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作 者:丁晓东[1] Ding Xiaodong
机构地区:[1]中国人民大学法学院
出 处:《东方法学》2025年第1期75-89,共15页Oriental Law
基 金:国家社科基金重大项目“当代中国数字法学基本范畴体系研究”(项目批准号:23&ZD154)的阶段性研究成果。
摘 要:知情状态在平台间接侵权中被赋予重要地位,共同侵权制度中的过错判断与避风港制度中的通知都与知情状态密切相关。但以知情状态判断平台过错与责任,只适合分析平台平等参与特定个案的侵权。在此类侵权中,可以分析平台在个案中是否“知道”或“应知”,是否存在过错和尽到合理注意义务。而典型的平台间接侵权是大规模治理下所产生的问题,其“知道”“应知”或注意义务应当以是否具有整体性治理过错为依据,其判断因素包括危害性与治理必要性、治理可能危及的合法性活动、平台辨识合法与非法活动的难度、直接侵权制度是否更有效等。从典型平台间接侵权的大规模治理型侵权特征出发,可以对传统共同侵权与避风港制度进行协调,通过分领域和案例积累而破解算法推荐等场景下知情分析的不确定性,同时消除平台“不做不错”“做多错多”的悖论。The state of knowledge plays an important role in platform indirect infringement,for the fault determination in joint infringement and notice in the safe harbor mechanism both are closely related to knowledge. However, using the state of knowledge to determine platform's fault and responsibility is only suitable for analyzing cases where platforms equally participate in specific instances of infringement. In this type of infringement, it is possible to analyze whether the platform "knew" or "should have known" in the individual case, whether it was at fault and whether it exercised reasonable care. However, a typical example of platform indirect infringement arises in large-scale governance contexts, where the judgment of "knowing", "ought to know", or due diligence should be based on whether there is an overall fault of governance. Factors for this judgment include the potential harm and governance necessity, legality of activities that governance could endanger, difficulty for platforms to distinguish between legal and illegal activities, and whether direct infringement regimes are more effective. Starting from the characteristics of large-scale governance-induced infringement of the typical platform indirect infringement, it is possible to coordinate traditional joint infringement with safe harbor mechanism. The uncertainties in analyzing the state of knowledge in scenarios such as algorithmic recommendations can be resolved by subdividing the field and accumulating cases, while eliminating the paradox of platforms that "do nothing for nothing wrong" or "do more for more mistakes".
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