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Title: | 論人工智慧相關發明與專利充分揭露要件 Discuss the AI-related Inventions and Sufficiency of disclosure in Patent Law |
Authors: | 吳玉珍 Wu, Yu-Zhen |
Contributors: | 沈宗倫 吳玉珍 Wu, Yu-Zhen |
Keywords: | 專利法 人工智慧 電腦軟體相關專利 據以實現 充分揭露 Patent law Artificial Intelligence Computer software-related patents Enablement Sufficiency of disclosure |
Date: | 2024 |
Issue Date: | 2024-09-04 14:51:37 (UTC+8) |
Abstract: | 近年來人工智慧之發展興盛,在日常生活及產業界都漸漸佔有一席之地,各國對於人工智慧也日趨重視,紛紛提出相關的重要策略及發展計畫,人工智慧及相關法律研究也成為世界關注議題,其中人工智慧專利之數量大幅提升,相關專利申請成長速率可觀。 自專利制度充分揭露要件觀察,係藉由專利發明資訊之揭露,使從事相關技術領域之人得以了解發明創作內容,避免重複投入資源,並且讓發明專利成為未來創新基石,提升相關技術領域產業水準,貢獻產業發展,實具有公益之性質,故本文將先討論各國充分揭露要件重點、審查基準及實務案例。 而人工智慧的本質是由演算法而生,其發展歷程亦與技術特性相關,透過人工智慧發展情形及技術演進,將能更了解人工智慧於專利制度上所遭遇之難題;又人工智慧自演算法出發並透過電腦軟體程式所建構,因此人工智慧相關發明通常以電腦軟體或電腦實現發明觀點進行審查,人工智慧相關發明實與電腦軟體發明具有密切關聯,從各國實務觀察,普遍將人工智慧相關發明列入電腦實施發明之子類別,因此電腦軟體發明實務審查之發展亦為了解人工智慧相關發明審查之重點。 另外,對於人工智慧相關發明目前各國審查基準之調整以及案例之發展,也具有細微之不同,本文將聚焦於人工智慧相關發明實務上針對充分揭露要件之討論及相關判決作為重點研究內容,最後探討人工智慧專利在充分揭露要件上可能之解決方案及挑戰。 In recent years, the development and prosperity of AI have gradually occupied a place in daily life and industry. Many countries have also paid increasing attention to AI and proposed essential strategies and development plans. AI and AI-related legal research have also become issues of concern worldwide. The number of AI-related patents has increased significantly, and the growth rate of AI-related patent applications is considerable. From the perspective of the disclosure requirement of patent law, a patent application discloses a claimed invention in sufficient detail so that the person skilled in the art can carry out that claimed invention. It will help avoid duplication of effort, make patents fundamental to innovation, raise the industrial and technical level to drive industry development and serve the public good. Therefore, this paper will first discuss the critical points of sufficiency of disclosure and consider how to examine the requirements and practices in various countries. AI is a set of algorithms, and its development process is also related to technical characteristics. We can better understand the difficulties AI-related applications encounter in the patent law system through the evolution of AI technology. In addition, AI starts from algorithms and constructs through software programs. Therefore, AI-related inventions are usually examined from the perspective of computer software or computer-implemented inventions. AI-related inventions are closely related to computer software inventions. From practical observations in various countries, AI-related inventions are generally included in the subcategory of computer-implemented inventions. Therefore, the development of a practical review of computer software invention applications is also the focus of understanding the examination of AI-related invention applications. In addition, there are subtle differences in the current adjustment of examination standards and the development of cases in various countries for AI-related inventions. We will focus on discussing disclosure requirements and related judgments in the practice of AI-related inventions as the main point of this paper. Finally, we will discuss the possible solutions and challenges in the sufficiency of disclosure for AI-related patents. |
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E/SCP/30/5(2019). 10.SCP, Study on the sufficiency of disclosure, E/SCP/22/4(2015). 11.United States Patent and Trademark Office, 2019 Revised Patent Subject Matter Eligibility Guidance, 84 FR 50 (2019). 12.United States Patent and Trademark Office, Examining Computer-Implemented Functional Claim Limitations for Compliance With 35 U.S.C. 112, 84 FR 57 (2019). 13.United States Patent and Trademark Office, Inventing AI: Tracing the diffusion of artificial intelligence with US patents (2020) , available at https://www.uspto.gov/sites/default/files/documents/OCE-DH-AI.pdf (Last visited: 2024/07/21). 14.United States Patent and Trademark Office, Inventorship Guidance for AI-Assisted Inventions (2024), available at https://www.federalregister.gov/documents/2024/02/13/2024-02623/inventorship-guidance-for-ai-assisted-inventions (Last visited: 2024/07/21). 15.United States Patent and Trademark Office, Manual of Patent Examining Procedure (Feb. 2023), available at https://www.uspto.gov/web/offices/pac/mpep/index.html (Last visited: 2024/07/21). 16.United States Patent and Trademark Office, Patent eligible subject matter: Public views on the current jurisprudence in the United States (2022), available at https://www.uspto.gov/sites/default/files/documents/USPTO-SubjectMatterEligibility-PublicViews.pdf (Last visited: 2024/07/21). 17.United States Patent and Trademark Office, Public Views on Artificial Intelligence and Intellectual Property Policy (2020), available at https://www.uspto.gov/sites/default/files/documents/USPTO_AI-Report_2020-10-07.pdf (Last visited: 2024/07/21). 18.World Intellectual Property Organization, Getting the Innovation Ecosystem Ready for AI: An IP policy toolkit, GENEVA: WORLD INTELLECTUAL PROPERTY ORGANIZATION (2024), available at https://www.wipo.int/publications/en/details.jsp?id=4711 (Last visited: 2024/07/21). 