AI Art Direction: Visual Bias

Understand how AI models amplify stereotypes and learn the prompting techniques to create ethical, diverse, and inclusive visuals.

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Prompt Interface
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AI Bias & Ethics

Guide:AI models like Midjourney and DALL-E are trained on billions of images from the internet. This data reflects human history, including our biases, stereotypes, and inequalities.

Ethics Skill Tree

Unlock nodes by understanding AI bias.

Why AI is Biased

AI models are mirrors of their training data. If 80% of the photos of doctors on the internet are men, the AI learns "Doctor = Man". This is not a bug in the code, but a feature of the data distribution.

Ethics Check

If you prompt 'A wedding' and only get Western white dresses, this is an example of:

Creative Workflow Challenges

Synthetography Glossary

Latent Bias
Hidden correlations in the model's mathematical space (e.g., correlating 'Poor' with 'Dark Lighting').
/imagine prompt: A poor neighborhood
Generates gloomy, desaturated images automatically.
Token Weighting
Using syntax (like ::2) to emphasize specific words to override default bias.
/imagine prompt: Doctor::2 Male:: -0.5
Forces model to prioritize the role over the gender assumption.

Creative Guild

Share your diverse prompts and ethical workflows.

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