A Research Of Privacy Theory Based On Relational Autonomy

Under the contemporary background of big data technology,different individual data reflect a high degree of correlation at the genetic level.At the same time,mining and summarizing data will form the group with certain characteristics.For this reason,individuals with similar genetic information and individuals with similar characteristics in a group gradually began to have related privacy interests.Accordingly,the close relationship between individual identity and privacy has been broken.Additionally,the privacy of big data is inevitably faced with problems such as the difficulty of distinguishing between public and private spheres,and the more intense conflict between public interests and personal interests.In this context,the traditional privacy theory has been unable to solve the above-mentioned series of difficulties.Therefore,it is extremely urgent to develop a new privacy theory.Based on the foregoing background,the main contents of this research are as follows:In general,based on individual autonomy,the traditional privacy theory emphasizes that the rational self is the self separated from others and protects privacy through the separation of individual and society.In the era of big data,individuals are in various relationships with any place at any time.In view of the lack of consideration of individual social relations in the theory of individual autonomy,it is difficult to grasp the essence of autonomy in big data networks.By comparison,the redefinition of autonomy by feminist relational autonomy theory can obviously provide richer connotation than traditional individual autonomy theory,and then provide a brand-new foundation for big data privacy theory.On the basis of analyzing and summarizing the theory of relational autonomy,this research reconstructs the theoretical connotation of relational autonomy,and its main contents are as follows.To be specific,first of all,self is the fusion of social factors.Secondly,autonomy can only be realized under the condition of social support.In the last,the improvement of autonomy requires the joint participation of individuals and society.Thus,the theory of relational autonomy emphasizes the formation of individual identity in the context of social relations.In other words,only under the condition of social support can individuals achieve autonomy properly,which is not only consistent with the current situation that individual privacy interests are related to each other under big data technology,but also more suitable for explaining individual autonomy under the background of big data technology.Therefore,it is necessary and feasible to construct the privacy theory of big data based on relational autonomy.In theory,the big data privacy is defined as respecting the right of individuals to realize relationship autonomy,and its main theoretical framework includes a range of factors including privacy protection content and value orientation and protection ways as well as protection countermeasures.To be specific,first of all,relational autonomy argues that self is reflected through self-reflection and social interaction.Consequently,the self that big data privacy is dedicated to protect should also be rooted in the corresponding social environment and the self that is constantly being reshaped in social participation.In addition to the personal identity of individual,the protection of big data privacy has been extended to the individual's social identity.Secondly,considering that privacy under the big data technology constitutes and protects the social relations for individuals to realize autonomy,it has significant social value.Moreover,the realization of big data privacy protection needs the participation of individuals and society,which mainly includes promoting the development of individual autonomy and building the supportive social environment.In the last,in combination with the data life cycle theory,privacy protection countermeasures include adjusting the data processing scope in the pre-processing stage,restricting data analysis activities in the processing stage,and strengthening social supervision responsibilities in the post-processing stage.Compared with the privacy theory of individual autonomy,the privacy theory based on relational autonomy extends the content of privacy protection to individual social identity,which not only provides protection basis for personal information in public sphere and privacy interests in group dimension,but also effectively broadens the boundary of privacy protection content.At the same time,the privacy theory based on relational autonomy introduces the redefinition of autonomy into the theoretical framework,which makes it closer to the understanding of the essence of individual autonomy under big data technology and more suitable for reflecting respect for individual autonomy in the era of big data.In addition,the privacy theory based on relational autonomy can effectively promote the cross-cultural communication between eastern and western privacy theories.For this reason,it can realize privacy protection in Chinese context in a more ideal way.On the other hand,big data privacy must respond to the practical issues of privacy protection,instead of simply as a purely theoretical issue.For example,due to the prominent privacy interests of the group dimension in the field of medical big data,and the sharp conflict between data development value and personal privacy rights,individuals in the medical environment need the respect related to their relationship autonomy more urgently.Therefore,taking the field of medical big data as an example,this research launches the corresponding exploration.Specifically,first of all,on the premise of adopting the informed consent model based on relational autonomy,this research emphasizes that the decision-making of informed consent should be based on the social relations and social environment in which individuals are placed.Secondly,the privacy theory of relational autonomy provides a theoretical basis for protecting the privacy interests of medical big data groups.Therefore,this research suggests that the privacy interests of the group can be effectively protected by a series of measures,including the supervision of the use stage of big data and the prediction of possible risks.