Ethical Machine Learning

Injecting Ethical and Legal Constraints into Machine Learning Models

Equipping ML models with ethical and legal constraints is a serious issue as without this the future of ML is at risk. In the UK, this is recognized by the House of Commons Science and Technology Committee, which has formed a Council of Data Ethics.

Building ML models with fairness, confidentiality, and transparency constraints is an active research area, and disjoint frameworks are available for addressing each constraint. However, how to put them all together is not obvious. Our long-term goal is to develop an ML framework with plug-and-play constraints that is able to handle any of the mentioned constraints, their combinations, and also new constraints that might be stipulated in the future.

Funded by Engineering and Physical Sciences Research Council (EPSRC): 1 October 2017 - 31 March 2019 (£100,675).