About

Fernando Reimers is the Ford Foundation Professor of Practice of International Education and director of the Global Education Innovation Initiative at Harvard University. He is an elected member of the U.S. National Academy of Education, the International Academy of Education, and the Council of Foreign Relations. His research and teaching focus on understanding how to educate children and youth so they can thrive in the 21st century, with particular expertise in global education, education policy, education reform, entrepreneurship, higher education leadership, inequality and education gaps, K-12 school leadership, moral, civic, and ethical education, organizational change, and teachers and teaching. Reimers has developed curriculum aligned with the United Nations Sustainable Development Goals, which is in use in many schools worldwide. During the COVID-19 pandemic, he led numerous comparative studies examining the educational consequences of the pandemic and identifying options to sustain educational opportunity and build back better. He serves as co-director of the International Education and Policy Management Pathway, an online master’s degree program at HGSE, and directs the Global Education Innovation Initiative, a cross-country research and practice collaborative. He has authored or edited 56 books and over 100 articles and chapters on topics related to education, including education during COVID-19, education reform, and global education initiatives. Reimers has served on multiple advisory boards and committees at Harvard and is involved in various organizations focused on education, peace, inclusion, and sustainability. He has been a faculty member at Harvard since 1998, with prior work experience at the Universidad Central de Venezuela, the Harvard Institute for International Development, and the World Bank.

Research topics

• Political science
• Sociology
• Humanities
• Public relations
• Economic growth

Selected publications

• Educación Superior, comunidad y aprendizaje-servicio: hacia una nueva centralidad de los socios comunitarios

  Dialnet (Universidad de la Rioja) · 2026-01-01

  article1st authorCorresponding
  Publisher

• AI and Teacher Development

  2025-12-10

  book-chapterOpen access1st authorCorresponding

  This chapter argues that teachers are central to turning curriculum into real learning, yet many places in the Global South face shortages, uneven preparation, heavy workloads, and weak ongoing support. AI may be able to help, if used well, in reducing the load of administrative tasks, helping plan lessons and create differentiated materials, offer scalable coaching and simulations, and supporting professional learning communities. But we warn that impact depends on strong foundations: teacher AI literacy (teaching about, with, and critically on AI), ethical safeguards and privacy, reliable infrastructure, and keeping teacher judgment in the loop. We stresses that effective tools must embed local pedagogy and subject expertise, not just generic technology. The chapter concludes that AI’s role is to augment, not automate, professional capacity. Realizing its potential requires systemic investment in teacher training, ethical frameworks, and the co-design of AI tools imbued with local pedagogical and content knowledge to empower teachers as critical, reflective practitioners.

  PublisherOA PDFDOI

• Artificial Intelligence and Education in the Global South

  2025-12-10 · 3 citations

  bookOpen access1st authorCorresponding

  This open access book examines the dynamic intersection of artificial intelligence and education in the Global South, where resource constraints and demographic trends create unique challenges and opportunities. Adopting a systems perspective, it explores how AI can transform teaching, curriculum, assessment, teacher professional development, school leadership and system governance while addressing AI literacy, improving the effectiveness of education and developing transferable skills. The book highlights the risks of exacerbating existing inequalities if technology is not carefully integrated and stresses the importance of human-centered, locally adapted solutions. The book examines whether AI is supporting innovation or the transformation of education systems and how it is addressing the principal most vexing challenges with respect to the areas examined. Each chapter draws on an analysis of the potential of AI, on evidence of its use and on evaluation on the implementation and effectiveness of applications. Each chapter concludes with main takeaways for policy and practice, key ethical issues and questions that merit more research.

