On the Determination of Copyright Infringement in Machine Learning:Beyond the Non-Expressive Use Theory
Regarding the difficult issue of determining copyright infringement in the machine learning of artificial intelligence(AI),the theory of the non-expressive use which has recently attracted significant attention delineates the infringement liability based on the method of categorizing machine learning into"expressive one"and"non-expressive one",and advocates for prohibiting AI from imitating the personal creative style of specific authors.However,the teleological interpretation,historical interpretation and case-based analysis of the reproduction right reveal that the theory of non-expressive use fails to overcome the long-standing misconception that"carrying out the reproduction equals infringement",facing three-faceted predicaments at the logical,jurisprudential,and practical levels.Thus,it is necessary to critically assimilate the theory of non-expressive use,re-establish a new standard for determining copyright infringement in machine learning,replace the formalistic notion of"carrying out reproduction equals infringement"with the high probability of public access to the expression of the original work.
Machine LearningArtificial IntelligenceInfringement DeterminationNon-expressive UseHigh Probability
万方数据
维普
