The thinness of GenAI: body size in relation to the construction of the normate through GenAI image models

Aisha Sobey
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引用次数: 0

Abstract

While generative AI (genAI) image models are increasingly popular, they are not without critique for their biased outputs. Building on assessments of Dall-E’s prejudiced and homogenising production of race, this paper seeks to understand how fat bodies are presented compared to straight-size bodies in 649 images created by nine different, free-to-use genAI image models. The images are examined through critical visual analysis and reflexive thematic analysis. In the first instance, auditing highlights that, if not explicitly prompted to show larger bodies, none of the models create fatness or disability. Secondly, in the outputs with a larger body-size prompt, the models produced images which contravened their own content guidelines, showed fewer positive facial expressions, and had higher rates of mistakes and anomalies compared to images without a body-size prompt. This paper argues that the social imaginaries created through genAI images are foreclosing on difference and forming new normate standards of personhood, which explicitly exclude people who exist in socially deviant bodies.

GenAI的瘦度:身体大小与通过GenAI图像模型构建规范的关系
虽然生成式人工智能(genAI)图像模型越来越受欢迎,但它们也因其有偏见的输出而受到批评。基于对Dall-E种族偏见和同质化生产的评估,本文试图了解由9个不同的免费使用的基因图像模型创建的649张图像中,与身材正常的身体相比,肥胖的身体是如何呈现的。通过批判性的视觉分析和反思性的主题分析来检查图像。在第一个例子中,审计强调,如果没有明确提示显示更大的身体,没有模特造成肥胖或残疾。其次,在身体尺寸提示较大的输出中,与没有身体尺寸提示的图像相比,模特产生的图像违背了自己的内容指南,显示出较少的积极面部表情,并且有更高的错误率和异常率。本文认为,通过基因图像创造的社会想象排除了差异,形成了新的人格规范标准,明确排除了存在于社会偏差身体中的人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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