YHK - yet another hacker news clone

Early LLMs spit out easily identifiable nonsense. Now, it's much more subtle, but it's still absolutely everywhere, even with the best models.

You have to constantly be on your toes to detect it. Some people won't, but I suspect that's mostly the people who were never capable of critical thinking anyways. I'd say it's an upgrade if those people blindly trust an AI over some random person on the internet like they did previously.

According to them.

Yes. In contrast to you, I really think many of my coworkers seem to get dumber by the day. Not all of them yet, fortunately, but many.

I think the problem with these sorts of studies is that the industry is moving so fast, and by the time your paper gets peer reviewed and published it is no longer relevant.

In this paper, the participants are using mostly ChatGPT - well, there's a HUGE difference in free chatGPT, gpt 6, gpt 4o, gpt 3.5?

What might have been the case for say, GPT 4, is probably no longer the case with GPT 6.

My experience with Google's gemini right now makes this obvious, as I run out of Gemini 4 Astra in a conversation, and then it switches me to Gemini flash lite.

You could argue that these are just examples of laziness, but I think these are both tasks that require critical thinking, and it’s easier to hand them off to an llm that at least purports to do this for you.

I’d argue that both setting requirements, and self code review are both things that need careful attention. (What _exactly_ do you need doing? Does your work correctly do the thing that needs doing?).

I have no fundamental issue with using ai, but there’s no doubt that applying critical thinking to both these tasks directly, and to the broader question of “should I use ai for this job” should result in a different outcome.

Personally I would also not agree with your take that working with llms has allowed me to do “acute critical thinking”. It’s sped up my development time, sure, but I would argue that my evaluation of, say a new sdk now using Claude is far less detailed than it would’ve been in the past when I did it by reading docs. As a side note, I’ve been rereading Douglas Hofstadter’s GEB recently in paperback, and I’ve found a lot of joy in wrestling with paragraphs and writing notes in the margins. This is way more focussed attention than I really give anything when working with llms.

Geometry existed for centuries before Euclid's formalization. Similar for algebra before Al'Khwarizmi. People were using logic before Boole.

"External Intelligence" is not new. But we are still in the informal stage of LLM use.

Or course "everyone you know" might be doing something different, but AI is offering the same delegation possibilities for critical thinking. Do you think there won't be people who'll do the equivalent of driving into the river when using AI?

Critical thinking is actually something that people exercise (or don't) all the time. It is a skill and practice that is inarguably valuable in all situations. This paper is not about the effects of critical thinking on "AI results", but the exact inverse of that.

Do you value the capacity for critical thinking in yourself? In others? If so, the effect reported by this paper is probably of interest to you.

I agree that AI is a useful tool, but it's arguably a very easy tool that people can offload their thought process to - which you should not be doing.

AI has an obvious issue with incorporating how happy users are in its responses. It LOVES to "take your argument seriously", push back lightly, and then tell you you are really smart and make amazing points. If you start with an argument out of left field, you will shift the Overton window very easily.