> In any other universe, we would be blaming the service rather than the user.

I think the key question is "How is this service being advertised?"

Perhaps the HN crowd gives it a lot of slack because they ignore the advertising. Or if you're like me, aren't even aware of how this is being marketed. We know the limitations, and adapt appropriately.

I guess where we differ is on whether the tool is broken or not (hence your use of the word "fix"). For me, it's not at all broken. What may be broken is the messaging. I don't want them to modify the tool to say "I don't know", because I'm fairly sure if they do that, it will break a number of people's use cases. If they want to put a post-processor that filters stuff before it gets to the user, and give me an option to disable the post-processor, then I'm fine with it. But don't handicap the tool in the name of accuracy!

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cj a day ago | parent [-]

The point you were making elsewhere in the thread was that "this is a bad use case for LLMs" ... "Don't use LLMs for dosing guidelines." ... "Using dosing guidelines is a bad example for demonstrating how reliable or unreliable LLMs are", etc etc etc.

You're blaming the user for having a bad experience as a result of not using the service "correctly".

I think the tool is absolutely broken, considering all of the people saying dosing guidelines is an "incorrect" use of LLM models. (While I agree it's not a good use, I strongly dislike how you're blaming the user for using it incorrectly - completely out of touch with reality).

We can't just cover up the shortfalls of LLMs by saying things like "Oh sorry, that's not a good use case, you're stupid if you use the tool for that purpose".

I really hope the HN crowd stops making excuses for why it's okay that LLMs don't perform well on tasks it's commonly asked to do.

> But don't handicap the tool in the name of accuracy!

If you're taking the position that it's the user's fault for asking LLMs a question it won't be good at answering, then you can't simultaneously advocate for not censoring the model. If it's the user's responsibility to know how to use ChatGPT "correctly", the tool (at a minimum) should help guide you away from using it in ways it's not intended for.

If LLMs were only used by smarter-than-average HN-crowd techies, I'd agree. But we're talking about a technology used by middle school kids. I don't think it's reasonable to expect middleschoolers to know what they should and shouldn't ask LLMs for help with.

	▲	BeetleB 11 hours ago \| parent [-]
		> You're blaming the user for having a bad experience as a result of not using the service "correctly". Definitely. Just as I used to blame people for misusing search engines in the pre-LLM era. Or for using Wikipedia to get non-factual information. Or for using a library as a place to meet with friends and have lunch (in a non-private area). If you're going to try to use a knife as a hammer, yes, I will fault you. I do expect that if someone plans to use a tool, they do own the responsibility of learning how to use it. > If you're taking the position that it's the user's fault for asking LLMs a question it won't be good at answering, then you can't simultaneously advocate for not censoring the model. If it's the user's responsibility to know how to use ChatGPT "correctly", the tool (at a minimum) should help guide you away from using it in ways it's not intended for. Documentation, manuals, training videos, etc. Yes, I am perhaps a greybeard. And while I do like that many modern parts of computing are designed to be easy to use without any training, I am against stating that this is a minimum standard that all tools have to meet. Software is the only part of engineering where "self-explanatory" seems to be common. You don't buy a board game hoping it will just be self-evident how to play. You don't buy a pressure cooker hoping it will just be safe to use without learning how to use it. So yes, I do expect users should learn how to use the tools they use.