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<p>The integration of artificial intelligence (AI) into education marks a critical transition, not only through the adoption of new tools but by challenging the epistemological foundations of teaching and learning. AI reshapes how knowledge is produced, mediated, and evaluated, raising critical questions around equity, agency, and accountability in increasingly data-driven environments. Its emergence compels educators and policymakers to reconsider long-standing assumptions about what counts as learning, how it is measured, and who benefits from technological change. This paper examines how AI is transforming key structures and practices across the broader education landscape, with a particular focus on school education as a strategic and emblematic site for early intervention and pedagogical innovation. While many of the transformations discussed in the paper are relevant across educational levels, schools represent a crucial point where students first experience the cognitive, social, and ethical dimensions of AI, and where systems can act early to promote inclusion, reflection, and readiness. Drawing on major European frameworks, this paper analyzes how AI is reshaping four interdependent pillars of education: curricular content, teaching paradigms, assessment systems, and governance structures. International case-based insights illustrate diverse implementation strategies while also revealing persistent challenges, such as digital inequalities, gaps in teacher preparation, and limited availability of robust mechanisms for algorithmic accountability. Adopting a conceptual, policy-informed approach, this paper synthesizes scholarly literature, European regulatory frameworks, and implementation evidence to propose a systemic view of educational transformation. Rather than framing AI as a mere driver of automation, the paper argues for a transformative approach rooted in equity, human agency, and democratic values. In practical terms, it distills policy-relevant guidance on ethics-by-design, human-in-the-loop safeguards, and capacity building for teachers and school leaders to enable responsible, system-level implementation. The conclusions highlight that, when supported by coherent policy infrastructure and teacher empowerment, school education systems can align technological innovation with inclusive, ethical, and future-oriented learning, ensuring that AI contributes to social justice rather than reinforcing existing inequalities.</p>

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Rethinking Schooling in the Age of AI: Equity, Ethics, and the Four Pillars of Transformation

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Veronica Mobilio,
  • Giulia Guglielmini

摘要

The integration of artificial intelligence (AI) into education marks a critical transition, not only through the adoption of new tools but by challenging the epistemological foundations of teaching and learning. AI reshapes how knowledge is produced, mediated, and evaluated, raising critical questions around equity, agency, and accountability in increasingly data-driven environments. Its emergence compels educators and policymakers to reconsider long-standing assumptions about what counts as learning, how it is measured, and who benefits from technological change. This paper examines how AI is transforming key structures and practices across the broader education landscape, with a particular focus on school education as a strategic and emblematic site for early intervention and pedagogical innovation. While many of the transformations discussed in the paper are relevant across educational levels, schools represent a crucial point where students first experience the cognitive, social, and ethical dimensions of AI, and where systems can act early to promote inclusion, reflection, and readiness. Drawing on major European frameworks, this paper analyzes how AI is reshaping four interdependent pillars of education: curricular content, teaching paradigms, assessment systems, and governance structures. International case-based insights illustrate diverse implementation strategies while also revealing persistent challenges, such as digital inequalities, gaps in teacher preparation, and limited availability of robust mechanisms for algorithmic accountability. Adopting a conceptual, policy-informed approach, this paper synthesizes scholarly literature, European regulatory frameworks, and implementation evidence to propose a systemic view of educational transformation. Rather than framing AI as a mere driver of automation, the paper argues for a transformative approach rooted in equity, human agency, and democratic values. In practical terms, it distills policy-relevant guidance on ethics-by-design, human-in-the-loop safeguards, and capacity building for teachers and school leaders to enable responsible, system-level implementation. The conclusions highlight that, when supported by coherent policy infrastructure and teacher empowerment, school education systems can align technological innovation with inclusive, ethical, and future-oriented learning, ensuring that AI contributes to social justice rather than reinforcing existing inequalities.