AI in Global Education Policies: A Systematic Review of Equity in Access, Opportunities, and Outcomes

• In Event: Artificial intelligence and educational policy: impact and influence

Proposal

As artificial intelligence (AI) continues to influence educational landscapes globally, its role in shaping equity across diverse contexts has become a critical concern for policymakers, educators, and researchers. The adoption of AI technologies in education, along with related policies, remains in its formative stages and presents both opportunities and challenges, particularly regarding how it impacts various dimensions of equity. These technologies have the potential to democratize access to educational resources, provide personalized learning experiences, and address gaps in traditional education systems. However, there is also the risk that AI could exacerbate existing inequalities by deepening the digital divide, perpetuating biases, or favoring privileged groups over marginalized populations. As such, the implications of AI in education are far-reaching, affecting not only access to digital tools but also the broader distribution of educational opportunities and long-term outcomes. In this systematic literature review, we critically examine AI-related education policies across different regions to assess how equity is being conceptualized and addressed within these emerging frameworks.

In this study, equity is understood as a multi-dimensional concept that goes beyond mere access to technology. It encompasses fair access to AI tools, the equitable provision of learning opportunities for students from all backgrounds, and an evaluation of how AI-driven initiatives influence long-term educational outcomes. This broader view of equity includes addressing socio-economic disparities, geographic inequalities, and cultural contexts that may influence how students engage with AI-enhanced educational environments. By examining the current AI education policies, this review aims to determine whether such policies are successfully promoting inclusion and fairness, or if they unintentionally reinforce barriers to equitable education.

The factors we examine in this review include the digital divide, which refers to the unequal access to technology and digital infrastructure across regions and communities; algorithmic biases that could influence decision-making in AI systems, potentially disadvantaging certain groups; and the socio-economic conditions that affect how students interact with AI technologies. In addition, we consider the ways in which AI may perpetuate or disrupt existing power dynamics in education, particularly with respect to marginalized communities. The review also incorporates an analysis of how cultural diversity is acknowledged and integrated into AI educational frameworks, exploring whether AI systems account for the unique educational needs of students from different cultural backgrounds or if they reinforce a one-size-fits-all approach.

To provide a comprehensive analysis, this systematic review draws on a diverse range of sources, including peer-reviewed academic literature, governmental and institutional policy reports, and grey literature published over the past decade. The inclusion of grey literature ensures that we capture perspectives from non-traditional sources, such as reports from NGOs, think tanks, and educational consortia, which may offer unique insights into how AI policies are being implemented on the ground. Using a structured methodological approach, this research synthesizes findings from these sources to identify key trends, challenges, and gaps in the global AI education policy landscape.

One of the key objectives of this review is to highlight the implications of AI education policies for underserved and marginalized communities, including low-income populations, ethnic minorities, rural and remote learners, and students from under-resourced regions. These communities often face the greatest risk of being left behind in AI-driven educational reforms, particularly if policies do not adequately address issues such as access to reliable internet, digital literacy, and culturally relevant content. By focusing on the intersection of AI technologies with issues such as inclusivity, resource distribution, and culturally responsive teaching, this research provides a nuanced understanding of the role AI plays in shaping educational equity across diverse settings.

The findings from this review will provide a critical evaluation of how AI-driven educational innovations are being implemented across different countries and contexts. Specifically, the review will examine whether these innovations are leading to more equitable educational outcomes or, conversely, deepening existing inequalities. In doing so, the study will provide an analysis of both the potential benefits and risks associated with AI in education, shedding light on the policy gaps that need to be addressed to ensure that AI promotes greater fairness and inclusivity.

In addition to identifying current trends and challenges, this study will offer a set of policy recommendations aimed at fostering more inclusive and equitable AI-driven educational systems. These recommendations will focus on ensuring that all students—regardless of their socio-economic background, geographic location, or cultural identity—have equitable access to the benefits of AI technologies in education. Policymakers will be encouraged to develop policies that not only expand access to AI tools but also ensure that these tools are used in ways that promote fairness, cultural sensitivity, and long-term educational success for all learners.

Ultimately, this research will contribute to the growing discourse on the role of AI in global education systems, particularly with respect to equity and social justice. By bridging the gap between AI advancements and equitable educational practices, this review aims to influence the development of more inclusive AI-driven educational systems. The findings will serve as a valuable resource for policymakers, educators, and researchers seeking to understand and address the complex challenges and opportunities that AI presents for the future of education. In doing so, this review hopes to advance social justice in education and ensure that the benefits of AI technologies are shared by all, regardless of their background or circumstances.

Authors

• Youngbeen Ahn, OISE, University of Toronto

• Hodan Ismail, University of Toronto