AI-Assisted Cognition Endangers Human Development

LLMs carry persistent inductive biases rooted in their base model pre-training that post-training cannot fully override. When large populations use a small number of AI models for brainstorming, writing, and reasoning, those biases homogenize thought at a societal scale — a phenomenon the author calls 'cognitive inbreeding.' The piece introduces the 'Dynamic Dialectic Substrate' as a framework for understanding how human knowledge evolves through dialectical processes, and argues that AI-skew disrupts this evolution by anchoring collective cognition to outdated or biased patterns. Practical mitigation strategies include diversifying AI models, using web search instead of direct AI answers, and prioritizing human-to-human discussion.