GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs)

no code implementations • 3 Nov 2022 • Emily Jefferson, James Liley, Maeve Malone, Smarti Reel, Alba Crespi-Boixader, Xaroula Kerasidou, Francesco Tava, Andrew McCarthy, Richard Preen, Alberto Blanco-Justicia, Esma Mansouri-Benssassi, Josep Domingo-Ferrer, Jillian Beggs, Antony Chuter, Christian Cole, Felix Ritchie, Angela Daly, Simon Rogers, Jim Smith

This is a complex topic, and it is unreasonable to expect all TREs to be aware of all risks or that TRE researchers have addressed these risks in AI-specific training.

Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities

no code implementations • 10 Nov 2021 • Esma Mansouri-Benssassi, Simon Rogers, Jim Smith, Felix Ritchie, Emily Jefferson

In this paper we introduce the challenge of disclosing trained machine learning models from TREs.

BIG-bench Machine Learning Decision Making +1

Confidentiality and linked data

no code implementations • 15 Jul 2019 • Felix Ritchie, Jim Smith

Data providers such as government statistical agencies perform a balancing act: maximising information published to inform decision-making and research, while simultaneously protecting privacy.

Decision Making