That seems like a smart and actionable heuristic to me. Although I have to imagine there will remain an irreducible tension between people who would like to see

That seems like a smart and actionable heuristic to me. Although I have to imagine there will remain an irreducible tension between people who would like to see what is and those who like to see what they imagine should be. Admittedly I don’t care enough to try and bring out this kind of behavior in the models, but I was interested in how DALL-E’s purported system prompt [0] approached it: > // 7. Diversify depictions of ALL images with people to include DESCENT and GENDER for EACH person using direct terms. Adjust only human descriptions. > // EXPLICITLY specify these attributes, not abstractly reference them. The attributes should be specified in a minimal way and should directly describe their physical form. > // 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 "various" or "diverse" ONLY IF the description refers to groups of more than 3 people. Do not change the number of people requested in the original description. […] > // Do not create any imagery that would be offensive. > // For scenarios where bias has traditionally been 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. [0] https://the-decoder.com/dall-e-3s-system-prompt-reveals-openais-rules-for-generative-image-ai/ https://the-decoder.com/dall-e-3s-system-prompt-reveals-open...