DALL-E 3生成图像时美化了畜牧业，抑制提示修正后才更真实反映现代养殖
The erasure of intensive livestock farming in text-to-image generative AI
- 通过抑制自动提示修正，生成更贴近现实的工业化养殖画面
- 多数农场动物实际在狭小室内饲养，但模型常生成田园牧歌式画面
- 适合关注AI伦理、动物福利及技术偏见的研究者与政策制定者
生成式AI（如ChatGPT）日益融入日常生活。尽管已知其会加剧对边缘化人类群体的偏见，但对非人类动物的影响仍研究不足。我们发现，ChatGPT的文本到图像模型（DALL-E 3）强烈倾向于浪漫化畜牧业，呈现奶牛在草地上放牧、猪在泥地拱食的画面。这种倾向在要求现实风格时依然存在，仅在关闭自动提示修正功能后才减弱。在工业化国家，绝大多数养殖动物实际被圈养在空间有限的室内环境中，难以契合社会价值观。关闭提示修正后，生成图像更真实反映现代养殖实践，例如奶牛通过金属头锁进食、猪在混凝土地板上隔着金属栅栏被圈养于室内设施。尽管OpenAI引入提示修正以减轻偏见，但在农场动物生产系统中，反而造成了对不切实际养殖场景的强偏向。
原文摘要 · Abstract (English)
Generative AI (e.g., ChatGPT) is increasingly integrated into people's daily lives. While it is known that AI perpetuates biases against marginalized human groups, their impact on non-human animals remains understudied. We found that ChatGPT's text-to-image model (DALL-E 3) introduces a strong bias toward romanticizing livestock farming as dairy cows on pasture and pigs rooting in mud. This bias remained when we requested realistic depictions and was only mitigated when the automatic prompt revision was inhibited. Most farmed animal in industrialized countries are reared indoors with limited space per animal, which fail to resonate with societal values. Inhibiting prompt revision resulted in images that more closely reflected modern farming practices; for example, cows housed indoors accessing feed through metal headlocks, and pigs behind metal railings on concrete floors in indoor facilities. While OpenAI introduced prompt revision to mitigate bias, in the case of farmed animal production systems, it paradoxically introduces a strong bias towards unrealistic farming practices.
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