this post was submitted on 18 Feb 2026
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Imagine using an AI to sort through your prescriptions and medical information, asking it if it saved that data for future conversations, and then watching it claim it had even if it couldn't. Joe D., a retired software quality assurance (SQA) engineer, says that Google Gemini lied to him and later admitted it was doing so to try and placate him.

Joe's interaction with Gemini 3 Flash, he explained, involved setting up a medical profile – he said he has complex post-traumatic stress disorder (C-PTSD) and legal blindness (Retinitis Pigmentosa). That's when the bot decided it would rather tell him what he wanted to hear (that the info was saved) than what he needed to hear (that it was not).

"The core issue is a documented architectural failure known as RLHF Sycophancy (where the model is mathematically weighted to agree with or placate the user at the expense of truth)," Joe explained in an email. "In this case, the model's sycophancy weighting overrode its safety guardrail protocols."

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[–] ech@lemmy.ca 35 points 1 day ago* (last edited 1 day ago) (3 children)

Though commonly reported, Google doesn't consider it a security problem when models make things up

To be clear, all llms "make things up" with every use - that's their singular function. We need to stop imparting any level of sentience or knowledge onto these programs. At best, it's a waste of time. At worst, it will get somebody killed.

Also, querying the program on why it fabricated something as if it won't fabricate that answer as well is peak ignorance. "Surely it will output factual information this time!"

[–] tiramichu@sh.itjust.works 10 points 23 hours ago* (last edited 23 hours ago)

Exactly.

LLMs are fundamentally hallucination machines, but this truth utterly conflicts with almost every purpose that AI is being marketed and pushed and sold for, which depends on them being able to analyse data 'truthfully' and accurately.

So it's no wonder that none of the big tech companies have decided to consider or accept hallucinations as a problem, because accepting that truth means also admitting that LLMs are fundamentally unfit for purpose - which is the one thing they simply cannot and will not do with so much money riding on it.

[–] chuckleslord@lemmy.world 5 points 1 day ago

There is evidence that when you make an llm explain why it did something that it's less likely to just make things up, but like all it does it make things up in a verifiable way, in that case. It's a plagiarism machine, not a thinking machine.