代表性和面孔主义:图像搜索中的性别偏见
Roberto Ulloa1, Ana Carolina Richter2, Mykola Makhortykh3
1GESIS-Leibniz Institute for the Social Sciences, Germany.
概括
搜索引擎图像显示性别偏见,女性代表较少,面对身体比例较小 (面对面). 需要算法失调来解决这些表示和面孔主义偏见.
科学领域:
- 媒体研究 媒体研究
- 计算机科学 计算机科学
- 社会学 社会学 社会学
背景情况:
- 在媒体表现中,性别偏见很普遍.
- 女性面临的代表性不足 (代表性偏见) 和歪曲的图像比例 (面貌主义偏见).
研究的目的:
- 调查搜索引擎图像结果中的代表性和面孔主义偏见.
- 确定搜索引擎是否延续了其他媒体中发现的性别偏见.
主要方法:
- 使用性别中立和性别化术语对四个搜索引擎 (谷歌,Bing,百度,Yandex) 进行系统查询.
- 使用自动识别分析前100个性别表达和面对身体比率的图像结果.
主要成果:
- 搜索引擎图像证实了代表性偏见,在性别中立术语的结果中显示的女性较少.
- 面对主义偏见也得到证实,女性的面对身体比率较低.
- 这些偏见反映了在更广泛的媒体环境中发现的偏见.
结论:
- 搜索引擎图像结果延续了对女性有害的性别偏见.
- 迫切需要进行算法除,特别是针对图像搜索结果中的性别偏见.
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