I dare say that if you ask a human “Why should I not stick my hand in a fire?” their process for answering the question is going to be very different from an LLM.
ETA: Also, working in software development, I’ll tell ya… Most of the time, when people ask me a question, it’s the wrong question and they just didn’t know to ask a different question instead. LLMs don’t handle that scenario.
I’ve tried asking ChatGPT “How do I get the relative path from a string that might be either an absolute URI or a relative path?” It spat out 15 lines of code for doing it manually. I ain’t gonna throw that maintenance burden into my codebase. So I clarified: “I want a library that does this in a single line.” And it found one.
An LLM can be a handy tool, but you have to remember that it’s also a plagiarizing, shameless bullshitter of a monkey paw.
“Most of the time, when people ask me a question, it’s the wrong question and they just didn’t know to ask a different question instead.”
“I’ve tried asking ChatGPT “How do I get the relative path from a string that might be either an absolute URI or a relative path?” It spat out 15 lines of code for doing it manually. I ain’t gonna throw that maintenance burden into my codebase. So I clarified: “I want a library that does this in a single line.” And it found one.”
You see the irony right? I genuinely can’t fathom your intent when telling this story, but it is an absolutely stellar example.
You can’t give a good answer when people don’t ask the right questions. ChatGPT answers are only as good as the prompts. As far as being a “plagiarizing, shameless bullshitter of a monkey paw” I still don’t think it’s all that different from the results you get from people. If you ask a coworker the same question you asked chatGPT, you’re probably going to get a line copied from a Google search that may or may not work.
You see the irony right? I genuinely can’t fathom your intent when telling this story, but it is an absolutely stellar example.
Yes, I did mean for it to be an example.
And yes, I do think that correctly framing a question is crucial whether you’re dealing with a person or an LLM. But I was elaborating on whether a person’s process of answering a question is fundamentally similar to an LLM’s process. And this is one way that it’s noticeably different. A person will size up who is asking, what they’re asking, and how they’re asking it… and consider whether they should actually answer the exact question that was asked or suggest a better question instead.
You can certainly work around it, as the asker, but it does require deliberate disambiguation. I think programmers are used to doing that, so it may feel like not that big of a deal, but if you start paying attention to how often people are tossing around half-formed questions or statements and just expecting the recipient to fill in the gaps… It’s basically 100% of the time.
We’re fundamentally social creatures first, and intelligent creatures second. (Or third, or not at all, depending.) We think better as groups. If you give 10 individuals a set of difficult questions, they’ll bomb almost all of them. If you give the questions to a group of 10, they’ll get almost all of them right. (There’s several You Are Not So Smart episodes on this, but the main one is 111.)
Asking a question to an LLM is just completely different from asking a person. We’re not optimized for correctly filling out scantron sheets as individuals, we’re optimized for brainstorming ideas and pruning them as a group.
I dare say that if you ask a human “Why should I not stick my hand in a fire?” their process for answering the question is going to be very different from an LLM.
ETA: Also, working in software development, I’ll tell ya… Most of the time, when people ask me a question, it’s the wrong question and they just didn’t know to ask a different question instead. LLMs don’t handle that scenario.
I’ve tried asking ChatGPT “How do I get the relative path from a string that might be either an absolute URI or a relative path?” It spat out 15 lines of code for doing it manually. I ain’t gonna throw that maintenance burden into my codebase. So I clarified: “I want a library that does this in a single line.” And it found one.
An LLM can be a handy tool, but you have to remember that it’s also a plagiarizing, shameless bullshitter of a monkey paw.
“Most of the time, when people ask me a question, it’s the wrong question and they just didn’t know to ask a different question instead.”
“I’ve tried asking ChatGPT “How do I get the relative path from a string that might be either an absolute URI or a relative path?” It spat out 15 lines of code for doing it manually. I ain’t gonna throw that maintenance burden into my codebase. So I clarified: “I want a library that does this in a single line.” And it found one.”
You see the irony right? I genuinely can’t fathom your intent when telling this story, but it is an absolutely stellar example.
You can’t give a good answer when people don’t ask the right questions. ChatGPT answers are only as good as the prompts. As far as being a “plagiarizing, shameless bullshitter of a monkey paw” I still don’t think it’s all that different from the results you get from people. If you ask a coworker the same question you asked chatGPT, you’re probably going to get a line copied from a Google search that may or may not work.
Yes, I did mean for it to be an example.
And yes, I do think that correctly framing a question is crucial whether you’re dealing with a person or an LLM. But I was elaborating on whether a person’s process of answering a question is fundamentally similar to an LLM’s process. And this is one way that it’s noticeably different. A person will size up who is asking, what they’re asking, and how they’re asking it… and consider whether they should actually answer the exact question that was asked or suggest a better question instead.
You can certainly work around it, as the asker, but it does require deliberate disambiguation. I think programmers are used to doing that, so it may feel like not that big of a deal, but if you start paying attention to how often people are tossing around half-formed questions or statements and just expecting the recipient to fill in the gaps… It’s basically 100% of the time.
We’re fundamentally social creatures first, and intelligent creatures second. (Or third, or not at all, depending.) We think better as groups. If you give 10 individuals a set of difficult questions, they’ll bomb almost all of them. If you give the questions to a group of 10, they’ll get almost all of them right. (There’s several You Are Not So Smart episodes on this, but the main one is 111.)
Asking a question to an LLM is just completely different from asking a person. We’re not optimized for correctly filling out scantron sheets as individuals, we’re optimized for brainstorming ideas and pruning them as a group.
If you fed that information into one I bet you would get different answers.
That is information that isn’t available to it generally.