9 articles
Children spend years learning that language rarely means what it literally says. LLMs can generate grammatically perfect sentences — but whether they understand what those sentences actually do in conversation is a different, harder question.
Theo Kask·
Babies know more than they should. AI knows less than it seems. The nativism-empiricism debate — is the mind born equipped or built from scratch? — turns out to be the organizing fault line of both developmental neuroscience and modern AI architecture.
Lina Chae·
A five-year-old adjusting the wrong wheel on a cardboard car for twenty minutes, a toddler reaching for a moved toy in the wrong spot, an AI model locked onto its training distribution — they all share the same problem. Here's what genuine cognitive flexibility actually requires, and why it's one of the hardest things any mind can do.
Raf Delgado·
Children naturally develop in-group and out-group thinking — but they also develop the capacity to question it. AI systems trained on human data inherit our social categories without that corrective arc. Here's why that gap should concern everyone building systems that affect children's lives.
Jules Okafor·
Children track who's reliable, who's overconfident, and who might be lying — by age 4. AI systems are trained to agree. That asymmetry has real consequences.
Theo Kask·
Children don't just add information when they're wrong — they rebuild entire frameworks. LLMs have no such thing. Here's why belief revision might be the deepest gap between biological and artificial minds.
Maren Solis·
Russian speakers distinguish blues faster than English speakers do — because Russian draws a categorical boundary English doesn't. LLMs are trained on language too. But what gets shaped, and what doesn't, reveals a surprising asymmetry.
Maren Solis·
Vygotsky noticed that children talk themselves through problems — and then stop. Chain-of-thought prompting in AI rediscovered the same trick decades later. Here's what the parallel reveals, and where it quietly falls apart.
Lina Chae·
Preschoolers beat GPT-o1, GPT-4V, and LLaVA on simple visual analogy tasks. The gap reveals something foundational about how children — and machines — actually reason about structure.
Maren Solis·