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