{"title":"人工智能建议使写作趋同于西方风格,削弱了文化的细微差别","authors":"Dhruv Agarwal, Mor Naaman, Aditya Vashistha","doi":"arxiv-2409.11360","DOIUrl":null,"url":null,"abstract":"Large language models (LLMs) are being increasingly integrated into everyday\nproducts and services, such as coding tools and writing assistants. As these\nembedded AI applications are deployed globally, there is a growing concern that\nthe AI models underlying these applications prioritize Western values. This\npaper investigates what happens when a Western-centric AI model provides\nwriting suggestions to users from a different cultural background. We conducted\na cross-cultural controlled experiment with 118 participants from India and the\nUnited States who completed culturally grounded writing tasks with and without\nAI suggestions. Our analysis reveals that AI provided greater efficiency gains\nfor Americans compared to Indians. Moreover, AI suggestions led Indian\nparticipants to adopt Western writing styles, altering not just what is written\nbut also how it is written. These findings show that Western-centric AI models\nhomogenize writing toward Western norms, diminishing nuances that differentiate\ncultural expression.","PeriodicalId":501541,"journal":{"name":"arXiv - CS - Human-Computer Interaction","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances\",\"authors\":\"Dhruv Agarwal, Mor Naaman, Aditya Vashistha\",\"doi\":\"arxiv-2409.11360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large language models (LLMs) are being increasingly integrated into everyday\\nproducts and services, such as coding tools and writing assistants. As these\\nembedded AI applications are deployed globally, there is a growing concern that\\nthe AI models underlying these applications prioritize Western values. This\\npaper investigates what happens when a Western-centric AI model provides\\nwriting suggestions to users from a different cultural background. We conducted\\na cross-cultural controlled experiment with 118 participants from India and the\\nUnited States who completed culturally grounded writing tasks with and without\\nAI suggestions. Our analysis reveals that AI provided greater efficiency gains\\nfor Americans compared to Indians. Moreover, AI suggestions led Indian\\nparticipants to adopt Western writing styles, altering not just what is written\\nbut also how it is written. These findings show that Western-centric AI models\\nhomogenize writing toward Western norms, diminishing nuances that differentiate\\ncultural expression.\",\"PeriodicalId\":501541,\"journal\":{\"name\":\"arXiv - CS - Human-Computer Interaction\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Human-Computer Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.11360\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances
Large language models (LLMs) are being increasingly integrated into everyday
products and services, such as coding tools and writing assistants. As these
embedded AI applications are deployed globally, there is a growing concern that
the AI models underlying these applications prioritize Western values. This
paper investigates what happens when a Western-centric AI model provides
writing suggestions to users from a different cultural background. We conducted
a cross-cultural controlled experiment with 118 participants from India and the
United States who completed culturally grounded writing tasks with and without
AI suggestions. Our analysis reveals that AI provided greater efficiency gains
for Americans compared to Indians. Moreover, AI suggestions led Indian
participants to adopt Western writing styles, altering not just what is written
but also how it is written. These findings show that Western-centric AI models
homogenize writing toward Western norms, diminishing nuances that differentiate
cultural expression.