Course summary

An innovative, interdisciplinary degree with Edinburgh Futures Institute Technology and data are transforming governance across the globe. How we apply ethical and innovative use of data and technology to society’s most pressing challenges is key to how we govern our future world. This new MSc programme in the Edinburgh Futures Institute (EFI) explores and analyses the challenges and opportunities that big data brings to the future of democracy. This is a unique, new interdisciplinary programme offering an innovative approach to study that will help you develop advanced thinking in governance and policy-making for the future. It is for critical thinkers who seek to develop leading-edge knowledge to help them shape the world, and their careers, by driving positive change through policy and decision-making. You will gain the skills and knowledge required to evaluate and use diverse data sources and emerging technologies to understand, critique and shape the future of governance. The cross-sector, interdisciplinary approach used within the Futures Institute showcases the very best the University of Edinburgh has to offer and includes collaboration with policy and communication experts and decision-makers across the public, private and third sectors. You will:

• develop a deep understanding of democracy and participation in an era of rapidly developing technological change and data-driven decision-making

• interrogate the challenges and opportunities that new and big data sources bring to the future of governance

• increase your knowledge of ethical decision-making in the context of data-driven policy-making, and your confidence in using new and big data

• learn to identify the most appropriate methods required to address policy issues and learn how to apply a strong, critical and interdisciplinary understanding to the challenge of our democratic futures

• core data skills

• data ethics

• the ability to interrogate issues of global scope using methods from across disciplines

• creative and analytic approaches to knowledge