A Research On The Legal Regulation Of Automated Decision-making In China Based On Article 24 Of The Personal Information Protection Law

With the continuous progress of modern science and technology,the world has entered the era of big data,algorithms and artificial intelligence.Automated decision-making has been widely used in various fields with the rapid development.It can recommend the topics people might be interest in when they browse news,recommend the goods they need when it comes to shopping.The government uses it for administrative management,and even the judicial department use it to assist in decision making.Automatic decision-making is widely favored for its advantages such as saving time and improving work efficiency,which is deeply embedded in society.Meanwhile,a series of legal risks such as the risk of discrimination,the risk of privacy and the risk of loss of subjectivity brought by it are also increasingly valued by people.How to ensure the rationality,legitimacy and fairness of automated decision-making through legal regulation and reduce the risks of automated decision-making in various fields should become the focus of academic attention.This not only requires an in-depth analysis of the real harm caused by automated decision-making,but also needs to actively explore the expansion of algorithmic regulation to deal with the violation of algorithmic automated decision-making while drawing on the effective experience of artificial intelligence governance in Europe and the United States.Based on the article 24 of Personal Information Protection Law,this paper analyzes the risks brought by automation decision-making,combs the legal regulation system of automation decision-making,compares and analyzes the related regulation thoughts of Europe and the United States,and puts forward the related improvement path of law regulation of automation decision-making.This thesis consists of five chapters:Chapter 1 is the introduction,which mainly expounds the research background of the thesis.Big data and artificial intelligence are deeply integrated,reconstructing our survival,production and life-style at an unprecedented speed,and more and more fields begin to apply automated decision-making.Effective regulation of algorithmic automated decision-making can largely respond to the challenges of AI and guide AI to progress on the right track.The current research includes three perspectives:research on basic theory,research on regulation of specific violations,and research on general regulation paths.In the writing process,the author comprehensively adopts the case analysis methodology and the comparative analysis methodology.Chapter 2 provides an overview of automated decision-making.Clarifying the concept of automated decision-making in China is automatically analyzes and evaluates the various conditions of the data subject through computer algorithms based on user portraits,and then replaces or assists their decision-making process.Among them,an algorithm is a method by which people make a computer perform certain tasks automatically by writing programs and data input.The automated decision-making discussed in this thesis is based on the use of personal information,and identifiability is the most critical criterion for distinguishing personal information from non-personal information.Automated decision-making has the characteristics of limited autonomy,black-box,and difficult attribution,which leads to its infringement of personal privacy,boosts the risk of discrimination,and generates algorithmic power that hinders free will,which is the starting point for its regulation.Chapter 3 is an analysis of the legal regulation mode and path of automated decision-making.Under the concept of human rights,it is found that the European Union adopts a unified legislative model,which regulates by setting general prohibitions and exceptions to the prohibition path allowed for automated decision-making,and setting up the right of algorithmic interpretation as a remedy.Under the concept of freedom,the United States adopts a decentralized legislative model,uses scenario-oriented theory to give full play to the advantages of collaborative governance,and builds a more systematic regulatory system.At present,the legal provisions regulating automatic decision-making in China are scattered in legal norms in different fields,while the Personal Information Protection Law adopts a governance model different from the EU’s rights path,trying to strike a balance between personal information protection and promoting the development of the digital industry.Although the EU has limitations such as difficult implementation and high cost,the United States also has problems such as high compliance costs and complex coordination between laws,and its useful experience is still worth learning from.Chapter 4 specifically and systematically argues the main content and problems of automated decision-making legal regulation in China.As the core legislation in the field of personal information protection,Article 24 of the Personal Information Protection Law sets a special clause on automated decision-making.This thesis takes this article as the core,and systematically analyzes in depth that the legal regulation of automated decision-making is based on the empowerment mechanism in China.By establishing the principles of transparency,fairness and reasonableness,to exercise the right to be informed and the right to fair dealing.Guarantee the right of choice or refusal by requiring non-personal options or a convenient method of refusal.By granting the right to explain the request and the right to refuse to provide relief,a relatively complete regulatory system has been formed.However,there are still problems in this regulatory system.For example,the individual empowerment model cannot solve the functional problem of automated decision-making,the supporting exercise mechanism is lacking,and the algorithm interpretation power is controversial,which needs further discussion and improvement.Chapter 5 proposes improvement paths.At first,solve the dilemma of the individual empowerment model through scenario-based governance,improve the algorithm classification system and the algorithm impact assessment system under the leadership of the government.Then,improve the legal guarantee system by refining legal provisions,promulgating lower-level laws or judicial interpretations.At last,explicitly set the right of algorithm interpretation as the final barrier for individuals to seek relief.