Had a lot of fun with my stats students today. I gave them two data sets. One from a random number generator, the other was one I made up that was not random, but designed to look random. They were able to figure out which one was fake.
Then we had ChatGPT make the same kind of data set (random numbers 1-6 set of 100) and it had the same problems as my fake set but in a different way.
We talked about the study about AI generated passwords.
There is something very creepy about the way LLMs willy cheerfully give lists of "random" numbers. But they aren't random in frequency, and as my students pointed out "it's probably from some webpage about how to generate random numbers"
But even then, why is the frequency so unnaturally regular? Is that an artifact from mixing lists of real random numbers together?
The LLM is like a little box of computer horrors that we peer into from time to time.
I'm sorry but the whole interface is just so silly.
You ask for random numbers with sentences and it pretends to give them to you? What are we doooooing?
@futurebird I do truly wonder how many "non techies" understand that none of this AI stuff actually understands the questions it is asked, or the things it reads, etc.
Like, you and I know it's just sparkling autocomplete. But how many of my family members know that? And actually understand what that means? And why it leads to the outcomes it does?
This is the epistemological issue I have with the interface. It's ... well, not to be harsh but it's deceptive.
If you ask a "computer" for random numbers that has a kind of meaning, and expected process. If you ask a computer "how did you generate those random numbers?" that also has a set of expectations... and an LLM isn't meeting ANY of them.
myrmepropagandist
Rick Osborne