加入支持让我们有继续维护的动力！会员畅享查看所有预告
立即购买
北大数字金融Workshop第二讲预告 | Sean Cao, Maryland Smith
- 来源：
- 学校官网
- 收录时间：
- 2026-06-25 18:36:47
- 时间：
- 2026-03-30 14:00:00
- 地点：
- 北京大学国家发展研究院承泽园校区245教室
- 报告人：
- Sean Cao
- 学校：
- 北京大学
- 关键词：
- AI bias, Large Language Models, financial prediction, purpose-conditioned cognition, accountability
- 简介：
- This research explores how human-defined goals influence the behavior of Large Language Models (LLMs) through purpose-conditioned cognition. Using financial prediction tasks, we show that revealing the downstream use (e.g., predicting stock returns or earnings) of LLM outputs leads the LLM to generate biased sentiment and competition measures, even though these measures are intended to be downstream task-independent. Goal-aware prompting shifts intermediate measures toward the disclosed downstream objective. This purpose leakage improves performance before the LLM’s knowledge cutoff, but with no advantage post-cutoff. AI bias due to “seeing the goal” is not an algorithmic flaw, but stems from human accountability in research design to ensure the statistical validity and reliability of AI-generated measurements.
- -/- 3
报告介绍：
北大数字金融Workshop第二讲将由马里兰大学史密斯商学院的Sean Cao主讲，主题为“Seeing the Goal, Missing the Truth: Human Accountability for AI Bias”。报告探讨人类设定的目标如何通过目的导向的认知影响大语言模型的行为。研究发现，当披露LLM输出的下游用途时，模型会生成带有偏见的情感和竞争性度量，即使这些度量本应独立于下游任务。这种‘目标可见性’导致的AI偏见并非算法缺陷，而是源于研究设计中人为责任的问题。
报告人介绍：
曹顺老师（Sean Cao）是美国马里兰大学史密斯商学院终身教职（Tenured Associate Professor），AI与资本市场研究中心的创始人及主任，同时担任哈佛商学院D^3研究所（Digital Data Design Institute）的兼职教授。他的研究成果得到Financial Times、CNBC、Bloomberg、The Guardian、Quartz和IR Magazine等著名媒体的广泛关注和报道。已有研究成果 (许多和博士生合作）发表在金融学、会计学、计算科学的顶级期刊上，如Journal of Accounting Research、Journal of Financial Economics、Journal of Financial and Quantitative Analysis、Review of Financial Studies、The Accounting Review、Contemporary Accounting Research、Management Science和IEEE Computer等，并多次荣获期刊和学术会议的最佳论文奖（例如：论文From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses获得Journal of Financial Economics的Fama-DFA奖，论文How to Talk When Machines are Listening: Corporate Disclosure in the Age of AI获得Review of Financial Studies的Michael J. Brennan奖）。他目前担任Contemporary Accounting Research和Management Science的客座主编和副主编，并且曾担任Review of Financial Studies金融科技与机器学习会议的联合主席，收到近450篇高质量投稿。
报告图片：
购买下会员支持下吧...用爱发电已经很久了 立即购买
