2 ms·

I think this is called Knoll's law of media accuracy [0] or wikipedia [1] - "Everything you read in the newspapers is absolutely true except for the rare story

I think this is called Knoll's law of media accuracy [0] or wikipedia [1] - "Everything you read in the newspapers is absolutely true except for the rare story of which you happen to have firsthand knowledge". Interestingly enough, I tried asking ChatGPT what it was before googling it, and it confidently told me I was asking about "Confirmation Bias." But then when I told it what I was talking about was indeed Knoll's Law, it got the definition of the law completely wrong! > I apologize for any confusion. You are correct, what you're describing is known as "Knoll's Law of Media Accuracy." It states that the accuracy of a story is inversely proportional to the number of people involved in its reporting, and the distance from the original source of information. In other words, the more people involved in reporting a story, the more likely it is to be inaccurate, and the further away the story is from the original source, the more likely it is to be inaccurate. This is one of the worst answers the bot has ever given me, and I've asked it a wide variety of prompts, from things I know to things I don't, including having it generate me fictional responses. [0] https://effectiviology.com/knolls-law/ https://effectiviology.com/knolls-law/ [1] https://en.wikipedia.org/wiki/Erwin_Knoll https://en.wikipedia.org/wiki/Erwin_Knoll

waterhouse 4y ago
Approximately the same phenomenon is also known as the Gell-Mann amnesia effect. It comes up on HN a lot, but for those who haven't encountered it before: > You open the newspaper to an article on some subject you know well. In Murray's case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward—reversing cause and effect. I call these the "wet streets cause rain" stories. Paper's full of them. > In any case, you read with exasperation or amusement the multiple errors in a story, and then turn the page to national or international affairs, and read as if the rest of the newspaper was somehow more accurate about Palestine than the baloney you just read. You turn the page, and forget what you know. https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect
omnicognate 4y ago
It did the same thing for me on Gell-Mann amnesia, which is the same concept. Read carefully, it's a particularly good example of "wrong but highly convincing": > Gell-Mann amnesia is a term coined by science writer Michael Crichton to describe the phenomenon where people tend to forget information that contradicts their preconceptions or beliefs. The term is named after physicist Murray Gell-Mann, who won the 1969 Nobel Prize in Physics for his work on the theory of elementary particles. > According to Crichton, Gell-Mann amnesia occurs when people encounter information that contradicts their beliefs, but rather than updating their beliefs to reflect the new information, they simply forget the information and continue to hold onto their preconceptions. This type of cognitive bias can be a significant barrier to learning and can lead to flawed decision-making.
dinkumthinkum 4y ago
Exactly. We should be realistic about AI and ChatGPT and LLMs. You have great example of how “confidently” produced atrocious results even with the oft-cited ad hoc solution of “follow up” it gave even more misinformation and you, the user, only know this because you happened to know the answer. Oddly enough, if you google the types of things you are talking about, you will largely get the correct answer as the first result. There is something to be said about being naive about the potential of LLMs models but I am astounded how hyped and eager everyone is to hand over the future of all knowledge work to them without even clear evidence that that would make sense.

waterhouse 4y ago

Approximately the same phenomenon is also known as the Gell-Mann amnesia effect. It comes up on HN a lot, but for those who haven't encountered it before: > You open the newspaper to an article on some subject you know well. In Murray's case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward—reversing cause and effect. I call these the "wet streets cause rain" stories. Paper's full of them. > In any case, you read with exasperation or amusement the multiple errors in a story, and then turn the page to national or international affairs, and read as if the rest of the newspaper was somehow more accurate about Palestine than the baloney you just read. You turn the page, and forget what you know. https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect

omnicognate 4y ago

It did the same thing for me on Gell-Mann amnesia, which is the same concept. Read carefully, it's a particularly good example of "wrong but highly convincing": > Gell-Mann amnesia is a term coined by science writer Michael Crichton to describe the phenomenon where people tend to forget information that contradicts their preconceptions or beliefs. The term is named after physicist Murray Gell-Mann, who won the 1969 Nobel Prize in Physics for his work on the theory of elementary particles. > According to Crichton, Gell-Mann amnesia occurs when people encounter information that contradicts their beliefs, but rather than updating their beliefs to reflect the new information, they simply forget the information and continue to hold onto their preconceptions. This type of cognitive bias can be a significant barrier to learning and can lead to flawed decision-making.

dinkumthinkum 4y ago

Exactly. We should be realistic about AI and ChatGPT and LLMs. You have great example of how “confidently” produced atrocious results even with the oft-cited ad hoc solution of “follow up” it gave even more misinformation and you, the user, only know this because you happened to know the answer. Oddly enough, if you google the types of things you are talking about, you will largely get the correct answer as the first result. There is something to be said about being naive about the potential of LLMs models but I am astounded how hyped and eager everyone is to hand over the future of all knowledge work to them without even clear evidence that that would make sense.