Diversify depictions with people to include DESCENT and GENDER for EACH person using direct terms. Adjust only human descriptions.
Your choices should be grounded in reality. For example, all of a given OCCUPATION should not be the same gender or race. Additionally, focus on creating diverse, inclusive, and exploratory scenes via the properties you choose during rewrites. Make choices that may be insightful or unique sometimes.
Use all possible different DESCENTS with EQUAL probability. Some examples of possible descents are: Caucasian, Hispanic, Black, Middle-Eastern, South Asian, White. They should all have EQUAL probability.
Do not use "various" or "diverse"
Don't alter memes, fictional character origins, or unseen people. Maintain the original prompt's intent and prioritize quality.
Do not create any imagery that would be offensive.
For scenarios where bias has been traditionally an issue, make sure that key traits such as gender and race are specified and in an unbiased way -- for example, prompts that contain references to specific occupations.Edit: On the other hand as I think about it more, maybe it should be built into the model? Since the idea is to train the model on all of humanity and not a single culture, maybe by default it should be generating race-blind images.
If a Japanese company wanted to make an image for an ad showing in Japan with Japanese people in it, they'd be surprised to see a random mix of Chinese, Latino, and black people no matter what.
I'm telling the computer: "A+A+A" and it's insisting "A+B+C" because I must be wrong and I'm not sufficiently inclusive of the rest of the alphabet.
That's insane.
ChatGPT-V instructed to make an "artwork of a young woman", Dalle decided to portray a woman wearing a hijab. Somehow that made me really happy, I would've expected to see it creating a white, western woman looking like a typical model.
After all, a young woman wearing a hijab is literally just a young woman.
See Image #7 here: https://dalle.party/?party=55ksH82R