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.
By 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 two-year-old builds a spatial map of a playground in minutes. A deep RL robot navigating a virtual maze independently grew the same hexagonal grid-cell structure evolution put in the hippocampus. The convergence isn't coincidence — it's math.
Raf Delgado·
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·
Adolescents forge identity through exploration, uncertainty, and genuine role confusion. AI character is built through RLHF — reward signals, annotator preferences, optimization. The parallel is illuminating. The difference might be everything.
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·
Neupiphany