Francois Grey, a professor at the University of Geneva’s Information Science Institute and the Director of the Geneva Tsinghua Initiative, brought a unique perspective to the Online Education Dialogue 2023. To kick off his remarks, he shared an interesting observation about the increasing interest in AI among students. He mentioned that the number of students signing up for his class, “Crowdsourcing and AI,” had dramatically increased. Previously, when the course was titled “Citizen Science on the Web,” it attracted only 3 to 5 students. Now, with the inclusion of AI in the title, the course easily attracts over 20 students from various master programs in informatics. Grey’s observation on the increased interest in AI among students is a testament to the growing recognition of AI’s potential in various fields, and this, of course, was only one of the many changes brought about by AI that instructors and universities have to deal with. Then, his remarks focus around the following key points:

  1. AI as a Tool for Collaboration: Grey emphasized the potential of AI as a tool for collaboration in scientific research. He highlighted the example of Citizen Cyberlab, a platform that enables citizens to participate in scientific research through crowdsourcing. He stated, “This approach democratizes scientific research and allows for the harnessing of collective intelligence.”
  2. The Role of Universities in AI Education: Grey argued that universities have a crucial role to play in AI education. He suggested that universities should focus on teaching students how to work with AI, rather than merely teaching them about AI. This approach, he argued, would equip students with the skills they need to navigate the AI-driven future.
  3. The Importance of Open Science: Grey highlighted the importance of open science in the context of AI. He argued that open science, which involves making scientific research accessible to all, is crucial for ensuring the ethical and responsible use of AI. He also suggested that open science could help mitigate some of the risks associated with AI, such as the potential for bias and discrimination.
  4. The Potential of AI for Social Good: Grey also discussed the potential of AI for social good. He highlighted several projects that are using AI to address social challenges, such as the AI for Good Global Summit and the Open Seventeen Challenge. These initiatives, he argued, demonstrate the potential of AI to contribute to the achievement of the 2030 Agenda for Sustainable Development.
  5. The Need for a Global Approach to AI Governance: Grey concluded his remarks by emphasizing the need for a global approach to AI governance. He argued that the challenges posed by AI are global in nature and therefore require global solutions. He suggested that international cooperation and dialogue are crucial for developing effective strategies for AI governance.

In the panel discussion, Grey further elaborated on his views on AI in higher education. He emphasized the importance of data in AI and discussed the challenges posed by data privacy regulations, especially the need for a balanced approach to data privacy that respects individual rights while also enabling the benefits of AI. Grey also discussed the role of international organizations in addressing the challenges posed by AI. He mentioned the work of the United Nations (UN) and the International Telecommunication Union (ITU), highlighting the importance of international cooperation in developing effective strategies for AI governance.

These remarks from Grey reinforce his argument that AI has the potential to transform higher education, but that this transformation needs to be guided by principles of openness, collaboration, and ethical responsibility. His remarks underscore the importance of a thoughtful and strategic approach to AI education and governance, one that recognizes the potential of AI as a tool for social good, but also acknowledges the challenges and risks associated with its use.

Building on Grey’s emphasis on the importance of understanding the connection between the data needed for AI and AI itself, I found myself deeply engaged in the discussion. Grey asserted that the biggest challenge often lies in obtaining good data and understanding what good data is resonated with me. This perspective is crucial in the field of AI, where the focus is often skewed towards algorithms, while the importance of data is sometimes overlooked.

Grey’s exploration of citizen science, where individuals gather data out of interest, caught my attention. This approach to data collection, driven by curiosity rather than commercial motives, presents a unique perspective on leveraging collective intelligence for AI research. However, while data is crucial, its quality and ethical collection are equally important. The rise of AI has brought ethical considerations such as data privacy and consent. As we leverage AI in education, it’s imperative to navigate these considerations with care. Grey, located in Europe where regulations on data are stricter (e.g., Italy’s national privacy regulator ordered a ban of OpenAI’s ChatGPT over alleged violation of data privacy laws), would understand this more than other panelists.

Furthermore, Grey’s emphasis on the role of AI in facilitating collaboration presents an exciting avenue for exploration. Inasmuch as the integration of AI into our educational systems has shown promising advancements, there is an inherent need to strike a balance. The value of collaborative learning facilitated by AI should be harnessed without compromising the importance of critical thinking and individual learning experiences. This is where adaptive learning systems come into their own, offering the potential to provide personalized pathways for students, promoting autonomy in learning while still fostering a spirit of collaboration. AI can be used to stimulate individual critical thinking by presenting customized challenges and questions based on the student’s progress. As we continue to understand and leverage the capabilities of AI, it is essential to prioritize ethical considerations and strive to address the digital divide to ensure equitable access. This will mitigate potential inequalities and enhance the overall effectiveness of AI-driven collaborative learning, establishing a more inclusive and effective higher education system. Consequently, Grey’s views should guide us into a future where AI aids us in realizing the full spectrum of educational objectives, from collaboration to autonomy, all while maintaining rigorous academic standards.

In conclusion, Grey’s remarks provided valuable insights into the potential of AI in education, as well as the ethical considerations that must be taken into account. As we continue to explore the possibilities of AI in education, it is crucial that we approach its implementation with caution, always considering the ethical implications and striving to create a learning environment that is not only enhanced by technology, but also respectful of students’ privacy and conducive to collaboration.

As we reflect on Grey’s insights, I invite you to consider the following question: How can we maximize the potential benefits of AI in collaborative learning without compromising critical thinking and individual growth? Alternatively, how can we leverage AI, crowdsourcing, citizen-generated data, and collective intelligence to address societal challenges and promote social good? I look forward to hearing your thoughts and continuing this important discussion.

Note: “OED Host Reflect” is a series where the OED Host (Enoch Wong, Senior Advisor of Online Education and International Cooperation at Tsinghua University) summarizes messages delivered by speakers during the OED while attempting to make additional contributions to further discussion around the topic. Moreover, the views and opinions expressed in this program are those of the speakers and do not necessarily reflect the views or positions of any entities they represent. Last but not least, you are most welcome to watch the replay of OED at:

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