CCAI9019 Artificial Intelligence
The Political Economy of AI and Big Data

This course is under the thematic cluster(s) of:

  • Sustaining Cities, Cultures, and the Earth (SCCE)

SDG-08
SDG-10
SDG-11
Sustainable Development Goals

Timetable for Lectures

Course Description

This course introduces key ideas such as AI and Big Data’s impact on economic production, technological progress, data privacy, and AI ethics. The course will offer students an opportunity to reflect on how the rapid technological advancements in AI and Big Data are transforming society, individuals, and relationships. Students will utilize concepts from economics, political science, technology, and ethics to critically analyze the impact of AI and Big Data on society. It encourages students to engage with new political-economic and ethical questions raised by AI and Big Data, promoting interdisciplinary learning and global awareness. The course aligns with the United Nations Sustainable Development Goals of promoting decent work and economic growth and reducing inequalities by examining the impact of AI on the economy and job market.

Course Learning Outcomes

On completing the course, students will be able to:

  1. Understand, analyze and critically interpret key economic concepts and ideas through applying them to understanding the economics of AI and Big data.
  2. Apply and integrate knowledge from various disciplines including economics, political science, technology, and ethics to critically assess the transformative impacts of AI and Big Data on society, individuals, and relationships.
  3. Propose policies to mitigate potential risks and maximize benefits associated with AI and Big Data.
  4. Demonstrate the communication and collaboration skills on projects related to an issue important to AI & big data.

Offer Semester and Day of Teaching

Second semester (Wed)

Study Load

Activities Number of hours
Lectures 20
Tutorials 12
Seminars 2
Reading / Self-study 28
Assessment: Essay / Report writing 25
Assessment: Presentation (incl preparation) 25
Assessment: Peer evaluation 8
Total: 120

Assessment: 100% coursework

Assessment Tasks Weighting
Group presentation 20
Peer evaluation 20
Term paper 50
Lecture and tutorial participation 10

Required Reading

  • Acemoglu, D., & Restrepo, P. (2018). Artificial intelligence, automation, and work. In A. Agrawal, J. Gans & A. Goldfarb, The economics of artificial intelligence: An agenda (pp. 197-236). University of Chicago Press.
  • Acemoglu, D., & Restrepo, P. (2018). The race between man and machine: Implications of technology for growth, factor shares, and employment. American Economic Review, 108(6), 1488-1542.
  • Agrawal, A., Gans, J., & Goldfarb, A. (2022). Power and prediction: The disruptive economics of artificial intelligence. Harvard Business Press.
  • Carriere-Swallow, M. Y., & Haksar, M. V. (2019). The economics and implications of data: an integrated perspective. International Monetary Fund.
  • Korinek, A., & Stiglitz, J. E. (2021). Artificial intelligence, globalization, and strategies for economic development.
  • Millbrook, A. (2023). A short history of tractors in English. The Economist. From https://www.economist.com/christmas-specials/2023/12/20/a-short-history-of-tractors-in-english

Course Co-ordinator and Teacher(s)

Course Co-ordinator Contact
Dr V.W.H. Yuen
Faculty of Business and Economics (Economics)		 Tel: 3917 1287
Email: yuenvera@hku.hk
Teacher(s) Contact
Dr V.W.H. Yuen
Faculty of Business and Economics (Economics)		 Tel: 3917 1287
Email: yuenvera@hku.hk
Professor M.C.L. Chau
Faculty of Business and Economics (Innovation and Information Management)		 Tel: 3917 1014
Email: mchau@business.hku.hk