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題名 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作者 吳玉珍
Wu, Yu-Zhen貢獻者 沈宗倫
吳玉珍
Wu, Yu-Zhen關鍵詞 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日期 2024 上傳時間 4-九月-2024 14:51:37 (UTC+8) 摘要 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. 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VI.Reports or Official Documents 1.European Patent Office & Japan Patent Office, Comparative Study On Computer Implemented Inventions/Software Related Inventions Report 2021 EPO & JPO(2020), available at https://www.jpo.go.jp/news/kokusai/epo/document/software_201903/01_en.pdf (Last visited: 2024/07/21). 2.European Patent Office, Case Law of the Boards of Appeal, 10 edition 2022, available at https://link.epo.org/web/case_law_of_the_boards_of_appeal_2022_en.pdf (Last visited: 2024/07/21). 3.European Patent Office, Guidelines for Examination in the European Patent Office (March 2024), available at https://link.epo.org/web/legal/guidelines-epc/en-epc-guidelines-2024-hyperlinked.pdf (Last visited: 2024/07/21). 4.European Patent Office, Patenting artificial intelligence: Conference summary (European Patent Office Munich 2018), available at https://e-courses.epo.org/pluginfile.php/23523/mod_resource/content/2/Summary%20Artificial%20Intelligence%20Conference.pdf (Last visited: 2024/07/21). 5.European Patent Office, Report of the IP5 expert round table on artificial intelligence (2018), available at https://link.epo.org/ip5/IP5+roundtable+on+AI_report_22052019.pdf (Last visited: 2024/07/21). 6.Japan Patent Office & China National Intellectual Property Administration, Comparative Study On AI-Related Inventions Report 2023 JPO and CNIPA (2024), available at https://www.jpo.go.jp/e/news/kokusai/cn/ai_report_2023_e.html (Last visited: 2024/07/21). 7.Japan Patent Office, Examination Handbook for Patent and Utility Model in Japan, March 2024. 8.Japan Patent Office, Recent Trends in AI-related Inventions (2023), available at https://www.jpo.go.jp/e/system/patent/gaiyo/ai/document/ai_shutsugan_chosa/report.pdf (Last visited: 2024/07/21). 9.SCP, Background Document on Patents and Emerging Technologies, U.N. Doc. 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)。 描述 碩士
國立政治大學
法律科際整合研究所
107652022資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107652022 資料類型 thesis dc.contributor.advisor 沈宗倫 zh_TW dc.contributor.author (作者) 吳玉珍 zh_TW dc.contributor.author (作者) Wu, Yu-Zhen en_US dc.creator (作者) 吳玉珍 zh_TW dc.creator (作者) Wu, Yu-Zhen en_US dc.date (日期) 2024 en_US dc.date.accessioned 4-九月-2024 14:51:37 (UTC+8) - dc.date.available 4-九月-2024 14:51:37 (UTC+8) - dc.date.issued (上傳時間) 4-九月-2024 14:51:37 (UTC+8) - dc.identifier (其他 識別碼) G0107652022 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/153347 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 法律科際整合研究所 zh_TW dc.description (描述) 107652022 zh_TW dc.description.abstract (摘要) 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。 