大数据时代人脸识别信息侵权构成的二元解释论——基于人脸识别信息二元属性的分析

Binary Interpretation of Face Recognition Information Infringement in the Era of Big Data:Based on the Analysis on Binary Attributes of Face Recognition Information

当下,实务界对人脸识别信息法律属性的误解,导致了对人脸识别信息侵权构成要件的片面解读。大数据时代“隐私信息化”成为新形态,使得人脸识别信息在不同场景呈现出个人隐私或个人信息的属性。根据人脸识别技术的应用目的将人脸识别信息的使用场景分为“对比”“分析”“识别验证”三类,在“分析”“识别验证”场景中,其个人隐私属性较强,此时加害行为表现为侵害隐私,采纳过错推定的归责原则,损害后果不限于下游损失,因果关系采用“条件说”与“相当因果关系说”结合的判断方法;在“对比”场景中,其个人信息属性较强,此时加害行为表现为侵害个人信息权益,归责原则与因果关系的判断方法同上,但损害后果仅限于下游损失。

At present,misunderstanding from the practice community on the legal nature of face recognition information result in a one-sided interpretation of the face recognition information infringement components.In the era of big data,“information-orientated privacy”has become a new form,which makes face recognition information show the attributes of personal privacy or personal information in different scenes.According to the application purpose of face recognition technology,the use scenarios of face recognition information can be divided into three categories:“contrast”,“analysis”and“recognition verification”.In the scenario of“analysis”and“identification and verification”,the personal privacy attribute is strong,in which the harm behavior is manifested as privacy infringement,the imputation principle of fault presumption is adopted,and the damage consequences are not limited to downstream losses,and the causality is judged by the combination of"conditional theory"and“considerable causality theory”.In the“contrast”scenario,the personal information attribute is strong,in which the harm behavior is manifested as infringement of personal information rights and interests,and the imputation principle and the judgment method of causality are the same as above,however the damage consequences are limited to the downstream losses.