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In my experience ChatGPT does reasoning extraordinarily well. The biggest key is that it can explain its thinking clearly. I may or may not agree what it's sayi

In my experience ChatGPT does reasoning extraordinarily well. The biggest key is that it can explain its thinking clearly. I may or may not agree what it's saying, or it could be outright wrong. But as long as I can see the "step by step" explanation of the thought process, I can make my own informed judgements. And there IS a thought process, that's clear and visible. The scope of topics and concepts it can work with is infinite. Of course there are a large number of edge cases and they are easy to find. But for the 80% of standard conversations, it seems to do just fine. I can have it build a list of pros and cons, rank options, make estimates. About any topic I can imagine, at any time. And all of that is backed by all of the data on the internet. Personally, I don't spend a lot of time asking it trick questions or philosophical gotchas. When I drill down on its reasoning, I find it to be very coherent. I've had a completely different experience than you.

kilgnad 4y ago
People are just latching on to the gotchas and the exceptions. Or they aren't really poking at this thing in-depth. ChatGPT is a different iteration of a language model. It does reasoning and it understands things.
anonymouskimmer 4y ago
Often when asked for their reasoning people will post-hoc a rationale. This post-hoc rationale is usually not the actual reasoning used to originally arrive at a point-of-view though. In one study I recall reading about but can't find at the moment people filled out multiple-choice surveys, then were asked to justify certain choices that the researcher told them they had chosen. They justified these choices even though they had originally chosen a different answer. Also: https://skepticink.com/tippling/2013/11/14/post-hoc-rationalisation-reasoning-our-intuition-and-changing-our-minds/ https://skepticink.com/tippling/2013/11/14/post-hoc-rational... I presume to some extent this is also the case with ChatGPT. I presume this because I don't think most people would understand (or have the time to fully read) the actual process the LLM is using to arrive at a particular output from a particular input. The end result looks kind of human. But is this the post-hoc human, the bullshitter human, or is this something else entirely (i.e. pattern matching - effectively mimicry, not of the human providing the input, but of the corpus)?
- zeknife 4y ago
  You can avoid post-hoc reasoning by making sure chatgpt works step by step to arrive at the answer instead of first presenting the answer and then the steps. This also makes correct answers more likely, especially if it involves math or some kind of iterative process.

kilgnad 4y ago

People are just latching on to the gotchas and the exceptions. Or they aren't really poking at this thing in-depth. ChatGPT is a different iteration of a language model. It does reasoning and it understands things.

anonymouskimmer 4y ago

Often when asked for their reasoning people will post-hoc a rationale. This post-hoc rationale is usually not the actual reasoning used to originally arrive at a point-of-view though. In one study I recall reading about but can't find at the moment people filled out multiple-choice surveys, then were asked to justify certain choices that the researcher told them they had chosen. They justified these choices even though they had originally chosen a different answer. Also: https://skepticink.com/tippling/2013/11/14/post-hoc-rationalisation-reasoning-our-intuition-and-changing-our-minds/ https://skepticink.com/tippling/2013/11/14/post-hoc-rational... I presume to some extent this is also the case with ChatGPT. I presume this because I don't think most people would understand (or have the time to fully read) the actual process the LLM is using to arrive at a particular output from a particular input. The end result looks kind of human. But is this the post-hoc human, the bullshitter human, or is this something else entirely (i.e. pattern matching - effectively mimicry, not of the human providing the input, but of the corpus)?

zeknife 4y ago
You can avoid post-hoc reasoning by making sure chatgpt works step by step to arrive at the answer instead of first presenting the answer and then the steps. This also makes correct answers more likely, especially if it involves math or some kind of iterative process.