zh_TW dc.description.abstract (摘要) 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. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究動機與目的 1 第二節 研究範圍與限制 6 第三節 研究方法與架構 6 第一項 研究方法 6 第二項 研究架構 7 第二章 專利法充分揭露要件 9 第一節 充分揭露要件目的及功能 9 第一項 該發明所屬技術領域具通常知識者 11 第二項 說明書應明確且充分記載 11 第三項 支持要求 12 第二節 美國專利法充分揭露要件概述 13 第一項 法規範及審查基準 13 第二項 重要實務案例 23 第三節 歐洲專利體系充分揭露要件概述 35 第一項 法規範及審查基準 35 第二項 重要實務案例 45 第四節 我國專利法充分揭露要件概述 54 第一項 法規範及審查基準 54 第二項 重要實務案例 65 第五節 小結 73 第三章 人工智慧技術發展及發明趨勢 82 第一節 人工智慧技術發展過程 82 第一項 導論 82 第一項 歷史演進 83 第二節 人工智慧技術介紹與產業應用 101 第二項 技術介紹 101 第三項 產業應用 110 第三節 人工智慧相關發明專利研究報告探討 113 第一項 WIPO 2019年人工智慧技術趨勢報告 114 第二項 USPTO 2020年美國人工智慧專利擴散分析報告 116 第三項 JPO 2023年人工智慧相關發明應用趨勢報告 117 第四節 小結 119 第四章 人工智慧之充分揭露要件實務發展與建議 122 第一節 人工智慧與專利審查基準 122 第一項 人工智慧與電腦軟體之關聯 122 第二項 電腦軟體專利審查與充分揭露要件 123 第三項 人工智慧發明與實務對應調整 140 第二節 人工智慧發明特性與充分揭露 158 第一項 資料為中心 159 第二項 跨技術領域結合 163 第三項 內部運作缺乏透明度 164 第三節 近期司法實務案例 167 第一項 Vasudevan Software, Inc v. MicroStrategy, Inc 167 第二項 T 2574/16決定 170 第三項 T 0161/18決定 172 第四項 T 1191/19決定 173 第四節 人工智慧相關發明滿足充分揭露之建議 174 第一項 訓練資料寄存 175 第二項 演算法寄存 176 第三項 人工智慧認證 177 第四項 本文觀點-類型化解決方案 179 第五章 結論與未來延伸議題 186 第一節 結論 186 第二節 未來延伸議題 192 參考文獻 194 zh_TW dc.format.extent 5191486 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107652022 en_US dc.subject (關鍵詞) 專利法 zh_TW dc.subject (關鍵詞) 人工智慧 zh_TW dc.subject (關鍵詞) 電腦軟體相關專利 zh_TW dc.subject (關鍵詞) 據以實現 zh_TW dc.subject (關鍵詞) 充分揭露 zh_TW dc.subject (關鍵詞) Patent law en_US dc.subject (關鍵詞) Artificial Intelligence en_US dc.subject (關鍵詞) Computer software-related patents en_US dc.subject (關鍵詞) Enablement en_US dc.subject (關鍵詞) Sufficiency of disclosure en_US dc.title (題名) 論人工智慧相關發明與專利充分揭露要件 zh_TW dc.title (題名) Discuss the AI-related Inventions and Sufficiency of disclosure in Patent Law en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 壹、中文資料(按作者姓氏筆畫排序) 一、書籍 (一)、IAN GOODFELLOW, et al.，深度學習(陳仁和；初版)，2019年10月。 (二)、李馨，資料庫系統管理與實作：Access + Excel商務應用，4版， 2022年8月。 (三)、松尾豐，了解人工智慧的第一本書：機器人和人工智慧能否取代人類？(江裕真；初版)， 2016年8月。 (四)、陳昇瑋 & 溫怡玲，人工智慧在台灣: 產業轉型的契機與挑戰，2019年6月。 (五)、陳家駿，AI/ChatGPT v.智慧財產權─美國生成式AI案例評析，2024年。 (六)、陳家駿，人工智能vs智慧財產權， 2021年9月。 (七)、謝銘洋，智慧財產權法，12版， 2023年。 二、期刊論文 (一)、吳漢傑、簡信裕，由智慧財產及商業法院判決探討我國人工智慧(AI)相關發明之進步性判斷，智慧財產權，302期，2024年2月。 (二)、李清祺、馮聖原，電腦軟體發明專利制度探討－－我國與歐洲制度發展的演進，智慧財產權，201期，2015年9月。 (三)、沈宗倫，由電腦軟體相關發明論專利法之發明評價與界限，萬國法律，第 244 期，2022年8月。 (四)、沈宗倫，抗體相關發明下專利「可據以實現要件」之再詮釋 ─ 以美國聯邦最高法院 Amgen Inc. v. 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