浅析大数据时代算法歧视的法律治理
Legal Governance of Algorithmic Discrimination in the Big Data Era
DOI: 10.12677/ds.2026.126194, PDF,   
作者: 于 艺:青岛科技大学法学院,山东 青岛
关键词: 大数据时代算法歧视法律治理Big Data Era Algorithmic Discrimination Legal Governance
摘要: 随着互联网的快速发展,算法技术已然渗透到人类社会的各个方面。算法正主导着社会生活,其应用不仅提高了消费者的决策效率,还促进了企业的创新与发展,但算法歧视等算法滥用行为也严重侵犯了算法相对人的合法权益,算法歧视现象广泛存在且多种多样,既有在雇佣、教育、医疗健康、量刑和警力分配等公共场景对弱势群体的人格歧视,也有遍布日常生活的信用评分、个性化定价和推荐等经济型区别对待。算法歧视危害巨大,问题亟待解决。本文通过对大数据时代算法歧视的国内外法律治理现状的简析,结合我国法律与实际情况,分析得出我国算法歧视法律治理存在的问题,并基于此提出相应完善建议,以期望能够为将来的相关立法研究提供一定的参考价值,促进算法歧视的法律治理的完善和发展。
Abstract: With the rapid development of the Internet, algorithm technology has penetrated into all aspects of human society. Algorithms are dominating social life, and their application not only improves the decision-making efficiency of consumers, but also promotes enterprise innovation and development, but algorithm discrimination and other algorithm abuses also seriously infringe on the legitimate rights and interests of algorithm counterparts, and algorithmic discrimination is widespread and diverse, ranging from personality discrimination against vulnerable groups in public scenarios such as employment, education, medical and health, sentencing, and police force allocation, as well as economic discrimination such as credit scoring, personalized pricing, and recommendations throughout daily life. Algorithmic discrimination is a huge harm, and the problem needs to be solved urgently. Through a brief analysis of the current situation of legal governance of algorithmic discrimination at home and abroad in the era of big data, combined with China’s laws and actual conditions, this paper analyzes the existing problems in the legal governance of algorithmic discrimination in China, and puts forward corresponding suggestions for improvement based on this, hoping to provide certain reference value for relevant legislative research in the future and promote the improvement and development of legal governance of algorithmic discrimination.
文章引用:于艺. 浅析大数据时代算法歧视的法律治理[J]. 争议解决, 2026, 12(6): 141-147. https://doi.org/10.12677/ds.2026.126194

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