首页|论生成式人工智能使用在先作品的版权困境与纾解路径

论生成式人工智能使用在先作品的版权困境与纾解路径

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生成式人工智能常态化爬取海量在先作品诱发侵权风险,长距离文本语义理解意欲掩盖侵权痕迹,开放式的跨域泛化推理为实施侵权提供技术便利.在作品数据投喂方面,生成式人工智能逾越合理使用制度的边界,或将使在先作品走向无保护或过度保护的极端;在生成内容可版权性方面,生成式人工智能凭借其生成内容的"广度"与"厚度"解耦著作权主体性,挑战现有独创性标准.重释适当引用制度和建立使用在先作品背书机制,应对合理使用制度适用难题;推动"作者中心主义"向"作品中心主义"横向过渡,使以人格权为出发点向财产权转向;建立基于可解释性的生成式人工智能独创性评估机制,重释独创性标准.
Research on the Copyright Dilemma and Solution Path of Generative Artificial Intelligence Using Previous Works
The rapidly development and embedded applications of generative artificial intelligence pose challenges to the existing copyright system.Generative artificial intelligence normalizes the crawling of mas-sive amounts of prior work data,inducing infringement risks.Long distance text semantic understanding abil-ity is intended to cover up infringement traces,and open cross domain generalization reasoning ability pro-vides technical convenience for infringement.In terms of data feeding in works,generative artificial intelli-gence may cross the boundaries of fair use systems or lead to the extreme of unprotected or overprotected rights in previous works;In terms of copyright-ability of generated content,generative artificial intelligence decouples copyright subjectivity with its high-quality and massive generation ability,meeting the"minimum creative standards"and originality requirements.Propose to establish an endorsement system for the use of prior works to address the problem of rational use of algorithms;Promote the horizontal transition from"au-thor centrism"to"work centrism",and shift the authors rights law starting from personality rights to copy-right law starting from property rights;Establish an interpretable generative artificial intelligence originality evaluation mechanism and reinterpret originality standards.

Generative artificial intelligencePrior work dataCopyrightabilitySubjectivityOriginalityEndorsement mechanism

刘祖兵

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同济大学法学院互联网与人工智能法律研究中心,上海,200092

生成式人工智能 在先作品 可版权性 主体性 独创性 背书机制

教育部人文社科规划基金项目上海市2022年度软科学研究项目

21YJA82003222692104400

2024

信息资源管理学报
中国高校科技期刊研究会,武汉大学

信息资源管理学报

CSSCICHSSCD
影响因子:0.885
ISSN:2095-2171
年,卷(期):2024.14(5)