Hugging Face 倫理與社會電子報 #4：文字生成圖像模型中的偏見問題
Original: Ethics and Society Newsletter #4: Bias in Text-to-Image Models
The Hugging Face Ethics and Society team has published the fourth edition of its newsletter, this time focusing on the problem of "bias" in…
本期 Hugging Face 倫理與社會電子報聚焦於文字生成圖像（Text-to-Image）模型的偏見。文章指出，這些模型在生成職業、社會角色等圖像時，常顯露出嚴重的性別與種族刻板印象。這源於訓練數據中不均衡的代表性，Hugging Face 呼籲社群透過開發評估工具與推動數據透明化來共同應對此挑戰。
The Hugging Face Ethics and Society team has published the fourth edition of its newsletter, this time focusing on the problem of "bias" in text-to-image (T2I) models. As image generation technologies like Stable Diffusion and Midjourney have become more widespread, these models — while demonstrating remarkable creative power — have also replicated and amplified pre-existing biases and stereotypes present in human society.
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