I work with a database that draws off experimental data on response times in human trials from Wash U St. Louis. Alternatively you can use standardized grade level vocab lists that exist in a number of states. Frequency data is also associated.

Obviously there’s no true silver bullet to defining it, but I think we all have some intuition or recognize a degree of objectivity to what a reasonably correct ordering of a random selection of words would look like based on our understanding of language (including two-word terms like “ice cream”, idiomatic phrases like “rain cats and dogs”, or borrowed expressions like “deja vu” and “savoir faire”). Which in my mind means GPT should also be able to achieve an intuition. I encourage people to try this with GPT, it doesn’t perform well (at least by any human intuition standard) in my experience.

What’s interesting to me is the possibility that the model defines the “difficulty of words” as it itself experiences them. Words that are for whatever reason more “difficult” for the model itself to assess.

Sorry, I’ll try to report back with something more concrete.

Another thing I’ve found that GPT still really struggles with is ranking a list of words accurately by difficulty. I tried many different prompt styles and couldn’t get a result that even approached satisfactory.

Even if the person were a minority, how would you even know… ?

We’re talking about a crazy person shoving ppl in front of trains. Any politics you try to put on it is wild speculation unless the perpetrator actually says that’s why they did it.