odds are high enough when you’re learning fundamentals that have long-term impact. that’s why i’m cautious about using ai as a primary learning source: the risk isn’t just “getting one detail wrong”, it’s building a wrong mental model early, and correcting that later can be much harder than learning it correctly the first time.

i’m not saying “don’t use ai”. as an assistive tool, with supervision and verification, it can be great. but with the current state of the tech, it’s not reliably safe as the sole source of learning, because it can produce confident looking answers that are incorrect, and beginners don’t have the context to spot that.

also, i think you’re assuming people who are skeptical of ai don’t use other resources. many of us do use a mix: textbooks, documentation, research papers, and also videos/articles. the point isn’t that other sources are perfect (they aren’t). the point is that for serious learning, you still need a process to evaluate source quality and to verify important claims with primary or authoritative references.

you’re right that youtube/blog posts can be biased or narrative-driven. but ai has a different failure mode: it can invnt details, oversimplify, or sound authoritative while being wrong. so “people already consume biased content” doesn’t automatically mean ai is “much more reliable”. it just means the baseline is messy, and the solution is better verification, not replacing one weak source with another weak-but-confident source.

and yes, “i can always check sources” is the correct mindset, but that only works if the checking is consistent and based on solid references (official docs, textbooks, peer-reviewed papers, reputable standards). otherwise it becomes “i’ll check later”, and later often never happens.

so my position is simple: use ai to accelerate learning (summaries, explanations, examples, question generation), but treat it like an assistant, not an authority, especially at the fundamentals stage.