Shaping AI-Driven Education: Key Takeaways from GEC Academy’s Onsite Faculty Meeting in Shanghai

On February 20, GEC Academy successfully hosted an engaging onsite faculty meeting in Shanghai, marking a key event in the 2025 iHUB Winter Research Program. Centered on the theme Generative AI and Educational Regulation: From Local Practices to Global Standards, the seminar featured five distinguished professors: Paul Armstrong-Taylor, Professor of International Economics at Johns Hopkins University; Rajesh Bhargave, Associate Professor of Marketing at Imperial College; Sophia Koutsogiannaki, Assistant Professor of Anesthesia at Boston Children’s Hospital; Caroline Terquem, Professor of Physics at the University of Oxford; and Alberto Grünbaum, Professor of Mathematics at the University of California, Berkeley.

Led by Ms. Wendy Wang, Co-founder of GEC Academy and Secretary General of ASI Global, the seminar sparked in-depth discussions on how AI is reshaping academic integrity, teaching methodologies, and global regulatory frameworks. The event also attracted a cohort of academically driven and research-oriented iHUB students from various disciplines, providing a platform for interdisciplinary perspectives on the evolving role of generative AI in education.

As universities worldwide navigate the complexities of integrating AI, the seminar addressed several pressing issues faced by educators and universities today. The discussions focused on the following key topics.

1.       Standards for Acceptable Use of AI in Academic Work

The seminar began by exploring the regulatory landscape governing AI use in academic settings. While some universities strictly prohibit AI-generated content in undergraduate theses, the guest speakers advocate viewing AI as a tool, rather than a threat. They emphasized the importance of guiding students toward responsible AI usage, ensuring transparency, proper attribution, and academic rigor, rather than imposing outright bans. Additionally, the limitations of AI-driven plagiarism detection tools were discussed, as these systems often struggle to distinguish between AI-assisted and human-generated content, posing challenges to maintaining academic integrity.

2.       The Role of Generative AI in University Classrooms

The discussion then turned to AI’s integration into university teaching and assessment. In medical education, AI-driven simulations are being used to provide students with hands-on clinical training, while business schools employ AI for data-driven case study analysis. However, there were concerns about the potential over-reliance on AI-generated feedback, with professors stressing the need for AI literacy education, ensuring students critically engage with AI tools rather than passively accepting their outputs.

3.       Ethical Guidelines and Regulations for AI Use in Academic Settings

Universities are adopting varied approaches to AI ethics—some have dedicated AI ethics committees, while others rely on broader institutional policies. Data privacy emerged as a critical concern, particularly in fields like medicine and business, where AI processes sensitive information. Another challenge is fairness in AI access. Students with premium AI subscriptions may gain an unfair academic advantage, raising concerns about equity in learning environments. Some universities have explored detecting AI-generated work through indirect methods like IP tracking, but speakers questioned both the feasibility and ethical implications of such enforcement.

4.       Global Frameworks and Regulations for AI in Education

The final discussion examined AI’s impact on educational access and global regulatory frameworks. While AI-powered tools have the potential to enhance learning efficiency and expand access to quality education, disparities in availability could deepen existing inequalities. To address this, guest speakers emphasized the importance of proactive policy interventions to ensure AI serves as a force for inclusion rather than exclusion. Some proposed institutional support mechanisms, such as university-provided AI access to level the playing field for students, while others stressed the role of international regulatory bodies in setting ethical standards for AI in education.

Engaging the Next Generation: Student Q&A Session

Following the panel discussion, an open Q&A session allowed iHUB students to engage directly with the guest speakers. Their thought-provoking questions touched on topics such as whether universities should introduce AI literacy courses, how to verify AI-generated information, and what AI’s rise means for the future of higher education. In response, professors reinforced that while AI will inevitably reshape learning, the core value of education remains the ability to ask the right questions, a skill that no algorithm can replace.