5 ms·
Something which should happen: AI productions must be allowed to express doubt, levels of low confidence and the like. In a (hypothetical) 1960s SciFi film a k
by masswerk 4y ago
Something which should happen: AI productions must be allowed to express doubt, levels of low confidence and the like.
In a (hypothetical) 1960s SciFi film a knowledge system may have responded like this:
> assumption: subject deceased
> confidence score: 0.0000020017
> sources: none
In contrast to this, current systems are tailored to respond with high confidence:
> I'm sure X died in 2018.
> It has been written about in the New York Times, The Guardian, Le Monde.
> Here is a (hallucinated) link: https://www.theguardian.com/obituaries/x-obituary
(Compare various related stories.)
- dom96 4y agoI wonder if you can simply ask ChatGPT to provide a confidence score with each answer it gives.
- rednerrus 4y agoChatGPT (gpt3.5-turbo) is terrible at calculating anything. I've seen some preliminary evidence that GPT 4.0 is better at calculation so it may be possible for it.
- OscarCunningham 4y agoMy understanding was that ChatGPT simply puts a probability distribution over the next word, so I don't see why it's not as simple as just reporting how high those probabilities were for the answer it gave, relative to whatever would be typical.
- recursivecaveat 4y agoThose values are probably not intelligible as confidence scores. For example if it answers a question with "They died in 1902", since there are a lot of euphamisms and rephrasings of 'died' it will get a relatively low probability. 1902 probably gets a high score, but you can't really rely on that since it might just as well be hallucinating and pulled the year from some famous event in that person's life.
- yeldarb 4y agoThe GPT-4 paper & post[1] describe that the original model is pretty good at predicting the probability of its own correctness (well-calibrated confidence) but the post-processing degrades this property: > GPT-4 can also be confidently wrong in its predictions, not taking care to double-check work when it’s likely to make a mistake. Interestingly, the base pre-trained model is highly calibrated (its predicted confidence in an answer generally matches the probability of being correct). However, through our current post-training process, the calibration is reduced. > Left: Calibration plot of the pre-trained GPT-4 model on an MMLU subset. The model’s confidence in its prediction closely matches the probability of being correct. The dotted diagonal line represents perfect calibration. Right: Calibration plot of post-trained PPO GPT-4 model on the same MMLU subset. Our current process hurts the calibration quite a bit. [1] https://openai.com/research/gpt-4#:~:text=GPT%2D4%20can%20also%20be%20confidently%20wrong%20in%20its%20predictions https://openai.com/research/gpt-4#:~:text=GPT%2D4%20can%20al...
- EarthLaunch 4y agoI love this because I want more emphasis on this between humans. I hear there are languages with built in confidence expression.
- orange_fritter 4y agoYep, I'm not a language expert but I remember a South American language, maybe related to Quechua, where a sentences contain a syllable that indicates "I am repeating hearsay, I don't know if this is true". Pretty cool.
- masswerk 4y agoThis would be an unexpected outcome: AI productions motivating us to generally move towards prefix/postfix/infix decorations. "X studied at uhm-Oxford." -> I'm not sure, if it was really Oxford, but I have picked this up somewhere. But I'm sure, X did go to university. (As opposed to, "X uhm-studied at uhm-Oxford": I think, X has some higher education and it may have well been at Oxford.) :-)