Dr Zhi (Aaron) Cheng, MAR.4.25

This course is available on the CEMS Exchange, Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MBA Exchange, MSc in Human Resources and Organisations (Human Resource Management/CIPD), MSc in Human Resources and Organisations (International Employment Relations/CIPD), MSc in Human Resources and Organisations (Organisational Behaviour), MSc in Management (1 Year Programme) and MSc in Management of Information Systems and Digital Innovation. This course is available with permission as an outside option to students on other programmes where regulations permit.

This course may be capped/subject to controlled access. For further information about the course's availability, please see the MG Elective Course Selection Moodle page (https://moodle.lse.ac.uk/course/view.php?id=3840).

Priority will be given to students on the MSc in Management of Information Systems and Digital Innovation programme.

Why and how should we manage artificial intelligence (AI) and maintain humanity? The course approaches the current and emerging managerial and strategic matters around big data, AI and robotics, covering the development and implementation of AI technologies from organisational, technical, social, economic and political viewpoints. 

The concepts and frameworks in the course provide an in-depth understanding of the designing and organising logic for AI. Students will engage in research and practice on AI management, understand the promises and perils of data-driven and algorithmic decision-making, analyse the roles of human judgment, and critically assess the implications of big data and AI technologies for individuals, organisations and the society at large.

15 hours of lectures and 13 hours and 30 minutes of seminars in the WT.

A reading week will take place in Week 6. There will be no teaching during this week.

In its Ethics Code, LSE upholds a commitment to intellectual freedom. This means we will protect the freedom of expression of our students and staff and the right to engage in healthy debate in the classroom.

Students will be expected to produce 1 essay and 1 other piece of coursework in the WT.

The formative assessments (submitted to recieve oral feedback) include:

• An initial proposal (500 words) of the individual essay.
• An outline (1-page A4 document) of the team project proposal.

The first formative assessment allows students to propose a research question relevant to AI management, demonstrate knowledge of the background and related literature, and outline the key structure before substantively developing the essay. The second formative assessment allows students to apply their conceptual understanding of AI management and propose AI strategic plans to address real-world challenges.

• Acemoglu, D. (2021). Redesigning AI. Boston Review/Boston Critic Inc.
• Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Press.
• Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450.
• Brynjolfsson, E., & McAfee, A. (2017). Artificial Intelligence, for Real. Harvard Business Review.
• Crawford, K. (2021). The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press.
• Floridi, L. (2023). The Ethics of Artificial Intelligence: Principles, Challenges, and Opportunities. Oxford University Press.
• Hosanagar, K. (2020). A Human’s Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control (Illustrated edition). Penguin Books USA.
• Iansiti, M., & Lakhani, K. R. (2020). Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World (Illustrated edition). Harvard Business Review Press.
• Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192-210.
• Russell, S.J., & Norvig, P. (2022). Artificial Intelligence: A Modern Approach (Fourth Edition), Global Edition. Pearson Education.
• Provost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O’Reilly Media, Inc.
• Zerilli, J. (2021). A Citizen’s Guide to Artificial Intelligence. MIT Press.

Essay (60%, 2000 words) and project (40%, 3000 words) in the WT.

Students will present their team projects in the seminars and receive developmental feedback. After the final presentation, each student team will submit a 3000-word project report.