PP415      Half Unit
Technology, Data Science and Policy

This information is for the 2022/23 session.

Teacher responsible

Professor Alexander Evans (School of 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), MPA Dual Degree (LSE and Columbia), MPA Dual Degree (LSE and Hertie), MPA Dual Degree (LSE and NUS), MPA Dual Degree (LSE and Sciences Po), MPA Dual Degree (LSE 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. 

Course content

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.

Formative coursework

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. 

Indicative reading

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.

Key facts

Department: School of Public Policy

Total students 2021/22: Unavailable

Average class size 2021/22: Unavailable

Controlled access 2021/22: No

Value: Half Unit

Guidelines for interpreting course guide information

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Personal development skills

  • Self-management
  • Team working
  • Application of information skills
  • Communication
  • Specialist skills