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題名 生成式AI對著作權侵權的挑戰與補償機制之研究
Copyright Challenges in Generative AI: A Study of Compensation Mechanisms作者 劉亭均 貢獻者 宋皇志
劉亭均關鍵詞 生成式人工智慧
美國著作權法
著作權侵權
合理使用原則
Generative AI
US Copyright Law
Copyright Infringement
Fair Use Doctrine日期 2024 上傳時間 4-Aug-2025 13:31:49 (UTC+8) 摘要 本文透過生成式人工智慧所帶來的衝突與現有機制的調和，探討生成式人工智慧對文化科技的發展和智慧財產權權益的影響。本論文旨在以美國著作權法為主，分析生成式人工智慧所帶來的著作權衝突，並探討可能的機制，以在著作權人、開發者和公眾的利益之間達成平衡。 本文首先介紹生成式人工智慧的技術發展與對人類社會的影響。接著重點討論因生成式人工智慧而產生的法律衝突，尤其是著作權侵權問題。透過分析人工智慧模型使用過程、美國著作權法以及近期發生的相關訴訟，本文認為生成式人工智慧確實有構成侵權的潛在可能。 在生成式人工智慧構成侵權的背景下，隨後本文討論了合理使用原則等法律機制是否有助於解決技術發展與著作權人權益之衝突。此外，本文亦分析現行行業慣例，以尋求各方之最大利益。然而，生成式人工智慧模型與其用途的多樣性也凸顯了該議題的複雜性。儘管目前法條規範尚可處理侵權與合理使用等問題，但其結果仍可能依個案情形而有所不同。 最後，本文認為，僅管著作權法可處理此議題，惟僅依賴現有的著作權法本質上是有限的，而政府透過設立法規強制介入也未必為最佳解法。人工智慧開發者和著作權人之間的談判與合作具有必要性。透過建立創新夥伴關係，本文認為比起法律約束，可以彈性地達成可行解決方案。
This thesis delves into the intersection between generative artificial intelligence (AI) and the US copyright law, exploring the profound impact of AI advancements on creative expression and intellectual property rights. This thesis aims to provide a comprehensive overview of the conflictual influence of generative AI and process possible mechanisms to reach a balance between the interests of copyright owners, AI developers, and the public. In the first part, it explains the technical foundations of generative AI. It traces the path of its development and clarifies the operational mechanics of prominent generative AI models. It contextualizes the profound implications of generative AI on traditional notions of creativity and authorship. This sets the stage for a nuanced examination of its legal consequences. The following part focuses on the legal disputes that arise from the increasing use of generative AI, specifically the issue of copyright infringement. Through analyzing the training progresses, US copyright law along with recent upcoming lawsuits, the thesis underscores the high potential of copyright infringement. The thesis then discusses whether the legal mechanisms, such as the fair use doctrine, can help resolve these conflicts. Additionally, flexible methods are examined as viable options for reducing tensions and promoting collaborative problem-solving in mediating conflicts. The fair use doctrine and prevailing industry practices are analyzed. However, the thesis also highlights the complex dynamics involved in this area, including the diversity of the generative AI models and their applications. In conclusion, this thesis posits that reliance solely on existing copyright laws is inherently limited, emphasizing the imperative for proactive negotiation and collaboration between AI developers and copyright holders. By fostering dialogue and embracing innovative partnerships, stakeholders can chart a course toward equitable resolutions that uphold the rights and interests of all parties involved.參考文獻 【中文書籍】 陳家駿、許正乾、林宜柔（2024），《AI/ ChatGPT v.智慧財產權──美國生成式AI案例評析》，初版，元照。 謝銘洋（2021），《智慧財產權法》，11版，元照。 Clifford A. Pickover（著），林柏宏（譯）（2020），《AI之書 : 圖解人工智慧發展史》，初版，時報文化。 