生成式AI内容使用者的专利犯罪风险与刑法规制
Criminal Risks of Patent Infringement by Users of Generative AI Content and Criminal Law Regulation
摘要: 随着人工智能生成技术以及算法和大模型的更新迭代,人工智能生成软件(以下称AI软件)进入大众的生活,尤其是在工作中提供便利且可直接适用的方案、实验数据等。使用者信赖AI生成的内容,若直接使用于商业活动中,可能面临侵犯他人专利权内容产生的刑事法律风险。在AI的使用中就出现了AI的无心之失和使用者的有意之罪,传统专利法以及《刑法》第216条假冒专利罪,在应对目前隐蔽性高、极可能引发大规模侵权的新型风险可能存在处罚漏洞。本文通过分析AI内容使用者的行为模式和主观认识,论证如存在间接故意或重大监督过失,并造成严重后果的刑事可罚性进行探讨,以比较法学经验的路径提出针对这一新型风险的审慎刑法规制路径。
Abstract: With the iterative upgrading of artificial intelligence generation technology, algorithms and large models, artificial intelligence generation software (hereinafter referred to as AI software) has stepped into people’s daily lives, and in particular, it provides readily usable solutions, experimental data and other materials to facilitate work. When users trust and directly apply AI-generated content to commercial activities, they may face criminal legal risks arising from the infringement of others’ patent rights contained in such content. The use of AI has thus given rise to inadvertent errors made by AI itself and intentional crimes committed by its users. Traditional patent law, as well as the crime of patent counterfeiting stipulated in Article 216 of the Criminal Law, may have punishment loopholes in addressing such new risks that are highly concealed and likely to trigger large-scale infringements. By analyzing the behavioral patterns and subjective cognition of users of AI-generated content, this paper demonstrates the criminal punishability of such users when they act with indirect intent or gross supervisory negligence and cause serious consequences, and puts forward a prudent criminal law regulation path for this new type of risk by drawing on the experience of comparative law.
文章引用:李睿思. 生成式AI内容使用者的专利犯罪风险与刑法规制[J]. 交叉科学快报, 2026, 10(2): 470-477. https://doi.org/10.12677/isl.2026.102059

参考文献

[1] 向婷, 唐卓, 郑佳丽, 等. 基于生成模型的图像数据增强方法综述[J/OL]. 图学学报, 1-16.
https://link.cnki.net/urlid/10.1034.T.20251210.1545.002, 2025-12-12.
[2] Deng, J., Dong, W., Socher, R., Li, L., Kai Li, and Li, F.-F. (2009) ImageNet: A Large-Scale Hierarchical Image Database. 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, 20-25 June 2009, 248-255. [Google Scholar] [CrossRef
[3] 贺志军. 刑法中的“假冒他人专利”新释[J]. 法商研究, 2019, 36(6): 64-75.
[4] 储槐植, 唐风玉. 刑事一体化视域中专利权保护问题研究[J]. 河北法学, 2023, 41(9): 2-18.
[5] 欧超荣. 刑法“间接故意”重要争论问题的研究——评《刑法中的间接故意研究》[J]. 社会科学家, 2021(4): 172.
[6] 郑鹰, 张欣亮, 张雪飞. 生成式人工智能国内外标准化发展状况、面临挑战及对策研究[J/OL]. 标准科学, 1-6.
https://link.cnki.net/urlid/11.5811.T.20251215.0916.014, 2025-12-16.
[7] 纪林菲. 专利刑事保护的挑战与应对[J]. 河南科技, 2025, 52(1): 112-115.
[8] 杜昕越. 专利权行政保护与司法保护的衔接机制研究[D]: [硕士学位论文]. 长春: 吉林大学, 2025.
[9] 王悦玥, 马忠法. 论“假冒专利”的立法缺陷及其修正[J]. 北京理工大学学报(社会科学版), 2025, 27(4): 93-104.