This article is inspired by the ideas of cybernetics, Martin Heidegger, and Nassim Taleb. I’m looking at what I think is the largest danger of large language models (LLMs).

LLMs are extraordinarily proficient in the domain of language, and that proficiency has quietly created a philosophical problem that most technical discussions fail to notice. LLMs speak fluently, respond coherently, adapt style with ease, and generate text that fits seamlessly into human patterns of explanation and reflection.

The danger doesn’t lie in what they get wrong, but in how convincing they are when they appear to get things right. Fluency triggers attribution, and attribution tempts us to confuse linguistic competence with lived understanding. We humans are prone to jump to attributions. We seek purpose in anything and everything.

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