4 ms·
I have tried asking it all sorts of questions about specific obscure word etymologies and translations, obscure people's biographies (ancient and modern), histo
by jacobolus 2y ago
I have tried asking it all sorts of questions about specific obscure word etymologies and translations, obscure people's biographies (ancient and modern), historical events, organizations, academic citations, mathematical definitions and theorems, physical experiments, old machines, native plants, chemical reactions, diseases, engineering methods, ..., and it almost invariably flubs every question I throw at it, sometimes subtly and sometimes quite dramatically, often making up abject nonsense out of whole cloth. As a result I don't bother too much; I've found it to waste more time than it saves. To be fair, the kinds of questions I would want a tool like this to answer are usually ones I would have to spend some time and effort hunting to answer properly, and I'm pretty fast and effective at finding information.
I haven't tried asking too much about questions that I could trivially answer some other way. If what you want to know can be found in any intro undergrad textbook or standard dictionary (or Wikipedia), it's plausible that it would be better able to parrot back more or less the correct thing. But again, I haven't done much of this, preferring to just get hold of the relevant dictionary or textbook and read it directly.
I'll give you an example. I just now asked chatgpt.com what Lexell's theorem is and it says this:
> Lexell's theorem is a result in geometry related to spherical triangles. Named after the mathematician Michel Léonard Jean Leclerc, known as Lexell, it states: ¶ In a spherical triangle, if the sum of the angles is greater than π radians (or 180 degrees), then the spherical excess (the amount by which the sum of the angles exceeds π) is equal to the area of the spherical triangle on a unit sphere. ¶ In simpler terms, for a spherical triangle, the difference between the sum of its angles and π radians (180 degrees) gives the area of the triangle when the sphere is of unit radius. This theorem is fundamental in spherical geometry and helps relate angular measurements directly to areas on a sphere.
This gets the basic topic right ("is a result in geometry related to spherical triangles", involves area or spherical excess) but everything else about the answer, starting with the mathematician's identity, is completely wrong.
If I tell it that this is incorrect, it repeats a random assortment of other statements, none of which is actually the theorem I am asking about. E.g.
> [...] In a spherical triangle, if you have a spherical triangle with vertices A, B, and C, and the sides of the triangle are a, b, and c (measured in radians), then: ¶ cos(a)cos(b) + sin(a)sin(b)cos(C) = cos(c). [...]
or
> [...] In a spherical polyhedron, the sum of the angles at each vertex is equal to 2π radians minus the sum of the interior angles of the faces meeting at that vertex. [...]
If you want to know what Lexell's theorem actually is, you can read the Wikipedia article I wrote last year: https://en.wikipedia.org/wiki/Lexell%27s_theorem https://en.wikipedia.org/wiki/Lexell%27s_theorem
> every spherical triangle with the same surface area on a fixed base has its apex on a small circle, called Lexell's circle or Lexell's locus, passing through each of the two points antipodal to the two base vertices.
The problem ChatGPT has is that it's not able to just say something true but incomplete such as "I'm not sure what Lexell's theorem is or who Lexell was, but I know the theorem has something to do with spherical trigonometry; maybe it could be found in the more comprehensive books about the subject such as Todhunter & Leathem 1901 or Casey 1889".
Instead it just authoritatively spouts one bit of nonsense after another. (Every topic I have ever tried asking it about in detail is more or less the same.) The incorrect statements range from subtly wrong (e.g. two different things with similar names got conflated and some of the properties of the more common one were incorrectly applied to the other) to complete nonsense (jumbles of technical jargon strung together that are more or less gibberish). It's clear if you read carefully about any technical topic that it doesn't actually understand what it is saying, and is just combining bits of vaguely related material. Answers to technical questions are almost never entirely technically accurate unless you ask a very standard question about a very basic topic.
Anyone using it for any purpose should (a) be already pretty media literate with some domain expertise, and (b) be willing to carefully verify every part of every statement.
- CamperBob2 2y agoCan't argue with that. Your earlier point is the key: "e.g. the answer you want isn't already included in Wikipedia." Anything specialized enough not to be covered by Wikipedia or similar resources -- or where, in your specific example, the topic was only recently added -- is not a good subject for ChatGPT. Not yet, anyway. Now, pretend you're taking your first linear algebra course, and you don't quite understand the whole determinant thing. Go ask it for help with that, and you will have a very different experience. In my own case, what opened my eyes was asking it for some insights into computing the Cramer-Rao bound in communications theory. I needed to come up to speed in that area awhile back, but I'm missing some prereqs, so textbook chapters on the topic aren't as helpful as an interactive conversation with an in-person tutor would be. I was blown away at how effective GPT4o was at answering follow-up questions and imparting actionable insights.
- kergonath 2y agoA problem, though, is that it is not binary. There is a whole spectrum of nonsense, and if you are not a specialist it is not obvious to figure out the accuracy of the reply. Sometimes by chance you end up asking for something the model knows about for some reason, but very often not. That is the wrong aspect of it. Students might rely on it in their 1st year because it worked a couple of times and then learn a lot of nonsense among the truthy facts LLMs tend to produce. The main problem is not that they are wrong. It would be simpler if they were. But then, recommending students to use them as tutors is really not a good idea, unless what you want is overconfidently wrong students (I mean more than some of them already are). It’s not random doomsayers saying this; it’s university professors and researchers with advanced knowledge. Exactly the people that should be trusted for this kind of things, more than AI techbros.
- CamperBob2 2y agoWe could probably find a middle ground for agreement if we said, "Don't use current-gen LLMs as a tutor in fields where the answer can't be checked easily." So... advanced math? Maybe not such a good idea, at least for independent study where you don't have access to TAs or profs. I do think there's a lot of value in the ELI5 sense, though. Someone who spends time asking ChatGPT4 about Galois theory may not come away with the skills to actually pass a math test. But if they pursue the conversation, they will absolutely come away with a good understanding of the fundamentals, even with minimal prior knowledge. Programming? Absolutely. You were going to test that code anyway, weren't you? Planning and specification stages for a complex, expensive, or long-term project? Not without extreme care. Generating articles on quantum gravity for Social Text? Hell yeah.