Depending on how broadly you define it, something like 10-30% of the world's population is white. Africa is about 20% of the world population; Asia is 60% of it.
One in four sounds about right?
One in four sounds about right?
The current state of the art in AI gets things wrong regularly.
If you ask for a picture of nazi soldiers it shouldn't have 60% Asian people like you say. You know you're wrong but instead of admitting it, you're moving the goalpost to "hands".
This entire thread is you being insincere.
Here's some corporate-lawyer-speak straight from Google:
> We are aware that Gemini is offering inaccuracies...
> As part of our AI principles, we design our image generation capabilities to reflect our global user base, and we take representation and bias seriously.
Probably the only chance where you wouldn't expect this are in heavily colonized places like South Africa, Australia, and the Americas.
Of course it has. Again, these things regularly give humans extra fingers and arms. They don't even know what humans fundamentally look like.
On the flip side, humans are shitty at recognizing bias. This comment thread stems from someone complaining the AI only rarely generated white people, but that's statistically accurate. It feels biased to someone in a majority-white nation with majority-white friends and coworkers, but it fundamentally isn't.
I don't doubt that there are some attempts to get LLMs to go outside the "white westerner" bubble in training sets and prompts. I suspect the extent of it is also deeply exaggerated by those who like to throw around woke-this and woke-that as derogatories.
> This comment thread stems from someone complaining the AI only rarely generated white people, but that's statistically accurate. It feels biased to someone in a majority-white nation with majority-white friends and coworkers, but it fundamentally isn't.
So the AI is simultaneously too dumb to figure out what humans look like, but also so super smart that it uses precisely accurate racial proportions when generating people (not because it's been specifically adjusted to, but naturally)? Bullshit.
> I don't doubt that there are some attempts to get LLMs to go outside the "white westerner" bubble in training sets and prompts. I suspect the extent of it is also deeply exaggerated by those who like to throw around woke-this and woke-that as derogatories.
You're dodging the question. Do you actually believe the reason that the last example in the article looks very much not like a man is a deep technical issue, or a DEI initiative? If the former, how much are you willing to bet? If the latter, why are you throwing out these insincere arguments?
It literally refuses to generate images of white people when prompted directly while not only happily obliging but only producing that specific race in all 4 results for all others. It’s discriminatory and based on your inability to see that, you may be too.