Comment by NetRunnerSu
Comment by NetRunnerSu 12 hours ago
The discussion here about "cognitive debt" is spot on, but I fear it might be too conservative. We're not just talking about forgetting a skill like a language or losing spatial memory from using GPS. We're talking about the systematic, irreversible atrophy of the neural pathways responsible for integrated reasoning.
The core danger isn't the "debt" itself, which implies it can be repaid through practice. The real danger is crossing a "cognitive tipping point". This is the threshold where so much executive function, synthesis, and argumentation has been offloaded to an external system (like an LLM) that the biological brain, in its ruthless efficiency, not only prunes the unused connections but loses the meta-ability to rebuild them.
Our biological wetware is a use-it-or-lose-it system without version control. When a complex cognitive function atrophies, the "source code" is corrupted. There's no git revert for a collapsed neural network that once supported deep, structured thought.
This HN thread is focused on essay writing. But scale this up. We are running a massive, uncontrolled experiment in outsourcing our collective cognition. The long-term outcome isn't just a society of people who are less skilled, but a society of people who are structurally incapable of the kind of thinking that built our world.
So the question isn't just "how do we avoid cognitive debt?". The real, terrifying question is: "What kind of container do we need for our minds when the biological one proves to be so ruthlessly, and perhaps irreversibly, self-optimizing for laziness?"
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.