Seminar (Dept. of Finance)

Title: Fintech and the Future of Finance: “Code is Law” or “Code and Law”?

Speaker: Luyao Zhang, Assistant Professor, Duke Kunshan University

Time: 10:00-11:30, Apr.13, 2023(Thursday)

Venue: Room 402, Mingde Business Building

Language: Chinese & English

ABSTRACT:

The past one hundred years have witnessed marvelous advancements in artificial intelligence (AI). The advancement is integrating cyberspace, physical space, and social space into the cyber-physical-social systems (CPSS), which expands extraordinarily the territories of human civilizations. However, AI per se is not enough to establish trust in CPSS, which is the cornerstone of prosperity in every civilized society. Blockchain, also coined as decentralized AI, has the potential to empower AI to be more trustworthy by creating a decentralized trust of privacy, security, and auditability. However, the current blockchain technology is evidently not a panacea for doubts about human trust. Then, why “throw the baby out with the bathwater?” Existing mechanisms for cultivating human trust have created economic prosperity and human civilizations for thousands of years. How can we integrate blockchain technology into the existing governance, economics, and ethics to create an ideal society in the new era of CPSS? Specifically, how government regulations and corporate governance (the law) can contribute to economic prosperity together with the blockchain technology (the code)? In this talk, we initiate an open dialog of interdisciplinary studies for Fintech and the Future of Finance. In spirits of Philosopher Hegel’s dialectics, we start with an introduction to decentralized finance (DeFi) as the first application of blockchain to economics, the being (thesis); then, we evaluate obstacles to overcome before DeFi can benefit the general public, the nothing (anti-thesis); finally, we envision the synthetic solutions where Centralized Finance (CeFi) and DeFi co-exist to benefit the future of finance, the becoming (synthesis). Our interdisciplinary approach includes both qualitative and quantitative methods in philosophy, AI, economics, sociology, psychology, and computational science.