Legal Risk Regulation of Personalized Recommendation Algorithms

XIE Yongjiang; YANG Yongxing; LIU Tao

doi:10.19979/j.cnki.issn10082689.2022110031

Volume 40 Issue 1

Feb. 2024

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XIE Yongjiang, YANG Yongxing, LIU Tao. Legal Risk Regulation of Personalized Recommendation Algorithms[J]. Journal of University of Science and Technology Beijing ( Social Sciences Edition), 2024, 40(1): 77-85. doi: 10.19979/j.cnki.issn10082689.2022110031

Citation:

XIE Yongjiang, YANG Yongxing, LIU Tao. Legal Risk Regulation of Personalized Recommendation Algorithms[J]. Journal of University of Science and Technology Beijing ( Social Sciences Edition), 2024, 40(1): 77-85. doi: 10.19979/j.cnki.issn10082689.2022110031

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Legal Risk Regulation of Personalized Recommendation Algorithms

doi: 10.19979/j.cnki.issn10082689.2022110031

Institute of Internet Governance and Law, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received Date: 2022-11-07
Available Online: 2024-01-04
Publish Date: 2024-02-25

Abstract

Abstract

Information overload has led to the rise of personalized recommendation algorithm for information distribution. Personalized recommendation algorithms, while solving problems of information overload and long tail, meeting users’ personalized needs, and improving the efficiency of Internet information service, have also triggered many legal risks such as the interference with with users’ self-generated meaning, privacy leakage, information cocoon, and algorithm discrimination. The mission of jurisprudence is not to praise the achievements of personalized recommendation algorithms, but to examine their potentially irrational consequences, and to explore how to reduce the risks possibly caused by the development of algorithmic recommendations through the rule of law. To this end, a responsive algorithm regulation should establish an open view of privacy protection, strengthen the obligation of algorithm notification and the right of algorithm application rejection, improve the right of algorithm interpretation, and build an algorithm audit system to reduce the legal risks brought by personalized recommendation algorithms under principles of integrity, autonomy, justice and proportionality.
- personalized recommendations,
- algorithm,
- legal risks,
- legal regulation

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References(34)

References

[1]	RESNICK P,VARIAN H R. Recommender systems [J]. Communications of the Association for Computing Machinery, 1997, 40(3):56-58. doi: 10.1145/245108.245121
[2]	杨博,赵鹏飞. 推荐算法综述[J]. 山西大学学报(自然科学版),2011,34(3):337-350.
[3]	孙光浩,刘丹青,李梦云. 个性化推荐算法综述[J]. 软件,2017,38(7):70-78.
[4]	赵俊逸,庄福振,敖翔,等. 协同过滤推荐系统综述[J]. 信息安全学报,2021,6(5):17-34.
[5]	刘勇,李永杰. 基于协同过滤算法的微信小程序智能助手[J]. 计算机系统应用,2019,28(5):71-76.
[6]	石媛. 个性化推荐算法综述[J]. 智能计算机与应用,2020,10(8):110-112.
[7]	李爱君. 人工智能法律行为论[J]. 政法论坛,2019,37(3):176-183.
[8]	丁晓东. 用户画像、个性化推荐与个人信息保护[J]. 环球法律评论,2019,41(5):82-96.
[9]	SCHOONMAKER J. Proactive privacy for a driverless age [J]. Information & Communications Technology Law, 2016, 25(2):1-33.
[10]	郑驰. 算法推荐的权利风险及其治理[J]. 大连海事大学学报(社会科学版),2022,21(4):51-60.
[11]	理查德·泰勒,卡斯·桑斯坦. 助推:如何做出有关健康、财富与幸福的最佳决策[M]. 刘宁,译. 北京:中信出版社,2015.
[12]	YEUNG K. “Hypernudge”:Big Data as a mode of regulation by design [J]. Information,Communication & Society,2016(1):1-19.
[13]	凯斯·桑斯坦. 信息乌托邦[M]. 毕竞悦,译. 北京:法律出版社,2008.
[14]	SIMA Y,HAN J. Online carnival and offline solitude:“Information cocoon” effect in the age of algorithms [C]//2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022). Dordrecht:Atlantis Press,2022:2461-2465.
[15]	宋保振,秦瑞标. 算法推荐下信息公平失衡的法律应对[J]. 扬州大学学报(人文社会科学版),2022,26(2):42-55.
[16]	匡文波. 智能算法推荐技术的逻辑理路、伦理问题及规制方略[J]. 深圳大学学报(人文社会科学版),2021,38(1):144-151. doi: 10.3969/j.issn.1000-260X.2021.01.015
[17]	朱俊. 论大数据时代的算法解释请求权[J]. 宁夏社会科学,2021(4):105-113.
[18]	匡文波. 对个性化算法推荐技术的伦理反思[J]. 上海师范大学学报(哲学社会科学版),2021,50(5):14-23.
[19]	邹开亮,王霞. 大数据算法背景下就业歧视规制初探[J]. 价格理论与实践,2020(6):37-42. doi: 10.19851/j.cnki.CN11-1010/F.2020.06.191
[20]	史尚宽. 民法总论[M]. 北京:中国政法大学出版社,2000.
[21]	李艳霞,龙维. 个性化推荐行为法律规制路径的选择——基于中国cookie隐私权纠纷第一案的思考[C]// 最高人民法院. 全国法院第29届学术讨论会获奖论文集:2018年卷. 北京:人民法院出版社,2018:425-431.
[22]	MOTLOBA P D. Understanding of the principle of Autonomy (Part 1) [J]. South African Dental Journal, 2018, 73(6):418-420.
[23]	庄晓平. 康德的自主理论:能否成为生命伦理学的自主原则[J]. 学术研究,2011(8):26-30,159.
[24]	MITTELSTADT B D,ALLO P,TADDEO M,et al. The ethics of algorithms:Mapping the debate [J]. Big Data & Society, 2016, 3(2):1-21.
[25]	沈伟,赵尔雅. 数字经济背景下的人工智能国际法规制[J]. 上海财经大学学报,2022,24(5):123-137.
[26]	约翰·罗尔斯. 正义论[M]. 何怀宏,何包钢,廖申白,译. 北京:中国社会科学出版社,1988.
[27]	徐玖玖. 人工智能的道德性何以实现? ——基于原则导向治理的法治进路[J]. 现代法学,2021,43(3):24-40. doi: 10.3969/j.issn.1001-2397.2021.03.02
[28]	张兰兰. 作为权衡方法的比例原则[J]. 法制与社会发展,2022,28(3):187-205.
[29]	王利明. 隐私权概念的再界定[J]. 法学家,2012(1):108-120,178. doi: 10.16094/j.cnki.1005-0221.2012.01.007
[30]	杨立新. 人格权法[M]. 北京:法律出版社,2011.
[31]	许可,朱悦. 算法解释权:科技与法律的双重视角[J]. 苏州大学学报(哲学社会科学版),2020,41(2):61-69,191.
[32]	张欣,宋雨鑫. 算法审计的制度逻辑和本土化构建[J]. 郑州大学学报(哲学社会科学版),2022,55(6):33-42.
[33]	张永忠,张宝山. 算法规制的路径创新:论我国算法审计制度的构建[J]. 电子政务,2022(10):48-61.
[34]	赵丽莉,张雪. 网络经营者数据竞争性权益归属研究[J]. 北京科技大学学报(社会科学版),2021,37(6):660-669.