大数据杀熟行为的法律规制

Legal Regulation of Big Data Discriminatory Pricing behavior

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作者:

汤婉

摘要:

近年,大数据杀熟行为在交通出行、酒店预订和网络购物等诸多领域频繁发生。大数据杀熟行为本质上是计算机算法自动化决策所导致的算法歧视,直接侵犯了消费者的知情权、公平交易权和个人信息安全。目前我国对于大数据杀熟行为的相关立法尚未完善,监管难度较大,且消费者缺乏有效的救济途径。面对这些困境,论文基于国内法律规制的现状,结合大数据杀熟行为的法律性质及相关学说的分析,借鉴域外有益经验,探索进一步完善大数据杀熟行为法律规制的方法与路径。第一部分,论文首先分析了大数据杀熟行为的行为模式、特点和运行机制。对大数据杀熟行为的定性,学界有不同观点,主要是价格歧视说、价格欺诈说和算法歧视说。论文接下来从算法规制的必要性与大数据杀熟行为的违法性两方面论证了对大数据杀熟行为进行法律规制的必要性。此种行为侵犯了消费者的知情权、公平交易权和个人信息安全,违背了民法中的诚实信用原则。大数据杀熟行为还具有形成垄断的风险,可能破坏市场竞争秩序、侵害社会公共利益。第二部分,论文阐述了目前我国对于大数据杀熟行为法律规制的现状。《反垄断法》通过限制具有市场支配地位的经营者的价格歧视行为来规范大数据杀熟行为。《电子商务法》从保障消费者的知情权,规定经营者的信息披露义务来限制大数据杀熟。《个人信息保护法》是从个人信息保护的方面对大数据杀熟行为进行规制。《互联网信息服务算法推荐管理规定》对算法推荐服务作出了全面的规范,明确了算法治理体系和机制,有利于从源头上化解大数据杀熟行为。但目前我国该领域的立法中对算法权力的规范还不够完善,且存在消费者缺乏有效救济渠道、监管部门间的职能存在一定冲突等缺陷。第三部分,论文主要介绍了欧盟《个人信息保护条例》和美国的算法治理模式。欧盟《一般数据保护条例》规定了强大的数据主体权利,对数据控制者与数据处理者进行强监管。美国采用了行业自律和消费者隐私权立法并行的模式,法律还注重从算法治理方面规制大数据杀熟行为。论文指出可以借鉴域外这些有益经验,提高算法透明性,完善算法问责制,转变监管方式,采用多元化治理手段治理大数据杀熟行为。同时,确立数据主体权利,保护个人信息安全也是防范大数据杀熟的良方。第四部分,论文从不同角度提出了规制大数据杀熟行为的具体途径。必须推动相关的立法工作,避免法条竞合,破除平台与用户之间的信息不对称状况,保护公民个人信息和消费者知情权。应确立统一的监管主体,利用国家公权对算法权力进行有效制约和监督。要充分发挥互联网法院的职能,合理分配举证责任,畅通消费者投诉渠道,为消费者的维权之路扫清障碍。互联网行业要树立起相应的行业自律准则,规制算法决策自动化,遵循法律法规和人工智能伦理道德。消费者自身也应要增强自己的维权意识,积极防范大数据杀熟行为。

语种:

中文

提交日期

2022-06-17

引用参考

汤婉. 大数据杀熟行为的法律规制[D]. 西南政法大学,2022.

