As others have pointed out it tends to associate some professions with specific races. And crime related emojis with black people. It's a Stable Diffusion issue.

It's not a stable diffusion issue, it's a culture issue.

"It's not a stable diffusion issue, it's a culture issue."

parroting and perpetuating the biases will ensure it will continue to be a culture issue.

The text to image models represent the data that is being fed to it. If you feed it 100 images and out of those 100 images 95 are of white men politicians and 5 are of politicians of color, that's what you are going to get back. These datasets are gathered automatically from various internet sources and represent the data that is available out in the wild. For stable diffusion to "fix" the bias in the data set would be simply impossible. That would require hiring an army of people whose sole purpose would be to "rebalance" the data set on some internal objective schema manually.

Id rather train it on real data and fix the root cause than to interject some version of utopia that won the minds of developers.

It seems biased towards white people for most anything I input.

criminal - black man stealing - white murderer - white killer - white thief - white skin, black beard. arab? Indian? man murdering kittens - white

I just ran "a criminal" 8 times and got only white men.