杏吧论坛

Professor Alexander Evans (School of Public Policy)

This course is available on the Double Master of Public Administration (杏吧论坛-Columbia), Double Master of Public Administration (杏吧论坛-Sciences Po), Double Master of Public Administration (杏吧论坛-University of Toronto), MPA Dual Degree (杏吧论坛 and Columbia), MPA Dual Degree (杏吧论坛 and Hertie), MPA Dual Degree (杏吧论坛 and NUS), MPA Dual Degree (杏吧论坛 and Sciences Po), MPA Dual Degree (杏吧论坛 and Tokyo), Master of Public Administration and Master of Public Policy. This course is available with permission as an outside option to students on other programmes where regulations permit.

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. 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 present a brief history of technology and technology policy, consider the role of technology in government, cover main areas of 21st century technology policy, with a focus on competition and regulatory diplomacy and national strategies. The course will then cover key concepts in data science ethics broadly 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.

22 hours of lectures and 16 hours and 30 minutes of seminars in the LT.

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 assesment. 

A detailed reading list will be provided by the instructor prior to the start of the course.

Essay (35%, 3000 words), group presentation (30%) and policy memo (35%) in the LT.