19.World Intellectual Property Organization, Patent Landscape Report - Generative Artificial Intelligence (GenAI) , GENEVA: WORLD INTELLECTUAL PROPERTY ORGANIZATION (2024), available at https://www.wipo.int/web-publications/patent-landscape-report-generative-artificial-intelligence-genai/assets/62504/Generative%20AI%20-%20PLR%20EN_WEB2.pdf (Last visited: 2024/07/21). 20.World Intellectual Property Organization, WIPO technology trends 2019: Artificial intelligence, GENEVA: WORLD INTELLECTUAL PROPERTY ORGANIZATION (2019), available at https://www.wipo.int/edocs/pubdocs/en/wipo_pub_1055.pdf (Last visited: 2024/07/21). 21.World Intellectual Property Organization, World Intellectual Property Report 2022 - The Direction of Innovation, GENEVA: WORLD INTELLECTUAL PROPERTY ORGANIZATION (2022), available at https://www.wipo.int/edocs/pubdocs/en/wipo-pub-944-2022-en-world-intellectual-property-report-2022.pdf (Last visited: 2024/07/21). 22.World Intellectual Property Organization, World Intellectual Property Report 2024- Making Innovation Policy Work for Development, GENEVA: WORLD INTELLECTUAL PROPERTY ORGANIZATION (2024), available at https://www.wipo.int/edocs/pubdocs/en/wipo-pub-944-2024-en-world-intellectual-property-report-2024.pdf (Last visited: 2024/07/21). VII.Doctoral Dissertations and Master’s Theses 1.Paul Werbos, Beyond regression: New tools for prediction and analysis in the behavioral sciences, PHD THESIS, COMMITTEE ON APPLIED MATHEMATICS, HARVARD UNIVERSITY, CAMBRIDGE, MA (1974). VIII.Internet Source 1.Automatic Language Processing Advisory Committee, Language and Machines: Computers in Translation and Linguistics (1966). 2.Daniel Zhang, et al., Artificial Intelligence Index Report 2022 (2022) , available at https://aiindex.stanford.edu/wp-content/uploads/2022/03/2022-AI-Index-Report_Master.pdf (Last visited: 2024/07/21). 3.Dario Amodei, Danny Hernandez, AI and compute (2018), available at https://openai.com/research/ai-and-compute (Last visited: 2024/07/21). 4.ImageNet Large Scale Visual Recognition Challenge (ILSVRC), available at https://www.image-net.org/challenges/LSVRC/ (Last visited: 2024/07/21). 5.IP5, Examination practices on AI-related inventions (2023), available at https://www.jpo.go.jp/news/kokusai/ip5/document/gochou_ai/chart.pdf (Last visited: 2024/07/21). 6.IP5, IP5 NET/AI roadmap (2021), available at https://link.epo.org/ip5/IP5_NET_AI_roadmap_FIN.pdf (Last visited: 2024/07/21). 7.IP5, IP5 NET/AI Task Force Scoping document (2020), available at https://link.epo.org/ip5/IP5+NET_AI+TF+scoping+document.pdf (Last visited: 2024/07/21). 8.James Lighthill, Artificial intelligence: A general survey (Science Research Council London 1973). 9.JavaTpoint, Deep learning vs. Machine learning vs. Artificial Intelligence, available at https://www.javatpoint.com/deep-learning-vs-machine-learning-vs-artificial-intelligence (Last visited: 2024/07/21). 10.Joe Osborne, Google’s tensor processing unit explained: this is what the future of computing looks like, 6 TECHRADAR (2017),available at https://www.techradar.com/news/computing-components/processors/google-s-tensor-processing-unit-explained-this-is-what-the-future-of-computing-looks-like-1326915 (Last visited: 2024/07/21). 11.Michael Chui, et al., The economic potential of generative AI, (2023), available at https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier (Last visited: 2024/07/21). 12.Michael Chui, et al., The state of AI in 2022—and a half decade in review (2022), available at https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review (Last visited: 2024/07/21). 13.Michael Chui, et al., The state of AI in 2023: Generative AI’s breakout year (2023), available at https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year (Last visited: 2024/07/21). 14.Patrick Heckeler, Software patent applications: How the EPO examines innovative software, available at https://www.bardehle.com/europeansoftwarepatents/software-patent-epo/ (Last Visited 2024/07/21). 15.Ray Perrault & Jack Clark, Artificial Intelligence Index Report 2024 (2024), available at https://aiindex.stanford.edu/wp-content/uploads/2024/05/HAI_AI-Index-Report-2024.pdf (Last visited: 2024/07/21). 16. United States Patent and Trademark Office, AI-related resources, available at https://www.uspto.gov/initiatives/artificial-intelligence/artificial-intelligence-resources (Last visited: 2024/07/21). 17.What is the ACL and what is Computational Linguistics?, available at https://www.aclweb.org/portal/what-is-cl (Last visited: 2024/07/21). 18.World Economic Forum, Future of jobs report 2023 (2023), available at https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf (Last visited: 2024/07/21). 19.Young Global Leaders, World Economic Forum Annual Meeting 2016 : Mastering The Fourth Industrial Revolution(2016), available at https://www.weforum.org/publications/world-economic-forum-annual-meeting-2016-mastering-the-fourth-industrial-revolution/ (Last visited: 2024/07/21). 20.浅川直輝,ChatGPTの登場「AI進化の分岐点に」ソニーG北野CTO,日本経済新聞,2023年2月16日,https://www.nikkei.com/article/DGXZQOUC139810T10C23A2000000/ (最後檢視時間:2024/07/21)。 |
Description: | 碩士 國立政治大學 法律科際整合研究所 107652022 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0107652022 |
Data Type: | thesis |
Appears in Collections: | [法律科際整合研究所] 學位論文
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