嘉宾介绍：
陈伟博士是康涅狄格大学商学院运营与信息管理系的副教授，并担任康涅狄格大学数字前沿研究所（Digital Frontiers Initiative）的学术主任。该研究所专注于前沿技术的发展，致力于促进产学合作，特别是生成式AI的商业应用。
陈伟博士的研究领域包括平台与众包、金融科技、以及生成式AI设计与治理。他结合理论模型和数据分析，为这些领域的系统和市场设计提供严谨的证据。他的研究成果发表在多个顶级学术期刊上，包括《管理科学》（Management Science）、《信息系统研究》（Information Systems Research）、《管理信息系统季刊》（MIS Quarterly）和《生产与运营管理》（Production and Operations Management）。他在信息系统会议上多次获得最佳论文提名和奖项，并荣获INFORMS信息系统协会颁发的首届戈登·B·戴维斯青年学者奖（Gordon B. Davis Young Scholar Award）。
在2023年加入康涅狄格大学之前，陈伟博士是亚利桑那大学艾勒管理学院管理信息系统系的终身教员。他博士毕业于加州大学圣迭戈分校雷迪管理学院，主修创新、技术、与运营管理。
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讲座介绍：
AI is undergoing a paradigm shift with the rise of foundation models (e.g., GPT-4, Claude 3, Gemini, Llama 3, Stable Diffusion) trained on broad data using self-supervision at immense scale, which can then be adapted to myriad downstream tasks. This paper offers an economic theory of foundation model ecosystems that consist of upstream model developers and downstream model deployers. We model how fine-tuning games arise as downstream deployers competing in foundation model adoption and fine-tuning effort, and how model openness affects the fine-tuning games. Our theory provides insights into the economic implications and trade-offs for multiple stakeholders throughout the AI value chain (including developer, deployers, and consumers) and sheds light on how to harness the full potential of the foundation model value chain interactions and avoid pitfalls. An important implication of our findings is that the policymakers should explicitly consider potential unintended economic consequences of AI regulation on the ecosystem around open foundation models, in particular, the so-called ``openness trap" (i.e., a range of medium openness levels that should be avoided). Furthermore, we explore the welfare implications of prevalent market strategies employed by upstream developers, such as vertical integration and offering free trials. Our findings reveal that vertical integration proves effective when model openness is relatively limited. The developer's strategy of providing free trials can negatively affect the leading deployer within a moderate range of model openness, while benefiting all other stakeholders. Overall, our theory suggests that vertical integration and free trial are effective strategies for relatively closed foundation models, and more importantly, competition regulations on limiting such strategies at the developer level are most likely unnecessary.
