this post was submitted on 07 May 2024
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How traditional? How statistically relevant is it? Most Indians i know do not wear turbans at all.
If these stats are trustworthy (and i think they are), the only Indians that wear turbans are Sikhs (1.7%) and Muslims (14.2%). I'd say 15.9% is not statistically significant.
I think you're looking at it wrong. The prompt is to make an image of someone who is recognizable as Indian. The turban is indicative clothing of that heritage and therefore will cause the subject to be more recognizable as Indian to someone else. The current rate at which Indian people wear turbans isn't necessarily the correct statistic to look at.
What do you picture when you think, a guy from Texas? Are they wearing a hat? What kind? What percentage of Texans actually wear that specific hat that you might be thinking of?
A surprising number of Texans wear cowboy and trucker hats (both stereotypical). A surprising number of Indians don't wear turbans since it's by far a minority.
Woosh
I think the idea is that it's what makes a person "an Indian" and not something else.
Only a minority of Indians wear turbans, but more Indians than other people wear turbans. So if someone's wearing a turban, then that person is probably Indian.
I'm not saying that's true necessarily (though it may be), but that's how the AI interprets it...or how pictures get tagged.
It's like with Canadians and maple leaves. Most Canadians aren't wearing maple leaf stuff, but I wouldn't be surprised if an AI added maple leaves to an image of "a Canadian".
Imagine a German man from Bavaria... You just thought of a man wearing Lederhosen and holding a beer, didn't you? Would you be surprised if I told you that they usually don't look like that outside of a festival?
I don't picture real life people as though they were caricatures.
But AI does, because we feed it caricatures.
Are you literally the second coming of Jesus? Hey everybody! I found a guy who doesn't see race! I can't believe it but he doesn't think anyone is changed in any way by the place that they grew up in or their culture! Everyone is a blank slate to this guy! It's amazing!
No, I just don't lob groups of people together. It's not that hard to do, everyone's a different person.
He was imaginary though.
Point taken.
Ain't to me, couldn't care less. I was just trying to point out that most Indians do not seem to wear turbans (and based my reasoning on the religions dress alone).
What's the data that the model is being fed? What percentage of imaging featuring Indian men are tagged as such? What percentage of imaging featuring men wearing Turbans are tagged as Indian Men? Are there any images featuring Pakistan men wearing Turbans? Even if only a minority of Indian feature Turbans, if that's the only distinction between Indian and Pakistan men in the model data, the model will favor Turbans for Indian Men. That's just a hypothetical explanation.
You don't think nearly 1/6th is statistically significant? What's the lower bound on significance as you see things?
To be clear, it's obviously dumb for their generative system to be overrepresenting turbans like this, although it's likely to be a bias in the inputs rather than something the system came up with itself, I just think that 5% is generally enough to be considered significant and calling three times that not significant confuses me.
For statistics' sake? Yes.
For the LLM bias? No.
5/6 not wearing them seems more statistically significant
The fact less people of that group actually wear it than do is significant when you want an average sample. When categorizing a collection of images then, naturally, the traditional garments of a group is associated more with that group than any other group: 1/6 is bigger than any other race.
so if there was a country where 1 in 6 people had blue skin you would consider that insignificant because 5 out of 6 didn't?
For a caricature of the population? Yes, that's not what the algorithm should be optimising for.
Except if they trained it on something that has a large proportion of turban wearers. It is only as good as the data fed to it, so if there was a bias, it’ll show the bias. Yet another reason this really isn’t “AI”