暨南学报(哲学社会科学版)

作者：赵精武, 陆睿

关键词：算法公平,不合理差别待遇,场景一致性,算法透明

基金：国家社会科学基金重大项目“信息法基础”（16ZDA075）。

算法模型的持续优化、数据分析技术的迭代升级改善了现有的信息服务质量,同时也引发了价格歧视、评分排序歧视、平台自我优待等不公平问题。算法公平治理体系的建构需要首先明确法律意义上算法不公的认定标准。对此,可以结合具体场景从形式要件、实质要件、例外规则三方面进行综合判断。在明确算法不公认定标准的基础上,为化解人类对自动化决策失控的忧虑,应当强化算法透明要求,通过矫正信息不对称最大限度降低数据、算法、人力中的偏见因素,以实现起点数据的完整准确、决策过程的公开透明、输出结果的合乎预期为依托,保障消费者知情权与公平交易权,促进数字经济健康发展。"/>template{display:none;}.mag-rich-xref-fn { cursor: pointer;}//长视频$(document).ready(function(){if($("#showLongArticleVideo") && $("#showLongArticleVideo").length && $("#showLongArticleVideo").length>0){mag_ajax_update({ele_id:'showLongArticleVideo',url:mag_currentQikanUrl() + "/CN/article/showLongArticleVideo.do?id="+$("#articleId").val()});}});$(document).ready(function(){window.metaData = {"journal":{"issn":"1000-5072","qiKanMingCheng_CN":"暨南学报（哲学社会科学版）","id":2,"qiKanMingCheng_EN":"Jinan Journal"},"fundList_cn":["国家社会科学基金重大项目“信息法基础”（16ZDA075）。"],"article":{"keywordList_cn":["算法公平","不合理差别待遇","场景一致性","算法透明"],"juan":"45","zhaiyao_cn":"算法模型的持续优化、数据分析技术的迭代升级改善了现有的信息服务质量,同时也引发了价格歧视、评分排序歧视、平台自我优待等不公平问题。算法公平治理体系的建构需要首先明确法律意义上算法不公的认定标准。对此,可以结合具体场景从形式要件、实质要件、例外规则三方面进行综合判断。在明确算法不公认定标准的基础上,为化解人类对自动化决策失控的忧虑,应当强化算法透明要求,通过矫正信息不对称最大限度降低数据、算法、人力中的偏见因素,以实现起点数据的完整准确、决策过程的公开透明、输出结果的合乎预期为依托,保障消费者知情权与公平交易权,促进数字经济健康发展。","endNoteUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=EndNote&id=6785","reference":"","bibtexUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=BibTeX&id=6785","articleType":"","abstractUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/10.11778/j.jnxb.20231118","qi":"9","id":6785,"nian":2023,"bianHao":"1696924649132-717856601","zuoZheEn_L":"ZHAO Jingwu, LU Rui","juanUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2023","shouCiFaBuRiQi":"2023-10-10","qiShiYe":"69","qiUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2023/V45/I9","lanMu_cn":"中国式现代化·数据治理","pdfSize":"1403","zuoZhe_CN":"赵精武, 陆睿","risUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=Ris&id=6785","title_cn":"从公示到透明:算法公平的风险挑战与治理路径","doi":"10.11778/j.jnxb.20231118","jieShuYe":"82","keywordList_en":["Algorithmic fairness","Unreasonable differential treatment","Contextual integrity","Algorithmic transparency"],"endNoteUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=EndNote&id=6785","zhaiyao_en":"The continuous optimization of algorithm models and the iterative upgrade of data analysis technology have improved the quality of existing information services, but at the same time, they have also caused unfair problems, such as price discrimination, sorting discrimination, and self-preferential treatment. 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来源：2023年第9期

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