[what]

> So, if people's experience is with modern LLMs, they are being rational to accept that the answers as likely correct.

They are not.

But also wtf is a “modern” LLM? This is totally unhinged, every complaint about an LLM is always responded to with “you’re just using one from two months ago, it’s totally different now”. Repeat every two months for the same complaints.

[Filligree]

It’s not about the LLM being modern or not. 3.5 Flash is fairly new, but it’s also a flash model. It’s not designed to be knowledgeable.

People keep doing this. Pointing at the known limitations of cheap/fast LLMs and pretending they’re universal is not, in fact, valid reasoning.

[encomiast]

So then you need to ask: Why did they use a deliberately faulty LLM? They could have easily used a mainstream LLM from the past 18 months and it probably would have been less work to do so. But then they would not have that headline. The answers from the LLM would have likely made the participant's answers more accurate, not 3x less accurate. But then they would not have this juicy headline.

I understand that many of us are dealing with a lot of confident slop and support the point that we shouldn't uncritically accept LLM output. But the study is flawed and does not support this headline, or at least does not support it in the sense of how most of us would understand the term "AI advice".

[michaelmrose]

The actual study is more circumspect than this click bait and examines pretty deliberately how people respond to inaccurate data. It's neither a trick nor a design flaw. It's literally the thrust of the study.