- Neuroscience shows that learning is neither automatic nor uniform across life stages—it requires explicit instruction, practice, and conditions aligned with how the brain develops. In the age of AI, this becomes even more critical.
- Early and unguided use of technology can replace—rather than build—foundational skills, creating “cognitive debt” and widening learning gaps.
- The challenge is not limiting technology, but using it intentionally: protecting foundational learning in childhood and strengthening critical thinking and judgment in adolescence.
Reading is not natural. The brain has no innate circuits for reading. Unlike spoken language, which our brains are wired to acquire, reading requires explicit, systematic instruction and repetitive practice. Decades of neuroscience research (Maryanne Wolf and others) have shown that unlike speech, which humans evolved to produce and comprehend, reading is relatively recent. Our brains must repurpose and connect existing neural circuits, originally evolved for other functions like object recognition and language processing, to create new pathways for reading.
Stanislas Dehaene's research shows that learning to read requires the brain's visual system to recognize letters and letter patterns, connect them to sounds (phonemes), and link those to meaning, none of which happens automatically. This "neuronal recycling" process requires explicit teaching and thousands of hours of practice. Reading comprehension is a combination of decoding ability and language comprehension. Both must be explicitly taught, because neither develops naturally through mere exposure to print.
This isn't just an interesting neuroscience tidbit: it's the foundation for understanding why the way we educate children in the age of artificial intelligence and technology matters more than we might think. At the Inter-American Development Bank (IDB), we explored this broader challenge in a report on AI and education.
Thanks to advances in neuroscience over the past decades, we now have a much more precise understanding of how the learning process works at different stages of brain maturity. And here's what's crucial: we don't learn the same way at all stages of life.
- Childhood: The Critical Window. This is the period of high brain plasticity, the optimal moment for foundational learning, especially literacy. During these years, children's brains are extraordinarily receptive to forming the neural pathways necessary for reading. But this plasticity comes with requirements: clear, explicit instruction; daily practice and repetition; positive feedback that strengthens self-efficacy; and motivation through successful experiences.
- Adolescence: Reorganization and Identity. Adolescence brings neurocognitive reorganization and heightened socioemotional sensitivity. The teenage brain is literally restructuring itself, particularly in areas related to executive function, emotional regulation, and social cognition (prefrontal cortex). During this phase, effective learning requires metacognitive strategies (learning how to learn); complex texts and challenging problems; collaborative learning experiences; and a connection to identity and autonomy.
- Young Adults: Slower but Strategic. Brain plasticity continues into adulthood but at a slower pace. Adult learning relies more heavily on prior knowledge and experience; executive functions (planning, working memory, cognitive flexibility); contextualized instruction; clear connections to practical objectives.
The brain of our children and youth is developing under fundamentally different conditions than any previous generation. The factors affecting brain and socio-emotional development have changed dramatically with widespread exposure to technology, social media, and AI, and neuroscience is starting to reveal some of its consequences.
A recent study on infant screen exposure (children 0-2 years) reveals that higher infant screen time led to accelerated maturation of brain networks, and this acceleration is not good news. Certain brain networks develop too fast, before they've had time to develop the efficient connections needed for complex thinking. Think of it like a building where the scaffolding is removed before the structure is fully reinforced. This premature maturation can limit cognitive flexibility and resilience, leaving children less able to adapt later in life when they face novel challenges or need to learn new complex skills.
The impact doesn't stop in infancy. We know that technology exposure continues to affect the adolescent brain during a critical period when the prefrontal cortex (responsible for executive functions like planning, decision-making, and impulse control) is still developing. Excess exposure to digital devices delays the development of this part of the brain. In addition, social media, cyberbullying, social isolation, and lack of genuine social connectedness are affecting their mental health. The teenage brain, highly sensitive to peer feedback and social comparison, is being exposed to unprecedented levels of curated social comparison and dopamine-driven feedback loops at precisely the age when it's most vulnerable.
There is also an important connection between AI use and cognitive development. In a Massachusetts Institute of Technology study where college students were asked to develop essays with varying degrees of AI support, the findings were sobering: over-reliance on AI tools for cognitive tasks can hinder the development of deep cognitive skills and long-term learning. Early and uncritical use of these tools can result in what researchers call "cognitive debt": reduced neural engagement, impaired memory recall, and a weaker sense of ownership over one's own thinking and writing.
Understanding how the brain develops, and how technology is fundamentally altering that development, leads us to a clear but challenging conclusion: we need to be far more intentional about when, how, and how much we expose developing brains to digital tools. Technology needs to be used at the right developmental moments, in ways that build rather than bypass the neural architecture our children and youth need.
Navigating the technology paradox has two critical implications: that foundational skills are more essential, not less; and that the digital divide could become a learning divide. The tension between institutional adaptation and rapid individual appropriation will be central in the coming years. Students are adopting AI tools at speeds that far exceed regulators and schools' ability to integrate them.
This creates two risks:
- Risk 1: Skill replacement instead of skill enhancement. Students who use AI to bypass the cognitive work of writing, problem-solving, or research may never develop the foundational skills that make AI use productive. It's the difference between using a calculator to verify your mental math versus never learning to multiply.
- Risk 2: Inequality amplification. Students with strong foundational skills, critical thinking, and metacognitive abilities will use AI to accelerate their learning. Students without these foundations will use AI as a crutch that prevents development of those very capabilities.
Whether AI in education becomes a tool for reducing gaps or amplifying them depends on whether we get the foundational learning right. For that, education policy must:
- Protect the critical window of childhood. For infants and toddlers (0-2), minimize screen exposure. For young children (5-10), screen-based learning shouldn’t dominate. Technology-driven reading programs cannot replace systematic instruction. Young children need structured, guided learning experiences. Passive screen time or apps that promise "natural" learning through exposure won't build the systematic neural connections required for reading. The brain needs intentional, teacher-guided instruction during this critical window.
- Build digital wisdom in adolescence. Adolescents are highly susceptible to social feedback and comparison. The dopamine-driven reward systems of screens and social media limits the development of the prefrontal cortex and intersect with a brain that's particularly sensitive to peer validation and rejection. Teenagers need guidance and limits that we need to bring as adults. Technology can support collaborative learning, access to diverse information, and development of digital citizenship, if used intentionally.
This is the paradox we face: the same technologies that promise to revolutionize learning may actually impair the brain's development of the very capacities needed to use those technologies wisely.
A child who uses AI to write before learning to write, or to solve problems before learning to think through problems systematically, may never develop the neural architecture that makes independent, creative, critical thinking possible.
This isn't an argument against technology: it's an argument for being far more intentional about when, how, and how much we expose developing brains to these powerful tools. Because in the end, the most sophisticated AI in the world can't think for a brain that hasn't learned how to think in the first place.
Explore the IDB’s report on Artificial Intelligence and Education, that examines the role of artificial intelligence through the lens of what we already know from decades of digital education.