时间/Time：2024年 12月10日 周二 北京时间 下午14:00-15:30

地点/Venue：

线上：北大国发院承泽园校区132教室

线下：ZOOM会议（会议号: 897 2560 1400  密码: 938759）

主讲人/Speaker：欧阳书淼 Shumiao Ouyang

主持人/Host：   胡佳胤 Jiayin Hu      

摘要/Abstract:

This study examines the risk preferences of Large Language Models (LLMs) and how aligning them with human ethical standards affects their economic decision-making. Analyzing 30 LLMs reveals a range of inherent risk profiles, from risk-averse to risk-seeking. We find that aligning LLMs with human values, focusing on harmlessness, helpfulness, and honesty, shifts them towards risk aversion. While some alignment improves investment forecast accuracy, excessive alignment leads to overly cautious predictions, potentially resulting in severe underinvestment. Our findings highlight the need for a nuanced approach that balances ethical alignment with the specific requirements of economic domains when using LLMs in finance.

主讲人介绍/Biography:

Shumiao Ouyang is an Associate Professor of Finance (without tenure) at Saïd Business School, University of Oxford and a Tutorial Fellow in Management at Wadham College.

Shumiao earned his Ph.D. in Economics from Princeton University, an M.S. in Finance from Peking University, and a dual B.S. in Biology and B.A. in Economics from Tsinghua University.

Since 2018, he has been collaborating with prominent BigTech firms such as Ant Group and Alibaba, leveraging his expertise to further understand the evolving landscape of finance and technology.

Shumiao's research is primarily focused on FinTech, Household Finance, Data Privacy, and Financial Intermediation, with a particular interest in the emerging field of BigTech Finance. As an economist, he strives to examine the complex relationships between finance and technology, shedding light on the far-reaching economic consequences of our rapidly digitizing world.