CNCC2024特邀报告讲者 | 美国加州大学伯克利分校教授Michael I. Jordan

Michael I. Jordan是法国国家信息与自动化研究所（Inria）研究员，加州大学伯克利分校名誉教授。他的研究兴趣横跨计算科学、统计学、认知科学、生物学和社会科学等领域。他是美国国家科学院院士、美国国家工程院院士、美国艺术与科学院院士以及英国皇家学会外籍院士。他是2022年世界顶尖科学家协会奖的首位获奖者。2018年，他担任了国际数学家大会的特邀讲者。Michael I. Jordan荣获美国数学学会的乌尔夫·格伦德尔奖、电气和电子工程师协会（IEEE）的约翰·冯·诺依曼奖章、国际人工智能联合会议（IJCAI）研究卓越奖、大卫·E·鲁梅尔哈特奖和美国计算机协会（ACM）/美国人工智能协会（AAAI）艾伦·纽厄尔奖。2016年，根据语义学者搜索引擎的排名，Michael I. Jordan在《科学》杂志的一篇文章中被命名为全球“最具影响力的计算机科学家”。

他受邀出席CNCC2024，将在10月24日上午带来特邀报告：An Alternative View on AI: Collaborative Learning, Statistical Incentives, and Social Welfare

报告题目：An Alternative View on AI:  Collaborative Learning, Statistical Incentives, and Social Welfare

摘要：Artificial intelligence (AI) has focused on a paradigm in which intelligence inheres in a single, autonomous agent.  Social issues are entirely secondary in this paradigm.  When AI systems are deployed in social contexts, however, the overall design of such systems is often naive---a centralized entity provides services to passive agents and reaps the rewards.  Such a paradigm need not be the dominant paradigm for information technology.  In a broader framing, agents are active, they are cooperative, and they wish to obtain value from their participation in learning-based systems.  Agents may supply data and other resources to the system, only if it is in their interest to do so.  Critically, intelligence inheres as much in the overall system as it does in individual agents, be they humans or computers.  This is a perspective that is familiar in the social sciences, and a key theme in my work is that of bringing economics into contact with foundational issues in computing and data sciences.  I'll emphasize some of the mathematical challenges that arise at this tripartite interface.