{"title":"人工智能的性别视角:审视跨数字空间的新闻图像","authors":"Yibei Chen, Yujia Zhai, Shaojing Sun","doi":"10.1093/jcmc/zmad047","DOIUrl":null,"url":null,"abstract":"This study investigates gender representation in artificial intelligence (AI)-related images across various digital spaces to understand potential biases and visual narratives in the AI domain. We analyzed a dataset of 28,199 images from news media, technology news websites, social media, knowledge-sharing platforms, and other digital spaces. Our findings revealed the prevalence of male faces and the consistent underrepresentation of women across digital spaces. We also found distinct patterns in the visual framing of men and women, with women often portrayed as being disempowered and adhering to traditional gender stereotypes. Furthermore, our cluster analysis demonstrated consistent patterns of gender representation across various visual themes, reinforcing the pervasive nature of gender biases in AI news imagery. In conclusion, our study underscores the need for conscious efforts to promote a more balanced and inclusive portrayal of gender in AI news reporting, calling for a broad societal effort toward advancing gender equality and diversity.","PeriodicalId":48319,"journal":{"name":"Journal of Computer-Mediated Communication","volume":"190 1","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The gendered lens of AI: examining news imagery across digital spaces\",\"authors\":\"Yibei Chen, Yujia Zhai, Shaojing Sun\",\"doi\":\"10.1093/jcmc/zmad047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigates gender representation in artificial intelligence (AI)-related images across various digital spaces to understand potential biases and visual narratives in the AI domain. We analyzed a dataset of 28,199 images from news media, technology news websites, social media, knowledge-sharing platforms, and other digital spaces. Our findings revealed the prevalence of male faces and the consistent underrepresentation of women across digital spaces. We also found distinct patterns in the visual framing of men and women, with women often portrayed as being disempowered and adhering to traditional gender stereotypes. Furthermore, our cluster analysis demonstrated consistent patterns of gender representation across various visual themes, reinforcing the pervasive nature of gender biases in AI news imagery. In conclusion, our study underscores the need for conscious efforts to promote a more balanced and inclusive portrayal of gender in AI news reporting, calling for a broad societal effort toward advancing gender equality and diversity.\",\"PeriodicalId\":48319,\"journal\":{\"name\":\"Journal of Computer-Mediated Communication\",\"volume\":\"190 1\",\"pages\":\"\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer-Mediated Communication\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1093/jcmc/zmad047\",\"RegionNum\":1,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer-Mediated Communication","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1093/jcmc/zmad047","RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
The gendered lens of AI: examining news imagery across digital spaces
This study investigates gender representation in artificial intelligence (AI)-related images across various digital spaces to understand potential biases and visual narratives in the AI domain. We analyzed a dataset of 28,199 images from news media, technology news websites, social media, knowledge-sharing platforms, and other digital spaces. Our findings revealed the prevalence of male faces and the consistent underrepresentation of women across digital spaces. We also found distinct patterns in the visual framing of men and women, with women often portrayed as being disempowered and adhering to traditional gender stereotypes. Furthermore, our cluster analysis demonstrated consistent patterns of gender representation across various visual themes, reinforcing the pervasive nature of gender biases in AI news imagery. In conclusion, our study underscores the need for conscious efforts to promote a more balanced and inclusive portrayal of gender in AI news reporting, calling for a broad societal effort toward advancing gender equality and diversity.
期刊介绍:
The Journal of Computer-Mediated Communication (JCMC) has been a longstanding contributor to the field of computer-mediated communication research. Since its inception in 1995, it has been a pioneer in web-based, peer-reviewed scholarly publications. JCMC encourages interdisciplinary research, welcoming contributions from various disciplines, such as communication, business, education, political science, sociology, psychology, media studies, and information science. The journal's commitment to open access and high-quality standards has solidified its status as a reputable source for scholars exploring the dynamics of communication in the digital age.