Michael, who became a Cumberland Lodge Scholar in 2016, is a PhD student at University College London (UCL), working across the Departments of Science, Technology, Engineering and Public Policy (STEaPP) and Computer Science, co-supervised by the Government Office for Science.  

His research focuses on the responsible use of data-driven technologies in the public sector. For example, machine learning (sometimes called 'weak Artificial Intelligence') is a technology able to discern and act upon patterns in datasets, already being introduced in areas ranging from taxation to policing, to help ensure that public sector values such as fairness and accountability are preserved has emerged as a challenge. His research aims to understand how value concerns can practically feed into social and technical aspects of these decision-making and decision-support systems.

Michael has presented and lectured at many government departments, NGOs and universities. He leads the Analytic Methods for Policy module on UCL STEaPP’s Master’s of Public Administration (MPA), and is an external data governance researcher in the science–policy team at the Royal Society. Previously, he worked in the European Commission (DG Health & Food Safety) on connected technologies for an ageing population, and as a visiting data scientist at Bonsucro, the world’s largest metric sustainability standard for the sugarcane sector.  

Michael also has a BSc in Government & Economics from LSE and an MSc in Sustainability, Science and Policy from Maastricht University.  

He tweets at @mikarv.

 

Position: 
Cumberland Lodge Scholar, 2016-18
Team: