{"title":"你听到了什么,又看到了什么?了解人机交互过程中面部识别和语音识别系统的透明度","authors":"Kun Xu, Xiaobei Chen, Fanjue Liu, Luling Huang","doi":"10.1177/14614448241256899","DOIUrl":null,"url":null,"abstract":"As social robots begin to assume various social roles in society, the demand for understanding how social robots work and communicate grows rapidly. While literature on explainable artificial intelligence suggests that transparency about a social robot’s working mechanism can evoke users’ positive attitudes, transparency may also have negative outcomes. This study investigates the paradoxical effects of the transparency of facial recognition technology and speech recognition technology in human–robot interactions. Based on a lab experiment and combined analyses of users’ quantitative and qualitative responses, this study suggests that the transparency of facial recognition technology in human–robot interaction increases users’ social presence, reduces privacy concerns, and enhances users’ acceptance of robots. However, exposure to both facial and speech recognition technologies revives users’ privacy worries. This study further parses users’ open-ended evaluation of the prospective application of social robots’ tracking technologies and discusses the theoretical, practical, and ethical value of the findings.","PeriodicalId":443328,"journal":{"name":"New Media & Society","volume":"12 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"What did you hear and what did you see? Understanding the transparency of facial recognition and speech recognition systems during human–robot interaction\",\"authors\":\"Kun Xu, Xiaobei Chen, Fanjue Liu, Luling Huang\",\"doi\":\"10.1177/14614448241256899\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As social robots begin to assume various social roles in society, the demand for understanding how social robots work and communicate grows rapidly. While literature on explainable artificial intelligence suggests that transparency about a social robot’s working mechanism can evoke users’ positive attitudes, transparency may also have negative outcomes. This study investigates the paradoxical effects of the transparency of facial recognition technology and speech recognition technology in human–robot interactions. Based on a lab experiment and combined analyses of users’ quantitative and qualitative responses, this study suggests that the transparency of facial recognition technology in human–robot interaction increases users’ social presence, reduces privacy concerns, and enhances users’ acceptance of robots. However, exposure to both facial and speech recognition technologies revives users’ privacy worries. This study further parses users’ open-ended evaluation of the prospective application of social robots’ tracking technologies and discusses the theoretical, practical, and ethical value of the findings.\",\"PeriodicalId\":443328,\"journal\":{\"name\":\"New Media & Society\",\"volume\":\"12 9\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New Media & Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/14614448241256899\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Media & Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/14614448241256899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
What did you hear and what did you see? Understanding the transparency of facial recognition and speech recognition systems during human–robot interaction
As social robots begin to assume various social roles in society, the demand for understanding how social robots work and communicate grows rapidly. While literature on explainable artificial intelligence suggests that transparency about a social robot’s working mechanism can evoke users’ positive attitudes, transparency may also have negative outcomes. This study investigates the paradoxical effects of the transparency of facial recognition technology and speech recognition technology in human–robot interactions. Based on a lab experiment and combined analyses of users’ quantitative and qualitative responses, this study suggests that the transparency of facial recognition technology in human–robot interaction increases users’ social presence, reduces privacy concerns, and enhances users’ acceptance of robots. However, exposure to both facial and speech recognition technologies revives users’ privacy worries. This study further parses users’ open-ended evaluation of the prospective application of social robots’ tracking technologies and discusses the theoretical, practical, and ethical value of the findings.