eriods of disruption often bring along both crises and the potential for renewal. From the Agricultural to the Industrial Revolution, education has evolved—not just in delivery, but in the role it plays in shaping our collective future. Today is another such moment.
Artificial intelligence is reshaping what it means to learn and know. At the same time, over 244 million children globally remain out of school due to conflict, displacement, and inequality. The digital sphere—once seen as a great equalizer—is fragmenting along political, cultural, and regulatory lines.
This fragmentation takes many forms. Social media platforms often function as ideological echo chambers, reinforcing beliefs rather than broadening perspectives. Access to generative AI is also uneven: while some regions foster open experimentation, others restrict or replace them with tightly controlled or state–developed alternatives or, increasingly, paywalls. These divisions produce starkly different experiences of digital literacy, creativity, and agency.
The digital divide is no longer just about access to devices or connectivity. It is about the ability to engage meaningfully with new technologies. Those who are not necessarily better ‘educated’ in the conventional sense but who possess curiosity, critical thinking, and adaptability are often better prepared. These qualities are not reliably nurtured in traditional systems. What is needed now is not simply exam performance, but the capacity to learn—and relearn—throughout life.
AI itself adds complexity. Unlike simple web use, each AI query draws significantly more power and depends on vast compute infrastructure. The environmental impact is real. Yet software innovations such as DeepSeek suggest a more sustainable future is within reach.
But energy is not the only concern—so is quality. The AI landscape is crowded with tools of varying reliability. Some, like ChatGPT and ERNIE Bot, handle nuanced requests with ease; others, like the emerging Manus, show promise but remain inconsistent. This is not just a technical issue—it is educational. Learners must be taught to assess and apply such tools critically.
Education must now adapt. Policymakers and institutions must prioritize long–term public value over short–term efficiency. That means addressing AI’s environmental cost, ensuring equitable access to high-quality tools, and embedding digital literacy into the heart of learning.
The question is not whether change is coming, but whether policymakers will meet it with the clarity and cooperation it demands.
a global affairs media network
Digital divide about meaningful engagement, not just access
Image via Adobe Stock.
May 14, 2025
The digital divide is no longer just about access to devices or connectivity, but about the ability to meaningfully engage with technology. Our education systems must evolve to encourage digital literacy, creativity, and agency, writes Leonor Diaz Alcantra.
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eriods of disruption often bring along both crises and the potential for renewal. From the Agricultural to the Industrial Revolution, education has evolved—not just in delivery, but in the role it plays in shaping our collective future. Today is another such moment.
Artificial intelligence is reshaping what it means to learn and know. At the same time, over 244 million children globally remain out of school due to conflict, displacement, and inequality. The digital sphere—once seen as a great equalizer—is fragmenting along political, cultural, and regulatory lines.
This fragmentation takes many forms. Social media platforms often function as ideological echo chambers, reinforcing beliefs rather than broadening perspectives. Access to generative AI is also uneven: while some regions foster open experimentation, others restrict or replace them with tightly controlled or state–developed alternatives or, increasingly, paywalls. These divisions produce starkly different experiences of digital literacy, creativity, and agency.
The digital divide is no longer just about access to devices or connectivity. It is about the ability to engage meaningfully with new technologies. Those who are not necessarily better ‘educated’ in the conventional sense but who possess curiosity, critical thinking, and adaptability are often better prepared. These qualities are not reliably nurtured in traditional systems. What is needed now is not simply exam performance, but the capacity to learn—and relearn—throughout life.
AI itself adds complexity. Unlike simple web use, each AI query draws significantly more power and depends on vast compute infrastructure. The environmental impact is real. Yet software innovations such as DeepSeek suggest a more sustainable future is within reach.
But energy is not the only concern—so is quality. The AI landscape is crowded with tools of varying reliability. Some, like ChatGPT and ERNIE Bot, handle nuanced requests with ease; others, like the emerging Manus, show promise but remain inconsistent. This is not just a technical issue—it is educational. Learners must be taught to assess and apply such tools critically.
Education must now adapt. Policymakers and institutions must prioritize long–term public value over short–term efficiency. That means addressing AI’s environmental cost, ensuring equitable access to high-quality tools, and embedding digital literacy into the heart of learning.
The question is not whether change is coming, but whether policymakers will meet it with the clarity and cooperation it demands.