全文附件授权许可

知识共享许可协议-署名

  • dc.title
  • 大数据杀熟行为的法律规制
  • dc.title
  • Legal Regulation of Big Data Discriminatory Pricing behavior
  • dc.contributor.schoolno
  • 20200351022068
  • dc.contributor.author
  • 汤婉
  • dc.contributor.affiliation
  • 行政法学院
  • dc.contributor.degree
  • 硕士
  • dc.contributor.childdegree
  • 法律硕士专业学位
  • dc.contributor.degreeConferringInstitution
  • 西南政法大学
  • dc.identifier.year
  • 2022
  • dc.contributor.direction
  • 律师实务
  • dc.contributor.advisor
  • 刘文会
  • dc.contributor.advisorAffiliation
  • 行政法学院
  • dc.language.iso
  • 中文
  • dc.subject
  • 大数据杀熟,算法权力,价格歧视,个人信息安全,消费者权益
  • dc.subject
  • Big Data Discriminatory Pricing; Algorithmic Power; Price Discrimination; Personal Information Security; Consumer Rights
  • dc.description.abstract
  • 近年,大数据杀熟行为在交通出行、酒店预订和网络购物等诸多领域频繁发生。大数据杀熟行为本质上是计算机算法自动化决策所导致的算法歧视,直接侵犯了消费者的知情权、公平交易权和个人信息安全。目前我国对于大数据杀熟行为的相关立法尚未完善,监管难度较大,且消费者缺乏有效的救济途径。面对这些困境,论文基于国内法律规制的现状,结合大数据杀熟行为的法律性质及相关学说的分析,借鉴域外有益经验,探索进一步完善大数据杀熟行为法律规制的方法与路径。第一部分,论文首先分析了大数据杀熟行为的行为模式、特点和运行机制。对大数据杀熟行为的定性,学界有不同观点,主要是价格歧视说、价格欺诈说和算法歧视说。论文接下来从算法规制的必要性与大数据杀熟行为的违法性两方面论证了对大数据杀熟行为进行法律规制的必要性。此种行为侵犯了消费者的知情权、公平交易权和个人信息安全,违背了民法中的诚实信用原则。大数据杀熟行为还具有形成垄断的风险,可能破坏市场竞争秩序、侵害社会公共利益。第二部分,论文阐述了目前我国对于大数据杀熟行为法律规制的现状。《反垄断法》通过限制具有市场支配地位的经营者的价格歧视行为来规范大数据杀熟行为。《电子商务法》从保障消费者的知情权,规定经营者的信息披露义务来限制大数据杀熟。《个人信息保护法》是从个人信息保护的方面对大数据杀熟行为进行规制。《互联网信息服务算法推荐管理规定》对算法推荐服务作出了全面的规范,明确了算法治理体系和机制,有利于从源头上化解大数据杀熟行为。但目前我国该领域的立法中对算法权力的规范还不够完善,且存在消费者缺乏有效救济渠道、监管部门间的职能存在一定冲突等缺陷。第三部分,论文主要介绍了欧盟《个人信息保护条例》和美国的算法治理模式。欧盟《一般数据保护条例》规定了强大的数据主体权利,对数据控制者与数据处理者进行强监管。美国采用了行业自律和消费者隐私权立法并行的模式,法律还注重从算法治理方面规制大数据杀熟行为。论文指出可以借鉴域外这些有益经验,提高算法透明性,完善算法问责制,转变监管方式,采用多元化治理手段治理大数据杀熟行为。同时,确立数据主体权利,保护个人信息安全也是防范大数据杀熟的良方。第四部分,论文从不同角度提出了规制大数据杀熟行为的具体途径。必须推动相关的立法工作,避免法条竞合,破除平台与用户之间的信息不对称状况,保护公民个人信息和消费者知情权。应确立统一的监管主体,利用国家公权对算法权力进行有效制约和监督。要充分发挥互联网法院的职能,合理分配举证责任,畅通消费者投诉渠道,为消费者的维权之路扫清障碍。互联网行业要树立起相应的行业自律准则,规制算法决策自动化,遵循法律法规和人工智能伦理道德。消费者自身也应要增强自己的维权意识,积极防范大数据杀熟行为。
  • dc.description.abstract
  • In recent years, big data discriminatory pricing behavior has occurred frequently in many fields such as transportation, hotel reservation and online shopping. Big data discriminatory pricing behavior is essentially algorithmic discrimination caused by automatic decision of computer algorithms, which directly violates consumers' right to know, personal information security and fair trade. At present, the relevant legislation of big data discriminatory pricing behavior in China has not been perfected, and supervision is difficult, and consumers lack effective relief approaches. In the face of these difficulties, based on the current situation of domestic legal regulation, combined with the analysis of the legal nature of big data discriminatory pricing and related theories, this thesis uses useful experience from abroad to explore the methods and paths to further improve the legal regulation of big data discriminatory pricing.In the first part, the thesis first analyzes the behavior mode, characteristics and operation mechanism of big data discriminatory pricing behavior. There are different views on the qualitative of big data discriminatory pricing behavior, mainly price discrimination, price fraud and algorithm discrimination. Next, the thesis analyzes and demonstrates the necessity of legal regulation of big data discriminatory pricing from two aspects: the necessity of algorithmic regulation and the illegality of big data discriminatory pricing. Big data discriminatory pricing infringes consumers' rights to know, fair trade and personal information security, and violates the principle of good faith in the civil law. Big data discriminatory pricing also has the risk of forming monopoly, which may destroy the market competition order and infringe social public interests.In the second part, the thesis expounds the current status of China's legal regulation of big data discriminatory pricing. Anti-Monopoly Law of the People's Republic of China regulates big data discriminatory pricing by restricting price discrimination by dominant market operators. The E-Commerce Law of the People's Republic of China restricts the big data discriminatory pricing by guaranteeing consumers' right to know and stipulating operators' obligation of information disclosure. Personal Information Protection Law regulates big data discriminatory pricing from the aspect of personal information protection. Provisions on the Administration of Algorithm-generated Recommendations for Internet Information Services provide a comprehensive specification for algorithm recommendation services, and clarify the algorithm governance system and mechanism, which is conducive to resolving the big data discriminatory pricing behaviors from the source. However, the current legislation in this field in China is not perfect enough to regulate the power of algorithms, and there are deficiencies such as the lack of effective relief channels for consumers and the conflict between the functions of regulatory departments.The third part, the thesis mainly introduces the EU personal information protection regulations and the Algorithm governance model of the United States. The General Data Protection Regulation of the European Union provides for strong data subject rights and strong supervision of data controllers and data processors. The United States adopts the model of industry self-discipline and consumer privacy legislation in parallel and the law also focuses on the regulation of big data discriminatory pricing from the aspect of algorithmic governance. The thesis points out that we can learn from these useful experiences abroad, improve the transparency of the algorithm, improve the accountability system of the algorithm, change the supervision mode, and adopt diversified governance methods to govern the big data discriminatory pricing. Establishing the rights of data subjects and protecting personal information security is also a good way to prevent big data discriminatory pricing.In the fourth part, the thesis puts forward the specific ways to regulate the big data discriminatory pricing behavior from different angles. Relevant legislation must be promoted to avoid legal competition and convergence, break the information asymmetry between platforms and users, and protect citizens' personal information and consumers' right to know. The unified supervision subject should be established, and the algorithm power should be effectively restricted and supervised by the public power of the state. It is necessary to give full play to the functions of Internet courts, reasonably distribute the burden of proof, smooth the channels for consumers to complain, and clear the way for consumers to protect their rights. The Internet industry should establish corresponding industry self-discipline standards, regulate the automation of algorithm decision-making, and follow laws and regulations and artificial intelligence ethics. Consumers themselves should also enhance their awareness of rights protection and actively prevent big data discriminatory pricing behavior.
  • dc.date.issued
  • 2022-03-16
  • dc.date.oralDefense
  • 2022-06-05
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