If the people running the platform are advertising a product that produces truths while delivering falsehoods and pathetically refusing to label their falsehoods as falsehoods, that's a lie.
There is a bit right on the chat box above every conversation that says, verbatim, "may occasionally generate incorrect information".
Determining truth is not in the wheelhouse of a language learning model and it is not defective for not doing so in the same way a tablesaw is not defective for not driving nails. Adjust your expectations accordingly.
The points of this thread are 1) this is a dramatic understatement; ChatGPT's output is not just occasionally incorrect, but usually incorrect in some dimension, and 2) in the absence of any fine-grained confidence value for individual statements, you must pessimistically assume that all statements are incorrect until proven otherwise, which dramatically reduces the utility of the tool compared to how its fanboys portray it as the second coming of Christ.
The first point is a bald-faced assertion with only anecdotal evidence, the second is a reduction to the absurd. It is absurd because if you uncritically accept the words of anything you read online, without, say, validating them with common sense, your own experience and knowledge, and so forth, the problem is with the reader, not the words.
You and the author of this article are making this false dichotomy where there is no middle ground between "usually incorrect" (which is hyperbolic nonsense and trivially falsified by five minutes of using it), and "always correct" (which even your straw "fanboys" have not done to my knowledge), and then using this dichotomy to set up another one to pretend that the only way to act on information read from a computer screen is either uncritical acceptance or presume that it's bullshit.
Neither of these models are accurate and neither of them have any relation to how people in the real world generally interact with information online or with ChatGPT.
Furthermore, your insistence on "labeling falsehoods" is not something we can do accurately anyways, let alone in the context of a language model which has no concept of truth or falsehood in the first place! You are asking for something completely unreasonable and I can't tell if you're doing it out of ignorance or bad faith.
Determining truth is not in the wheelhouse of a language learning model and it is not defective for not doing so in the same way a tablesaw is not defective for not driving nails. Adjust your expectations accordingly.