杏吧论坛

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.

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 critically assesses the current and emerging issues of big data and artificial intelligence from an integrated social-economic-political-technical perspective.

The concepts, methods and frameworks introduced aim to develop an in-depth understanding of the designing and organising logic for machine intelligence. Students will engage in research and practice on the promises and perils of data exploitation and algorithmic decision-making, and critically evaluate the implications of big data and machine intelligence for individuals, organisations and societies.

15 hours of lectures and 15 hours of seminars in the LT.

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

• Formative assessment 1 – Outline (1-page A4 document) of group presentation. The student groups will receive oral feedback and will have an opportunity for consultation in dedicated office hours.
• Formative assessment 2 – An initial draft (500 words) of the individual research essay.

The first formative assessment allows students to check whether they understand the design elements for AI strategy. The second formative assessment allows students to propose a research question, demonstrate knowledge of the background and related literature, and outline the key structure before they substantively develop the essay.

• 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.
• 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.
• Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at Work: The New Contested Terrain of Control. Academy of Management Annals, 14(1), 366-410.
• Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192-210.
• 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.

Project (30%, 2500 words) and essay (70%, 3000 words) in the LT.

Group Project (30%)

• A non-marked group presentation (but with feedback from the instructor and peers).
• A marked group project report with 2500 words on an AI strategic plan to address a preserving business or societal challenge.

Individual Research Essay (70%)

• 3000-word individual research essay on an approved topic in the area of AI management.