Comment by alex77456
It's up to everyone to decide what to use LLMs for. For high friction / low throughput (eg, online research using inferieor search tools) tasks, i find text models to be great. To ask about what you don't know, to skip the 'tedious part' (I don't feel like looking for answers, especially troubleshooting arcane technical issues among pages of forums or social media, makes me smarter in any way whatsoever, especially that the information usually needs to be verified and taken with a grain of salt).
StackExchange, the way it was meant to be initially, would be way more valuable over text models. But in reality people are imperfect and carry all sorts of cognitive biases and baggage, while a LLM won't close your question as 'too broad' right after it gets upvotes and user interaction.
On the other hand, I still find LLM writing on the subjects familiar to me, vastly inferior. Whenever I try to write a say, email with its help, I end up spending just as much time either editing the prompt to keep it on track, or rewriting it significantly after. I'd rather write it on my own with my own flow, than proofread/peer review a text model.
>To ask about what you don't know, to skip the 'tedious part' (I don't feel like looking for answers, especially troubleshooting arcane technical issues among pages of forums or social media, makes me smarter in any way whatsoever, especially that the information usually needs to be verified and taken with a grain of salt).
quoting the article:
Perhaps one of the more concerning findings is that participants in the LLM-to-Brain group repeatedly focused on a narrower set of ideas, as evidenced by n-gram analysis (see topics COURAGE, FORETHOUGHT, and PERFECT in Figures 82, 83, and 85, respectively) and supported by interview responses. This repetition suggests that many participants may not have engaged deeply with the topics or critically examined the material provided by the LLM.
When individuals fail to critically engage with a subject, their writing might become biased and superficial. This pattern reflects the accumulation of cognitive debt, a condition in which repeated reliance on external systems like LLMs replaces the effortful cognitive processes required for independent thinking.
Cognitive debt defers mental effort in the short term but results in long-term costs, such as diminished critical inquiry, increased vulnerability to manipulation, decreased creativity. When participants reproduce suggestions without evaluating their accuracy or relevance, they not only forfeit ownership of the ideas but also risk internalizing shallow or biased perspectives.