Professor Alexander Evans

This course is compulsory on the MPA in Data Science for Public Policy. This course is available on the Double Master of Public Administration (LSE-Columbia), Double Master of Public Administration (LSE-Sciences Po), Double Master of Public Administration (LSE-University of Toronto), Master of Public Administration, Master of Public Policy, MPA Dual Degree (LSE and Hertie), MPA Dual Degree (LSE and NUS) and MPA Dual Degree (LSE and Tokyo). This course is available with permission as an outside option to students on other programmes where regulations permit. This course uses controlled access as part of the course selection process. For information on controlled access courses, including eligibility, application processes, deadlines, and departmental contact details, please refer to the Controlled Access Courses webpage.

Priority given to School of Public Policy students. Students from outside of the School of Public Policy should submit a statement in support of their request.

Deadline for application: 9am on Monday of AT Week 1 (including requests from School of Public Policy students). We aim to inform students of the outcome of their request by 12noon on Tuesday of AT Week 1.

For queries contact: spp.doubledegrees@lse.ac.uk

Basic familiarity with technology issues, machine learning and artificial intelligence is helpful. The course does not require any computer programming. 

Technology and Data Science are now a major driver of many areas of public policy. This course will present a globally comparative, integrated and historically informed perspective on key policy issues in technology, data science, and emerging technologies such as AI. This course will examine applied technology and data science policy from the following prisms: strategy, standards, regulation, industrial strategy and AI and emerging technologies. The course will have an inter-disciplinary approach that will consider policy issues from the point of view of governance, security, ethics, and the law.  The course will also cover data science ethics and discuss emerging issues with artificial intelligence. Students will emerge with a holistic view of the role of technology and data science in society and government, including policy case-studies and guest speakers from practice.

33 hours of seminars in the Autumn Term.

The course will have two 90 minute ‘Harvard style’ whole group teaching sessions per week - all students taking the course will need to attend both teaching sessions each week. 

Students will submit the outlines of their essays and policy memos (in bullet point format) for formative feedback prior to submitting the final written versions for summative assessment. There will also be a formative presentation, with feedback, to develop policy presentation skills.

• David Edgerton, The shock of the old (2019)
• Chris Miller, Chip War: the fight for the world’s most critical technology (2022)
• Nigel Inkster, The Great Uncoupling (2020)
• Nicole Perlruth, This is how they tell me the world ends (2021)
• Caroline Perez, Invisible Women (2019)
• Henry Farrell, Abraham Newman and Jeremy Wallace, ‘Spirals of Delusion: How AI Distorts Decision-Making and Makes Dictators More Dangerous’ Foreign Affairs (Sep/Oct 2022)

Essay (60%).

Memo (40%).

Essay (60%, 3000 words) and policy memo (40%) in the AT.