In December, I had the pleasure of participating in an expert panel addressing AI testing at the International Conference on Artificial Intelligence at Peterhouse College, at the University of Cambridge. You might be wondering what brought a cybersecurity researcher to an AI-centric event. I had the same scepticism when my multi-university research group decided we conduct AI-related research; what would my contribution be?
Our work has focused on defining meta-data for AI provenance, contributing to advancements in various facets of AI, including testing and auditability. Specifically, my focus lies on evaluating the dimensions of risk and trust within this context. Given the widespread impact of AI across diverse domains, there is a compelling opportunity for multidisciplinary research, consecutively, our group, has diverse expertise ranging from machine learning to psychology.
An initial publication on our work can be found here.
Author Dr Andrew M’manga







Prof. Ann Luce (FMC), Ms. Georgia Turner (PhD candidate FST), Ms. Lauren Kennedy (MSc student FST) and Dr. Reece D. Bush-Evans (Lecturer in FST) are pleased to announce the publication of their most recent work in British Medical Journal: Medical Humanities titled, “Quite simply they don’t communicate: a case study of a National Health Service response to staff suicide”. 

























BU academic publishes in online newspaper in Nepal
Final day of the ESRC Festival of Social Science
Using Art to enhance Research
Register now to attend the 17th Annual Postgraduate Research Conference – Wednesday 3 December 2025
Portrait Concert featuring BU academic at L’Espace du Son Festival 2025, Brussels
ECR Funding Open Call: Research Culture & Community Grant – Application Deadline Friday 12 December
MSCA Postdoctoral Fellowships 2025 Call
ERC Advanced Grant 2025 Webinar
Horizon Europe Work Programme 2025 Published
Horizon Europe 2025 Work Programme pre-Published
Update on UKRO services
European research project exploring use of ‘virtual twins’ to better manage metabolic associated fatty liver disease