Janet Wessler, T. Schneeberger, Leon Christidis, Patrick Gebhard
{"title":"虚拟反作用:支配地位的非语言表达导致对支配地位的女性比男性更不喜欢","authors":"Janet Wessler, T. Schneeberger, Leon Christidis, Patrick Gebhard","doi":"10.1145/3514197.3549682","DOIUrl":null,"url":null,"abstract":"Backlash is a form of social penalty occurring when people behave counter-stereotypically. When promoting themselves, dominant females compared to males are typically liked less and paid worse, because dominance is associated with males, and proscribed for females. Such backlash effects have been shown in human-human interactions, but attempts to replicate them in human-agent interactions have not been successful so far [40]. Here, the goal was to show backlash effects for virtual agents with a nonverbal manipulation of dominance. In an online experiment, N = 223 participants watched the video of a female or male virtual agent presenting themselves as a career coach while using either large or small gestures. They rated the agent's dominance, liking, competence, and made a monetary offer of how much they would pay for the coaching. Agents using large gestures were perceived as more dominant than those using small gestures. Moreover, a backlash effect emerged: Dominant female compared to male agents were liked less. Participants were not penalizing the female dominant agent in monetary offers. Overall, participants rated the female agents as less competent than male ones. The results underline the importance of considering effects of the agent's gender in research on human-agent interaction.","PeriodicalId":149593,"journal":{"name":"Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Virtual backlash: nonverbal expression of dominance leads to less liking of dominant female versus male agents\",\"authors\":\"Janet Wessler, T. Schneeberger, Leon Christidis, Patrick Gebhard\",\"doi\":\"10.1145/3514197.3549682\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Backlash is a form of social penalty occurring when people behave counter-stereotypically. When promoting themselves, dominant females compared to males are typically liked less and paid worse, because dominance is associated with males, and proscribed for females. Such backlash effects have been shown in human-human interactions, but attempts to replicate them in human-agent interactions have not been successful so far [40]. Here, the goal was to show backlash effects for virtual agents with a nonverbal manipulation of dominance. In an online experiment, N = 223 participants watched the video of a female or male virtual agent presenting themselves as a career coach while using either large or small gestures. They rated the agent's dominance, liking, competence, and made a monetary offer of how much they would pay for the coaching. Agents using large gestures were perceived as more dominant than those using small gestures. Moreover, a backlash effect emerged: Dominant female compared to male agents were liked less. Participants were not penalizing the female dominant agent in monetary offers. Overall, participants rated the female agents as less competent than male ones. The results underline the importance of considering effects of the agent's gender in research on human-agent interaction.\",\"PeriodicalId\":149593,\"journal\":{\"name\":\"Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3514197.3549682\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3514197.3549682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Virtual backlash: nonverbal expression of dominance leads to less liking of dominant female versus male agents
Backlash is a form of social penalty occurring when people behave counter-stereotypically. When promoting themselves, dominant females compared to males are typically liked less and paid worse, because dominance is associated with males, and proscribed for females. Such backlash effects have been shown in human-human interactions, but attempts to replicate them in human-agent interactions have not been successful so far [40]. Here, the goal was to show backlash effects for virtual agents with a nonverbal manipulation of dominance. In an online experiment, N = 223 participants watched the video of a female or male virtual agent presenting themselves as a career coach while using either large or small gestures. They rated the agent's dominance, liking, competence, and made a monetary offer of how much they would pay for the coaching. Agents using large gestures were perceived as more dominant than those using small gestures. Moreover, a backlash effect emerged: Dominant female compared to male agents were liked less. Participants were not penalizing the female dominant agent in monetary offers. Overall, participants rated the female agents as less competent than male ones. The results underline the importance of considering effects of the agent's gender in research on human-agent interaction.