LSE100      Half Unit
The LSE Course

This information is for the 2021/22 session.

Teacher responsible

Dr Christopher Blunt and Dr Jillian Terry


The course will be compulsory for all first year undergraduate students.

Course content

LSE100, LSE's flagship interdisciplinary course, is designed to enhance your undergraduate education by giving you the opportunity to learn from LSE’s leading academics from across the School and engage with ideas that transcend disciplinary boundaries. In this course, you will have the chance to collaborate with peers from other degree programmes, expanding your methodological skills, deepening your understanding of disciplinary modes of thinking, and synthesizing ideas from across disciplines to achieve comprehensive understanding of complex social issues. You will explore the relationship between theory, evidence and explanation, and develop your skills in thinking critically and creatively about complex issues. LSE100 aims not only to broaden your education and intellectual experience at the School, but also to deepen your understanding of your own discipline.

In 2021/22, LSE100 will focus on one of the most critical challenges of our time: ‘How can we control AI?’. In this module, you will explore the emergence of artificial intelligence and its implications using the ‘wicked problems’ framework, and investigate the ways in which social systems could be transformed by technological change. Using systems thinking tools for directing change, you will analyse the impact of AI on systems such as transportation, the labour market, criminal justice, and global security. In the process, you will gain expertise in the tools of systems thinking and continue to broaden your intellectual experience and deepen your critical understanding of your own discipline as you test theories, evidence and ideas from different disciplinary perspectives. You will also develop your research, communication, teamwork and leadership skills as you apply your intellect and creativity to the challenge of directing technological change. The Michaelmas Term will give students a common foundation in these concepts, all of which facilitate deeper understanding of disciplines and the benefits of interdisciplinary thinking.

In the Lent Term, you will deepen your engagement with social scientific understandings of AI and technological change through a group research project where, working in small, multi-disciplinary teams, you will select an area within your stream for further investigation. Your team’s work will be informed by input from LSE academics, readings, and other resources, and will culminate in presentations of each team’s analysis. Teams with excellent work will be encouraged to submit their projects to the next LSE Festival.


7 hours and 30 minutes of seminars in the MT. 7 hours and 30 minutes of seminars in the LT.

90-minute seminars take place in alternate weeks. Students will attend an LSE100 seminar in either weeks 2, 4, 6, 8 and 10 or weeks 3, 5, 7, 9 and 11 of Michaelmas term, and weeks 1, 3, 5, 7 and 9 or weeks 2, 4, 6, 8 and 10 of Lent term.

MT: Seminar – 5 x 90min

LT: Seminar – 5 x 90min

In addition to seminars students will engage with bespoke video lectures featuring academics from across the School (approx. 20 minutes per seminar).

Formative coursework

In seminars throughout both terms, students will practice:

  1. analysing quantitative and qualitative data
  2. using systems thinking and systems change tools
  3. constructing and communicating evidence-based academic arguments 

Teachers will provide feedback during seminars and in post-seminar communications to groups and individuals. 

During the Lent Term, students will also have the opportunity to try out the tools they can use for presenting their digital reports.

Indicative reading

The following readings are indicative of the texts students will be assigned for each stream. The total amount of reading assigned for each class will be 20-25 pages.

Oran R. Young (2017). ‘The age of complexity’ in Governing Complex Systems: Social Capital for the Anthropocene (MIT Press)

Betty Sue Flowers and Angela Wilkinson (2018). ‘Five principles of realistic hope’ in Realistic Hope: Facing Global Challenges (Amsterdam University Press)

Ruha Benjamin (2019). ‘Default Discrimination: Is the Glitch Systemic?’ in Race after Technology: Abolitionist Tools for the New Jim Code (Polity).

Frank Levy (2018). ‘Computers and populism: artificial intelligence, politics and jobs in the near term’ in Oxford Review of Economic Policy, Volume 34, Issue 3, Pages 393–417: 

Mark Coeckelbergh. ‘AI for climate: freedom, justice, and other ethical and political challenges’ in AI Ethics (2020):

Emily M. Bender, Timnit Gebru, Angelina McMillan-Major & Margaret Mitchell (forthcoming) ‘On the dangers of stochastic parrots: can language models be too big?’ available at:

Kate Crawford & Ryan Calo (2016) ‘There is a blind spot in AI research’ in Nature, 538: 311-3

Sarah Myers West, Meredith Whittaker & Kate Crawford (2019) Discriminating Systems: gender, race and power in AI (AI Now Institute)

Robert Sparrow & Mark Howard (2017) ‘When human beings are like drunk robots: driverless vehicles, ethics and the future of transport’ in Transportation Research, Part C: 80: 206-15


Coursework (50%, 1500 words) in the MT.
Project (50%) in the LT.

Summative assessment will include an individual written assessment in the Michaelmas Term (50%) and a collaborative research project in the Lent Term (50%).

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.

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: LSE

Total students 2020/21: Unavailable

Average class size 2020/21: Unavailable

Capped 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Leadership
  • Self-management
  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills