Disclaimer: This article is part of the Industry 4.0 Open Educational Resources (OER) Publication Initiatives jointly supported by Duke Learning Innovation Center and DKU Center for Teaching and Learning under the Carrying the Innovation Forward program. This article belongs to the OER Series No. 3 Computational Economics Spring 2022 collection. The Spring 2022 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. The co-author Yinhong Zhao was the Teaching and Research Assistant for Prof. Luyao Zhang in the course: COMPSCI/ECON 206 Computational Microeconomics at Duke Kunshan University Spring 2022, when he completed the joint article. The co-authors are forever indebted to Prof. Vincent Conitzer, who presented “Computer Science Meets Economics:” as a distinguished guest lecture for this course on Apr. 19, 2022.

Prof. Vincent Conitzer has contributed his leadership and insights to multiple disciplines in academia, industry practices, and beyond. He has been particularly active in the causes related to artificial intelligence (AI), computational economics, and innovative and interdisciplinary education.

Part I: Pioneer at the Intersection of Computer Science and Economics

The emergence of new computer networks has caused a profound expansion of the questions that computer science has had to address since these networks operate through the cooperation and competition of many participants, leading inevitably to underlying social and economic issues (Blume et al. 2015). Prof. Conitzer undertakes pivotal leadership positions in the intersection of computer science and economics. He served as general chair for the ACM Conference on Economics and Computation [4] in 2016 and the founding editor-in-chief of the ACM Transactions on Economics and Computation [5], a top conference and a top journal in economics and computation. Prof. Conitzer leads the reviews and editions on cutting-edge research works in advances in theory, empirics, and applications at the interface of economics and computation. His service contributes to the quality and impact of these academic publications, spreading innovative knowledge in the field.

Part II: Leadership in Innovative Interdisciplinary Education

At Duke, Prof. Conitzer enjoys an excellent reputation for his teaching and services. He won the distinctions of top 5% of all undergraduate instructors teaching in the Natural Science at Duke for the course of Computational Microeconomics in 2020 and the course of Artificial Intelligence in 2017. Conitzer (2012) shares the ambitious goal of the Computational Microeconoimcs course to bring together students from diverse backgrounds of Computer Science, Economics, and beyond, which is published in the Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence [3]. He was named the Bass Society Fellow [6] at Duke University for having achieved “true excellence in both research and teaching, and are good university citizens.” He excels in bringing research into the classroom and cultivating the next generation of computer scientists and economists to solve real-world problems, especially by computational methods. 

Part III: Leadership in Cooperative AI Research and Practices

Artificial Intelligence (AI) is intelligence demonstrated by machines (Rusell 2005). It is increasingly applied in various disciplines of human lives, including search engines, automated driving, computer vision, etc. However, AI’s lack of transparency and interpretability has aroused extensive concerns. Elon Musk claims that AI is humanity’s “biggest existential threat.” As an expert in the field, Prof. Conitzer has taken multiple leadership positions to lead research in AI ethics and cooperative AI. As Head of Technical AI Engagement at the Institute for Ethics in AI [1], Prof. Conitzer contributes his technical knowledge of AI to discussions with philosophers at Oxford. He also co-chairs the AAAI/ACM Conference on AI, Ethics, and Society (AIES) at Oxford University in 2022, editing the cutting-edge academic works on AI ethics. 

Prof. Conitzer’s involvement in philosophy and ethics lays a foundation for rapidly developing AI research. He is also elected as chair of the One Hundred Year Study on Artificial Intelligence (AI100) [2] at Stanford University, leading the study to anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live, and play. Recently, the Cooperative AI Foundation (CAIF) announced that its first major grant, of $500,000, will be to support the Foundations of Cooperative AI Lab (FOCAL) at Carnegie Mellon University (CMU), led by Prof. Vincent Conitzer. Cooperative AI is to upgrade AI from autonomy to cooperative intelligence, including four facets of understanding, communication, commitment, and norms & institutions.

After more than 15 wonderful years at Duke, Prof. Vincent Conitzer is moving to Carnegie Mellon University, where he will be founding FOCAL in the Computer Science Department. He will stay forever in the heart and eyes of the DKU-Duke Community. How can we ever appreciate his leadership more? We feel such a privilege to be together with Prof. Vincent Conitzer in taking over the culture of leadership that he had created here at Duke and pioneering new milestones in the same universe. To be continued.

References:

Blume, Lawrence, David Easley, Jon Kleinberg, Robert Kleinberg, and Éva Tardos. 2015. “Introduction to Computer Science and Economic Theory.” Journal of Economic Theory 156 (March): 1–13. https://doi.org/10.1016/j.jet.2014.11.002.

Conitzer, Vincent. 2012. “An Undergraduate Course in the Intersection of Computer Science and Economics.” AAAI’12, July, 2357–62. https://dl.acm.org/doi/abs/10.5555/2900929.2901064.

Dafoe, Allan, Yoram Bachrach, Gillian Hadfield, Eric Horvitz, Kate Larson, and Thore Graepel. 2021. “Cooperative AI: Machines Must Learn to Find Common Ground.” Nature 593 (7857): 33–36. https://doi.org/10.1038/d41586-021-01170-0.

Russell, Stuart J, and Peter Norvig. 2005. Artificial Intelligence : A Modern Approach. New Delhi: Prentice Hall.

Annotations:

[1]: Institute for Ethics in AI: The Institute for Ethics in AI brings together world-leading philosophers and other experts in the humanities with the technical developers and users of AI in academia, business, and government. The ethics and governance of AI is an exceptionally vibrant area of research at the University of Oxford and the Institute is an opportunity to take a bold leap forward from this platform.

[2]: One Hundred Year Study on Artificial Intelligence (AI100): The One Hundred Year Study of Artificial Intelligence (AI100) is a longitudinal study to study and anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live and play. It is hosted by Stanford University and managed by a standing committee of AI experts from institutions around the world, chaired by Peter Stone at the University of Texas at Austin.

[3]: AAAI/ACM Conference on AI, Ethics, and Society (AIES) in 2022: AIES is a conference convened each year by program co-chairs from Computer Science, Law and Policy, the Social Sciences, Ethics and Philosophy. The goal is to encourage talented scholars in these and related fields to submit their best work related to morality, law, policy, psychology, the other social sciences, and AI.

[4]: ACM Conference on Economics and Computation: Since 1999, the ACM Special Interest Group on Economics and Computation (SIGecom) has sponsored the leading scientific conference on advances in theory, empirics, and applications at the interface of economics and computation.

[5]: ACM Transactions on Economics and Computation: ACM Transactions on Economics and Computation (TEAC) focuses on the intersection of computer science and economics. Of interest to the journal is any topic relevant to economists and computer scientists.

[6]: Bass Fellow: In 1996, Fort Worth philanthropists Anne T. and Robert M. Bass gave Duke a generous gift to enhance the undergraduate experience through increased faculty-student interaction. The donation established the Bass Society of Fellows for Duke faculty members who have achieved “true excellence in research and teaching, and are good university citizens.” These faculty members receive named professorships and associate professorships created or partially funded by the Basses’ gift.