Prison Education - sponsored by Meganexus

AI for Prison Education - sponsored by Meganexus

Thursday, June 12, 2025 2:10 PM to 2:40 PM · 30 min. (Europe/London)
Wesley, Level 4
Seminar
Full Agenda Modernising Criminal Justice 2025Seminar Sessions

Information

This session presents - GENAIE, a generative AI personal education system used by His Majesty’s Prison and Probation Service (HMPPS) to explore innovations in education and training, as a means of supporting rehabilitation to reduce re-offending; a £17bn problem for the UK Ministry of Justice. The demand for high-quality, multilingual learning content in prison education is growing, yet resource constraints and skill shortages hinder keyworker content creation. This study explores the role of generative AI in addressing these challenges, focusing on time efficiency, reduction in skill requirements, and AI-assisted translation. Using an experimental approach with the GENAIE generative AI tool during a large-scale content pilot, we evaluated AI’s impact on content generation, translation, and Subject Matter Expert engagement. Findings indicate up to 96% reduction in content creation time, the ability to translate educational materials into up to 109 languages at a rate of 105,000 words per minute with 88% accuracy, and a significant decrease in reliance on Subject Matter Experts. These results suggest that generative AI can help education providers overcome resource and skill limitations, enabling scalable and accessible learning content in multiple languages. This has profound implications for enhancing digital learning opportunities in prison education and beyond. This is part of a larger University College London-Meganexus ‘AI for Social Good’ research programme to help educate disadvantaged people including the long-term unemployed, long-term sick, and underprivileged children.

Seating
Due to the interest expressed in this session, places will be allocated on a first come, first serve basis. If you would like to attend, please ensure you arrive early to avoid disappointment.