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“The LLMentalist Effect: how chat-based Large Language Models replicate the mechanisms of a psychic’s con” by @baldur
softwarecrisis.dev/letters/llm…

It is a long read but I feel does a good job of discussing how LLMs are more interested in truthiness than admitting when they don’t know.

This entry was edited (2 years ago)
in reply to Adrian Roselli

Here @eevee does a good job breaking down how users *thinking* an LLM response is good is *not* the same as the response being good (nor correct):
github.com/mdn/yari/issues/923…

(As before, please refrain from piling on in the comments.)

This entry was edited (2 years ago)
in reply to Adrian Roselli

Last month I argued why ‘AI’ will not fix #accessibility:
adrianroselli.com/2023/06/no-a…

As if to prove my point, #UserWay launched a broken LLM:
FuxMyCode.ai/

Yet the sorta-press shills nonsense like this PR from #AudioEye:
web.archive.org/web/2023070315…

Pay attention to who promotes LLMs as a solution. Usually it is a money play or laziness.

#a11y

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