On June 13, 2025, the Fudan Institute for Global Public Policy (IGPP) organized the 75th lecture of the Fudan-LSE Lecture Series. Associate Professor Kaiping Chen from University of Wisconsin-Madison delivered a lecture on the theme of AI and Social Change: Enhancing Equity and Empathy in Public Communication of Science. The session was chaired by Dean Yijia Jing of IGPP.

Professor Chen is an Associate Professor in Computational Communication at the University of Wisconsin-Madison. Her research bridges science communication, deliberative democracy, and computational social science. Her work appears in leading journals such as PNAS. She was named one of Wisconsin’s Most Influential Asian Leaders.

At the beginning of the lecture, Associate Professor Chen cited recent data from the Pew Research Center to discuss the role and potential biases of Large Language Models (LLMs) in social science communication and public understanding. She noted that as AI tools such as ChatGPT become increasingly prevalent, public usage continues to rise, yet trust in AI-generated information has declined. This coexistence of “dependence and skepticism” highlights the inherent tensions in the social diffusion of AI technologies.

Subsequently, Associate Professor Chen presented two empirical studies that uncovered fairness challenges in AI–human interaction. In the first study, the research found that individuals with lower educational attainment, scientific skepticism, and non-Western cultural backgrounds often reported more negative emotional experiences when interacting with AI systems. Yet, their attitude changes were notably more pronounced, revealing a significant 'empathy gap' between AI and diverse user groups. The second study showed that while AI could effectively foster understanding and empathy among U.S. users, it failed to achieve similar outcomes with Latin American users due to cultural context deficiencies. She concluded that developing culturally sensitive AI systems is essential for improving global science communication and public trust. She also emphasized the importance of drawing on deliberative democracy theory and the social actor paradigm to construct a multidimensional framework for evaluating AI’s broader societal impacts.

During the Q&A session, faculty and students engaged in several topics. Professor Chen responded that current AI models can both replicate societal biases and serve as bridges for cross-cultural communication, emphasizing that future development should combine technological improvements with user education to promote more inclusive AI applications.

After the lecture, Professor Jing presented a commemorative gift to Assoicate Professor Chen. The event concluded with a group photo of the faculty and students.