Admission requirements
Required course(s):
None, but the successful completion of at least Institutions of Governance & Development and one 200-level Governance, Economics & Development (GED) course is strongly recommended.
Description
This course is designed to teach students about government use of data-driven approaches to governance and policymaking. The course has a practical and utilitarian component, which is to introduce students to what these applications are, both those that are mundane and those that
are controversial. It also has an analytical component, which is to apply critical thinking towards such applications using findings from scholarly literature and public discussion about real cases.
On the first component, it will address questions of how the technologies work and why governments use them. For example, students will be introduced to the basic working principles of predictive policing and smart public installations such as lighting and traffic systems. These are each different in important ways and there are different technical and social consequences. Students will learn about key technology ‘affordances’ and frameworks to help know what to highlight and be critical of.
A second component will involve learning about real world cases and the arguments and evidence available from academic research. This component will pose questions such as what ethical issues arise from use of the technologies, whether robots will decide all the important matters that affect our lives, and whether there is anything that governments and citizens can do to use technologies to make government better. For example, we will review and discuss Google’s failed smart city project in Toronto. The global spread of big data technologies will be used as an opportunity to learn about a wide variety of countries and cities.
Students will learn to navigate the complex technical and ethical issues and put forward their own arguments through discussion and debate. Together, these skills and knowledge will help students to critically assess these tools and to become more expert both as critical users of technologies and as systems architects.
Course Objectives
Analyze examples of different kinds of data-driven applications in public services
Weigh, consider, and discuss the public values pros and cons of data-driven decision making in the public sector using real world examples and academic literature
Carry out a research project that critically evaluates an algorithmic decision-making system from the perspective of protecting and improving public values.
Timetable
Timetables for courses offered at Leiden University College in 2024-2025 will be published on this page of the e-Prospectus.
Mode of instruction
Seminar-based discussions of course topics. In particular, the course will employ case studies for each sub-topic to situate research and theory in examples of real-world practice.
Active student participation is a non-negotiable requirement for this course.
Assessment Method
Class participation (individual)
Written policy memo (individual)
Oral analysis briefing (indvidual)
Written research report (group)
Reading list
The reading list will be made available through the course syllabus on Brightspace.
Registration
Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator, course.administration@luc.leidenuniv.nl.
Contact
Dr. Matthew M. Young, m.m.young@fgga.leidenuniv.nl
Remarks
Students should be prepared to engage in dialog about each class’ topic (including the associated readings) not only with the instructor but with their peers. Laptop use in class is not allowed without a University-approved statement of need.