It Takes a Village to Raise GenAI: The Potential for GenAI to Address Longstanding Challenges in Global Education Systems

The 2024 ACUNS Annual Meeting, cohosted at the United Nations University and the University of Tokyo, convened from June 20-22 to address the theme “Global Governance and Sustainable Development: Revitalizing Research to Support Multilateral Solutions.” The meeting encompassed numerous sessions exploring different aspects of the theme, including a roundtable entitled “It Takes a Village to Raise GenAI: Exploring GenAI’s Impacts on Education and Research.”

Chaired by Jingbo Huang (UNU Macau), the session featured a panel of experts, including Francesco Foghetti (UNU Centre), Jonghwi Park (UNU-IAS), Mark Ray and Stephen Ta’Bois (Government of Cayman Islands), and Antonios Saravanos (New York University). This is Part 3 of the series.

The potential for Generative Artificial Intelligence (GenAI) to address longstanding challenges in global education systems, especially in marginalized communities, is promising. However, this technological advancement comes with its own set of complexities and considerations.  

The Global Education Challenge: Access and Learning Gaps

According to the recent data from UNESCO statistics, 260 million school-aged children are out of school worldwide. Reasons why they are not in school vary, ranging from poverty (often resulting in child labour), disabilities, wars and conflicts, family and social norms, geographical issues (e.g. long distance and safety to travel to schools), and others. If we were to accommodate the current volume of out-of-school children into the schools, a stark number of additional 44 million teachers are needed.

The challenges facing education go beyond access and participation issue. After the prolonged school closure due to the COVID-19 pandemic, children who cannot read and write a simple text at the age of 10, whether they are in school or not, has increased from 57% to 70% worldwide, according to a joint report (2022) by the World Bank, UNESCO and UNICEF. This troubling trend is particularly severe in low-income countries, where marginalized learners are hit hardest.

GenAI as a Tool for Personalized and Inclusive Learning

In this context, GenAI provides new opportunities for the marginalized learners who have limited access to quality education. For instance, AI-powered personalized tutors (e.g. Khanmigo) are already available while the ChatGPT has been explored and utilized by teachers and learners as supporting tools to enrich learning activities. Foundational learning, such as literacy and numeracy may benefit from leveraging the potential of GenAI to provide quality learning tailored to the diverse needs and different paces of learners.  

However, this promise is only viable if GenAI is developed to be universally inclusive. A stark digital divide exists: while almost 90% of school-aged children in high-income countries have access to the internet, less than 10% of those in low-income countries do (UNESCO, 2023). This disparity significantly contributed to the exacerbated learning losses during the pandemic, as online remote learning became an unattainable solution for many.

Language is another crucial barrier to inclusivity in GenAI. As GenAI is evolving itself through data available on the Internet, learners are left out if they do not speak the top 10 languages account for more than 80% of Internet content. In fact, a number of studies warn that the rate of language loss and extinction could triple within 40 years due to the dominance of a few languages on the Internet.  

Harnessing GenAI for Global Educational Policy

Despite these challenges, GenAI holds great potential to uphold the right to education for all. Since 2020, UNU-IAS and UNESCO have been studying the impact of climate change on human displacement and its effect on the right to education. We propose that GenAI could help build computational models to track the relationship between human mobility and climate change data. These models could offer data-driven projections to inform policies around education provision, including the planning of school locations, safe and resilient school infrastructure, effective teacher deployment, and the provision of emergency aid to ensure learning continuity amid the adverse impact of climate change and disasters.

Another new possibility lies in AI-generated synthetic data. Our research shows the extraordinary challenges in collecting data from displaced populations due to its temporary nature as well as the life-threatening situation that the informants face while the vitality of their voices cannot be understated in developing relevant policies for the rights of the populations. In this context, GenAI-generated synthetic data could help amplify what would otherwise be rare and difficult-to-collect information, supporting more robust and relevant policy decisions.

GenAI, with its immense potential, could transform education for millions, but only if we address the barriers of inclusivity, language, and access. As we continue to explore and expand its capabilities, we must ensure that its benefits reach all learners, especially the most marginalized. By harnessing GenAI effectively, we can create a more equitable and accessible future for education, closing the gaps and meeting the diverse needs of learners across the globe.