08/09/2026
【生成式 AI 如何解開因果關係的密碼？】
香港城市大學人文社會科學院（人院）於8月10日舉辦「人院進階方法學講座」（CAMS）主題演講，邀請美國哈佛大學政府學與統計學系講座教授今井耕介教授蒞臨分享前沿研究見解。
今井教授介紹一套名為「生成式AI賦能推論」（Generative AI–Powered Inference, GPI）的創新方法，探討如何運用生成式AI突破傳統研究的限制，從文字、圖像及影片等非結構化數據中辨識因果關係，將龐雜資訊轉化為嚴謹可靠的研究成果。
城大協理學務副校長（學術事務）溫子堅教授、人院院長何達基教授，以及人院副院長、CAMS召集人鄭煒教授亦有出席，了解相關理論與研究方法。
我們衷心感謝今井教授蒞臨城大，與師生分享寶貴洞見，為大家帶來一場精彩而富啟發性的講座。
想進一步了解講座內容，以及今井教授對生成式AI與因果推論的精闢分析？立即閱讀《明報》專題報道：https://bit.ly/3VgfPYx
【How Can Generative AI Unlock the Secrets of Causal Relationships?】
On 10 August, the College of Liberal Arts and Social Sciences (CLASS) at City University of Hong Kong (CityUHK) hosted Professor Kosuke IMAI, Edith and Benjamin Geisinger Professor in the Department of Government and the Department of Statistics at Harvard University, for the keynote speech of the CLASS Advanced Methods Seminars (CAMS).
Professor Imai introduced an innovative approach known as Generative AI-Powered Inference (GPI), which explores how generative AI can help overcome the limitations of conventional research methods. The approach enables researchers to identify causal relationships from unstructured data, such as text, images and videos, and to turn complex information into rigorous and reliable research findings.
Professor WAN Tze-Kin Alan, Associate Provost (Academic Affairs) at CityUHK; Professor AlfredTat-Kei HO, Dean of CLASS; and Professor Edmund CHENG, Associate Dean of CLASS and CAMS Convenor, also attended the seminar to learn more about the theory and methodology behind this emerging approach.
We extend our sincere thanks to Professor Imai for visiting CityUHK and sharing his valuable insights with our students and colleagues. The seminar offered an inspiring exploration of the potential of generative AI in causal inference.
To find out more about the seminar and Professor Imai’s insightful analysis of generative AI and causal inference, read the Ming Pao feature:
https://bit.ly/3VgfPYx (Chinese version only)
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