30.10.2025
©Terzo Algeri/Fotoatelier M/ TUM
Language Shapes Gender Bias in AI Images
TUM News
Alexander Fraser, MCML PI, and his team discovered that AI image generators reproduce gender stereotypes differently across languages. In their study of nine languages, they found that generic prompts like “accountant” mostly produced male images, while explicitly feminine or neutral prompts reduced bias but sometimes affected image quality.
The study highlights that AI is not language‑agnostic and careful wording can influence outcomes, underlining the need for fairness and multilingual awareness in AI systems.
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