🎉 About! 🎉

This course explores the interdisciplinary conversation between economics and artificial intelligence (AI). In experiential education, this course shows how the two disciplines advance each other by an explainable AI approach: economics makes AI more explainable by clarifying causal relationships, and AI empowers economic applications by increasing efficiency. Advanced research in Microeconomics, Macroeconomics, and Behavioral and Experimental Economics is covered with both a general literature review and a case study. The course concludes with a research proposal where students propose an executive plan for academic research and automated products collaboratively in a team of economists, data scientists, and data engineers. Instructor: Dr. Luyao Zhang, Assistant Professor of Economics at Social Science Division and Senior Research Scientist at Data Science Research Center, Duke Kunshan University.

Mission

Part of Industry 4.0 Open Educational Resource Publication Initiatives: Series No.2: Intelligent Economics: An Explainable AI Approach: https://ie.pubpub.org/

Series No. 1: Innovate on the Internet Computer: https://ic.pubpub.org/

Series No. 3: Computational Economics: https://ce.pubpub.org/

Series No.4: Summer Research Scholar by Sunshine: https://srs.pubpub.org/.

Series No. 5: Rising Star by Sunshine: https://rs.pubpub.org/

Diversity and Inclusion

Created collaboratively of the community, by the community, and for the community

Connect

A call for collaborations among university faculties, students, staff, and beyond

Acknowledgments:

• This project is partly supported by Duke Learning Innovation Center and DKU Center for Teaching and Learning under the Carrying the Innovation Forward program

• The Autumn 2021 collection is partly supported by the Social Science Divisional Chair’s Discretionary Fund to encourage faculty engagement in undergraduate research and enhance student-faculty scholarly interactions outside of the classroom. The division chair is Prof. Keping Wu, Associate Professor of Anthropology at Duke Kunshan University. And the supported students include Administrative Teaching Assistants, Xinyu Tian and Tianyu Wu, and Teaching Assistants, Jingwei Li, Chenyu Wang, and Zesen Zhuang. We thank Jiaxin Wu and the team at DKU Center for Teaching and Learning for their assistants in implementing Gradescope for class assignments. 

  • Xinyu Tian, Data Science, Class of 2023, Duke Kunshan University

  • Tianyu Wu, Applied Mathematics and Computational Science, Class of 2023, Duke Kunshan University

  • Jingwei Li, Data Science, Class of 2023, Duke Kunshan University

  • Chenyu Wang, Applied Mathematics and Computational Science, Class of 2023, Duke Kunshan University

  • Zesen Zhuang, Data Science, Class of 2023, Duke Kunshan University

• We thank Prof. William Parsons and Prof. Liguo Zhang for their guidance in proposing the initial syllabus of “Econ 211 Intelligent Economics: An Explanable AI approach” for the undergraduate curriculum at Duke Kunshan University and the further development of the course.

  • Prof. William Parsons, Associate Dean of Undergraduate Curricular Affairs, Duke Kunshan University

  • Prof. Liguo Zhang, Academic Dean, Duke Kunshan University