Design for data ethics: Using service design approaches to operationalize ethical principles on four projects

Abstract

Ethical frameworks provide helpful guidance about what you should-and should not-do in relation to data projects. But they do not provide definitive yes/no answers about what an ethical data project is or is not. Indeed, research (Ipsos-MORI 2015 Public dialogue into the ethics of data science in government) conducted for the initial development of the Government's Data Ethics Framework shows that the public does not hold any clear red lines; rather, they make nuanced assessments based on a number of variables, including public good and privacy. Ethical frameworks provide a list of these variables to consider in shaping the form of the work. Some are now starting to provide more practical tools and guidance to reshape data projects and push it along those variables into a more ethical space. Alongside technical tools, service design approaches can help enhance the degree to which a data project is ethical, and provides a toolkit for data scientists, analysts and policymakers to take projects from 'what should we do' to 'how can we do it'. This paper sets out the emergence of data science ethical frameworks within the context of the use of data for social good, and-with the recent release of the updated UK Government Data Ethics Framework-shows the recognition more practical guidance needs to be provided. The author then argues that service design approaches provide a helpful 'wrap around' for data projects, and draws on experience in using service design tools on four projects, as well as wider examples. This article is part of a discussion meeting issue 'The growing ubiquity of algorithms in society: implications, impacts and innovations'.