Criminal Risks And Regulation Of Deep Fake Technology Alienatio

Deep-fake is a typical product of Artificial Intelligence.With the widespread use of deep learning in the field of image,audio and video generation,deep-fake can automatically learn and analyze data from massive amounts of big data,and imitate data characteristics to generate false image information.However,there are still obvious traces of tampering in the output at this stage.The initial intention of creating deep-fake is to realize its positive value.However,in the process of its integration with economic and social fields to achieve large-scale commercialization,its negative influences inevitably appear.The issues of bio-security,network security and national security brought about by deep-fake have aroused widespread discussion and attention from all walks of life.The first chapter is “the operation principle and application scenarios of deep-fake”.Thanks to the progress and application of deep learning algorithms,especially generative adversarial network algorithms,compared with the traditional digital content forgery and tampering technology,the effect of deep-fake technology is more realistic,and the traces of tampering is more difficult to detect,which will bring greater threats to the overall security system of individuals,society and even countries.Criminal law should do something to address the criminal risks associated with the alienation of this technology.The second chapter is “the typed development of the alienating criminal risk of deep-fake”.Technology is a double-edged sword.While promoting human progress,it always brings new types of risks,making human beings uneasy.We should analyze the phenomenon and nature of new technology alienation,explore the relationship between the alienation of deep-fake and criminal risks,and conduct a typological analysis of risks contained in it.From the perspective of application form,“face replacement” and “face reproduction” deep-fake are based on personal biometric features as the technical core,and its essence is the abuse of false information.“Face synthesis” and “voice forgery” deep-fake do not involve personal biometric information.They use deep learning technology to create virtual facial images and virtual voices that do not exist in real life.The essence of their behavior is the the“extension” of the developer or the user’s behavior,realizing the will of the developer or user.The third chapter is “the legal basis of deep-fake alienation criminal risk regulation”.There must be good reasons for the intervention of criminal law to regulate deeply forged technologies.This article further examines the current status and inadequacy of the criminal law on the risk of deep-fake alienation.The article points out that the necessity of the criminal regulation of the alienation of deep-fake lies in the various criminal risks caused by the illegal act to bio-informatics security,citizens’ property interests,national security,etc..The legitimacy lies in the fact that this technology has brought about major changes in the way images,audio and video are synthesized,so that high-quality audio and video image tampering and counterfeiting technology has gradually become a “low threshold” skill.Besides,the current non-criminal regulatory means in China are difficult to effectively resist the alienation hazards of deep-fake alienation.The feasibility lies in the fact that China’s domestic criminal law already has a relatively perfect regulatory basis to deal with the harm of the alienation of deep-fake.In terms of sanction logic,“front-end sanctions based on personal information”,“end sanctions based on legal consequence” and“supplementary paths based on responsible subjects” are formed.The fourth chapter is “the difficult solution of deep forgery technology alienation criminal risk regulation”.Fist,the different answers to the question whether the risk of technological alienation infringes a new type of legal interest form the opposition between the path of legislative criminalization governance and the path of interpretive governance.Second,whether to exclude the black numbers automatically generated by the algorithm? The algorithm black number generated automatically by the artificial intelligence algorithm brings two problems.Third,the lack of criminal law regulation of deep-fake,that is,the regulation of the abuse of personal biometric information.While our country’s criminal regulatory system for personal information crimes is constantly improving,there has been a paradoxical dilemma of increasing infringement of personal biometric information.There are two reasons for this.One is because the regulation of personal biometric information relies on the protection of personal information rights.The other is due to the lack of criminal regulations for the abuse of personal biometric information in this era.The way out for criminal law in response to the risk of it should be based on the regulation of personal biometric information abuse.Based on “personal biometric information”,a criminal regulation system for deep-fake alienation risks should be constructed.We should separate the criminal protection norms of personal biometric information from the “crime of infringing on citizens’ personal information”.At the same time,the act of “abusing personal biometric information” should be added to the “crime of infringing on personal biometric information”,forming a relatively complete protection system for the entire process of personal biometric information from ‘illegal acquisition’(including theft),‘provision’(including sale)to ‘misuse’ of information.The allocation of penalties for the crime is as important as the establishment of the crime,directly related to the ultimate realization of the legal protection of personal biometric information.In the stage of crime establishment,it is mainly for crimes in the future,and retribution should be the main focus,and prevention the supplement.The allocation of penalties for this crime should follow the principle of balance of crime,responsibility and punishment.To this end,that the nature and severity of the punishment allocated to this crime is compatible with the nature of the crime and the degree of harm to society should be guaranteed.That the balance of the penalty allocation between the “crime of infringing on citizens’ personal information” and the“crime of infringing on personal biometric information” should be guaranteed.