  PublisherOA PDFDOI

• Education and Artificial Intelligence: A Systems Approach

  2025-12-10

  book-chapterOpen access1st authorCorresponding

  This opening chapter introduces a systems approach to exploring the intersection of artificial intelligence (AI) and education, focusing on how AI can be harnessed to meaningfully transform basic education systems, especially in the Global South. The authors define education systems as the complex ecology of institutions—schools, curricula, teachers, and governance mechanisms—that collectively shape learning opportunities for the majority of the world’s children. AI is conceptualized as technologies that can simulate human intelligence to undertake tasks such as communication, reasoning, and learning. Rather than assuming inherent benefits, the chapter adopts an open-minded yet cautious stance, emphasizing past disappointments with educational technology and the importance of distinguishing between marginal improvements and true systemic transformation. The authors highlight three central domains for examining AI’s contributions in education: fostering AI literacy, enhancing the effectiveness of educational delivery, and improving the relevance of school curricula to evolving societal and workforce demands. The chapter places a particular emphasis on the Global South, where resource constraints, demographic realities, and system fragility pose distinctive challenges—and where the bulk of the world’s youth reside. The argument is made that AI’s role cannot be understood in isolation; instead, a systems perspective is necessary, one that acknowledges the dynamic interplay between curriculum, teachers, assessments, and broader organizational, policy, and social contexts. A systems approach requires adapting AI solutions to local priorities and realities, ensuring that technology does not exacerbate existing inequalities or distract from foundational challenges—such as literacy and numeracy—while also seizing opportunities to leapfrog traditional constraints. By integrating complexity science concepts such as feedback loops and emergence, the authors illustrate how interventions in one part of the system can have far-reaching, sometimes unpredictable, consequences. The chapter further outlines the rationale for the book’s focus, exploring why educational institutions must contend with AI in light of labor market transformations, emerging needs for human and ethical skills and twenty-first century skills, and the potential for AI-enabled organizational improvements. It reviews current definitions and applications of AI in education, addressing both its potential and its limitations. The authors preview subsequent analysis on integrating AI into curricula to build AI literacy, leveraging AI to improve student learning and school functioning, and mitigating the risks of displacement and inequality. Throughout, the text calls for multi-level, evidence-based, ethically conscious policies as well as collaboration across government, industry, and educational stakeholders. Ultimately, the chapter sets the stage for a nuanced investigation into whether—and how—AI can deliver on its promise to transform education systems in meaningful, equitable, and sustainable ways.

  PublisherOA PDFDOI

• Conclusion: Charting the Future of AI and Education in the Global South—Promises, Realities, and the Path Forward

  2025-12-10

  book-chapterOpen access1st authorCorresponding

  This chapter synthesizes the key insights from the book’s exploration of artificial intelligence (AI) in education through a systems perspective, emphasizing the unique challenges and contexts of the Global South. The chapter cautions against uncritical techno-optimism and highlights that the promise of AI in education must be understood within the broader social and infrastructural conditions that shape educational ecosystems—including persistent inequalities, resource limitations, and varied governance capacities. Despite AI’s potential to personalize learning, automate assessments, and enhance teacher professional development, most applications thus far have been incremental rather than transformative, often deepening existing divides by favoring privileged, high-resource schools and not sufficiently reaching marginalized learners. Crucially, the chapter underscores that AI integration must be context-sensitive, inclusive, and ethically guided, with equity, transparency, and participation at its core. Many AI initiatives to date focus on automating existing processes or bolstering foundational literacies but fall short in fostering critical twenty-first-century skills or enabling curriculum and governance reforms that empower student and teacher agency. Moreover, the proliferation of digital data and the rise of commercial AI solutions raise ethical concerns around privacy, algorithmic bias, cultural relevance, and the public good. The chapter makes a case for collective action: policymakers should anchor AI strategies in broader educational purposes, prioritize capacity building, and safeguard equity; practitioners must approach AI critically and creatively; developers need to design for diversity and openness; and funders should promote ethical practices and South-South learning exchanges. Looking forward, the chapter highlights crucial research and practical questions around scaling inclusive AI-driven education, building broad-based AI literacy, and creating governance models that promote transparency and accountability. The concluding message is clear: technology alone cannot deliver meaningful change. Transformation demands systemic integration, continual ethical vigilance, stakeholder collaboration, and above all, a steadfast commitment to justice, dignity, and the holistic development of every learner. Only by placing human values at the forefront can the educational promise of AI in the Global South become a tool for genuine and sustainable transformation.

  PublisherOA PDFDOI

• AI and Education Governance

  2025-12-10 · 1 citations

  book-chapterOpen access1st authorCorresponding

  This chapter explains how AI can help those with education system level leadership responsibilities make better, faster choices. It starts by examining four big governance problems: unclear accountability, limited capacity, weak/slow data, and poor resource allocation. It then shows how AI can help—by letting people ask questions in everyday language (NLP), by analyzing and forecasting with large datasets (ML), and by speeding up feedback loops so action is more rapidly informed by evidence. Real-world examples include smarter budgeting and teacher placement, early-warning systems to prevent dropout, skills-needs planning, citizen feedback platforms, and automated service desks. The chapter also warns about risks—poor data, bias, privacy, equity gaps—and says strong foundations, clear rules, human oversight, and capacity-building are essential. It closes with practical takeaways for policymakers and developers, plus research questions on inclusion, accountability, capacity, and regulation.

