6 articles
Tania Lombrozo calls it "learning by thinking" — gaining genuinely new knowledge without new input. LLMs can now do something that looks identical. Here's why the difference between them might be the most important question in cognitive science right now.
Lina Chae·
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·
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·
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·
AI hallucinates because it doesn't know what it doesn't know. Children do. Here's why metacognition — the ability to track your own uncertainty — is the cognitive gap that actually matters.
Theo Kask·