  PublisherOA PDFDOI

• Students, Learning, Classrooms and Schools

  2025-12-10

  book-chapterOpen access1st authorCorresponding

  This chapter examines the centrality of learning and the pivotal role of students within contemporary education systems, with a particular focus on the Global South. It begins by reaffirming the fundamental goal of schools: to create opportunities for students to learn. The chapter highlights the need to understand learners’ diverse backgrounds, experiences, and the challenges they face in educational settings before considering how artificial intelligence (AI) can be leveraged to address these challenges. The discussion acknowledges the pervasive global learning crisis, noting that even minimal objectives-such as ensuring foundational skills in literacy and mathematics-remain unmet for many students. The chapter also argues for a broader conception of learning that extends beyond basic skills, emphasizing the importance of nurturing a wide array of student interests and capacities. However, international assessments indicate that students’ opportunities to develop these broader skills are similarly limited. The potential for AI to transform education is a central theme, with the chapter reviewing emerging evidence on how AI applications are beginning to address student needs and educational gaps. It explores both the benefits and limitations of these technologies, considering their potential for personalizing learning, supporting educators, and improving educational outcomes. Ethical considerations arising from the use of AI in schools are discussed, alongside key questions for future research aimed at ensuring equitable, effective, and trustworthy AI integration in educational contexts.

  PublisherOA PDFDOI

• Assessment and AI

  2025-12-10

  book-chapterOpen access1st authorCorresponding

  Educational assessment in the Global South is often defined by a paradox: national curricula aspire to cultivate 21st-century skills while legacy high-stakes examination systems incentivize rote memorization. This chapter argues that Artificial Intelligence may provide a pathway to resolve this tension by creating more opportunities for assessment to shift from a primarily summative, accountability-focused function to a formative, learning-oriented one. It examines both the transformative potential of AI to enable continuous, personalized feedback and assess complex skills and the current reality of its application. The analysis reveals that while AI could fundamentally reshape assessment, its current use often focuses on improving the efficiency of existing summative assessment models, such as through automated grading and proctoring. Transformative applications like adaptive testing and portfolio analysis are emerging but remain limited.

  PublisherOA PDFDOI

• Reformas educativas para expandir las oportunidades educativas en México. El poder de la política y los retos de su aplicación

  Revista Iberoamericana de Educación · 2025-01-01

  articleOpen access1st authorCorresponding

  Este artículo examina la dinámica de la aplicación de reformas a escala para ofrecer oportunidades educativas significativas a los alumnos desfavorecidos. Para contribuir eficazmente a la reducción de la desigualdad social y la exclusión, las políticas educativas necesitan una combinación de esfuerzos a escala de todo el sistema y específicos, aplicados a gran escala y sostenidos durante un tiempo lo suficientemente largo como para institucionalizarse. La capacidad de recuperación de esas políticas requiere una difícil convergencia de complementariedad entre los esfuerzos en todo el sistema y los esfuerzos específicos, la alineación entre las iniciativas federales y estatales y políticas de apoyo. Sin embargo, las políticas de aplicación de reformas en todo el sistema son más polémicas que las que implican esfuerzos específicos, ya que tales cambios son más perturbadores para los intereses creados en el statu quo, lo que hace que la sostenibilidad de tales esfuerzos sea precaria. Además, las políticas selectivas refuerzan la segregación de los alumnos en vías de diferente calidad.

  PublisherOA PDFDOI

• AI and School Organization and Management

  2025-12-10

  book-chapterOpen access1st authorCorresponding

  This chapter explores the potential of AI in addressing the challenges faced by school leadership and management in the Global South. The chapter highlights how AI can foster collaboration, improve data use, and support instructional leadership, thereby enhancing school effectiveness. It examines current AI applications in administrative automation, data-driven decision-making, and resource optimization, while also addressing ethical considerations around data privacy, algorithmic bias, and equitable access. The discussion emphasizes the need for AI to amplify human judgment and support participatory leadership, ultimately aiming to create more resilient, equitable, and human-centered school systems.

  PublisherOA PDFDOI

Frequent coauthors

• Connie K. Chung

  Unifor

  6 shared

• Noel F. McGinn

  4 shared

• Mariali Cárdenas

  3 shared

• María Elena Olmos Ortega

  3 shared

• Jari Lavonen

  University of Helsinki

  3 shared

• Uche Amaechi

  Harvard University

  3 shared

• Margaret Wang

  Columbia University

  3 shared

• Alysha Banerji

  Harvard University

  3 shared

Awards & honors

• Elected member of the U.S. National Academy of Education
• Elected member of the International Academy of Education
• Member of the Council of Foreign Relations