【中文期刊文章】 高嘉鴻（2018），〈人工智慧創作是否受著作權保護之略探〉，《智慧財產權月刊》，239期，頁18-34。 黃絜（2023），人工智慧生成作品與著作權保護之初探──以美國法原創性與作者身分要件之釐清為中心〉，《月旦法學雜誌》，335期，頁139-160。 馮震宇（2020），〈從人類創作到 AI 創作：智財權權利主體與權利歸屬之挑戰〉，《月旦法學教室》，212 期，頁34-43。 許力儒、莊弘鈺（2022），〈人工智慧創作之適格與歸屬──法律與技術之綜合觀點〉，《萬國法律》，241期，頁20-38。 徐龍（2021），〈論人工智慧創作之法律屬性與保護〉，《東吳法律學報》，33卷1期，頁139-181。 陳豐年（2023），〈人工智慧「作品」之著作權歸屬暨民事侵權責任 －美國法制的啟示〉，《月旦律評》，19期，頁103-112。 蔡明誠 （2024），〈論人工智慧時代著作權法上結合著作與其他著作類型之概念及利用〉，《月旦法學雜誌》，344期，頁6-21。 陳豐年、廖威智（2017），〈論著作權法之實質相似性（substantial similarity）：以美國聯邦第二巡迴上訴法院判決為中心〉，《智慧財產權月刊》，219期，頁41-63。 黃雙成（2024），〈人工智慧創作與著作之轉化性使用－結合法律及技術之觀點〉，《萬國法律》，253期，頁19-38。 張兆恬（2023），〈初探ChatGPT 管制挑戰與回應─美國法的觀點〉，《月旦法學雜誌》，341期，頁36-50。 陳家駿（2023），〈從美國人工智慧擴散模型訴訟案─談生成式AI 圖像之著作侵權議題〉，《智慧財產權月刊》，298期，頁6-35。 馮震宇（2023），〈論生成式AI 時代著作權之保護與規範─從美國DABUS 與Goldsmith 案談起〉，《月旦法學雜誌》，341期，頁6-25。 中文特刊論文 章忠信（2019），〈我國著作權集體管理制度之實務發展與未來〉，《慶祝智慧局20週年特刊》，頁114-129。 【中文網頁】 王思原（2023），〈美國第一件藝術家控告AI公司案：加州北區聯邦地區法院2023年Andersen v. Stability AI Ltd.et al案〉，《北美智權報》，347期，載於：http://www.naipo.com/Portals/1/web_tw/Knowledge_Center/Infringement_Cases/IPNC_231227_0302.html。 陳家駿、許正乾（2023），《AI聊天機器人ChatGPT引爆著作侵權疑雲？—文字篇》，載於：https://iknow.stpi.narl.org.tw/Post/Read.aspx?PostID=19599。 陳家駿、許正乾（2023），《Midjourney與Stability AI擴散模型自動生成引爆著作侵權疑雲？—圖形影像篇》，載於：https://iknow.stpi.narl.org.tw/Post/Read.aspx?PostID=19796。 鄭貞茂（2019/1/14），〈從21年前被「深藍」打敗的世界棋王，思考人工智慧的未來〉，《關鍵評論網》，載於：https://www.thenewslens.com/article/111755。 章忠信（2023），《生成式AI的合理使用可能》，載於：http://www.copyrightnote.org/ArticleContent.aspx?ID=9&aid=3154 【碩士論文】 張景富（2023），《AI製圖與我國著作權議題之探討》，中國醫藥大學科技法律碩士學位學程碩士論文，台中。 李慈恩（2023），《數位時代對著作財產權合理使用制度之挑戰 －以資料探勘技術之應用為中心》，國立中正大學財經法律系研究所碩士論文，嘉義。 黃雙成（2022），《人工智慧創作侵權之研究：以著作之轉化性使用為中心》，國立陽明交通大學科技法律研究所碩士論文，新竹。 何孟遠（2019），《論人工智慧之創作與著作權侵權》，世新大學智慧財產研究所碩士論文，台北。 郭建甫（2019），《人工智慧生成作品之著作權問題研究》，國立政治大學科技管理與智慧財產研究所碩士論文，台北。 嚴裕欽（2006），《著作財產權之限制—以美國著作權法合理使用為中心》，國立政治大學法律研究所碩士論文，台北。 【英文書籍】 Custers, B. (Ed.). (2022). 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國立政治大學
科技管理與智慧財產研究所
110364210資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110364210 資料類型 thesis dc.contributor.advisor 宋皇志 zh_TW dc.contributor.author (Authors) 劉亭均 zh_TW dc.creator (作者) 劉亭均 zh_TW dc.date (日期) 2024 en_US dc.date.accessioned 4-Aug-2025 13:31:49 (UTC+8) - dc.date.available 4-Aug-2025 13:31:49 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2025 13:31:49 (UTC+8) - dc.identifier (Other Identifiers) G0110364210 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158392 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 科技管理與智慧財產研究所 zh_TW dc.description (描述) 110364210 zh_TW dc.description.abstract (摘要) 本文透過生成式人工智慧所帶來的衝突與現有機制的調和，探討生成式人工智慧對文化科技的發展和智慧財產權權益的影響。本論文旨在以美國著作權法為主，分析生成式人工智慧所帶來的著作權衝突，並探討可能的機制，以在著作權人、開發者和公眾的利益之間達成平衡。 本文首先介紹生成式人工智慧的技術發展與對人類社會的影響。接著重點討論因生成式人工智慧而產生的法律衝突，尤其是著作權侵權問題。透過分析人工智慧模型使用過程、美國著作權法以及近期發生的相關訴訟，本文認為生成式人工智慧確實有構成侵權的潛在可能。 在生成式人工智慧構成侵權的背景下，隨後本文討論了合理使用原則等法律機制是否有助於解決技術發展與著作權人權益之衝突。此外，本文亦分析現行行業慣例，以尋求各方之最大利益。然而，生成式人工智慧模型與其用途的多樣性也凸顯了該議題的複雜性。儘管目前法條規範尚可處理侵權與合理使用等問題，但其結果仍可能依個案情形而有所不同。 最後，本文認為，僅管著作權法可處理此議題，惟僅依賴現有的著作權法本質上是有限的，而政府透過設立法規強制介入也未必為最佳解法。人工智慧開發者和著作權人之間的談判與合作具有必要性。透過建立創新夥伴關係，本文認為比起法律約束，可以彈性地達成可行解決方案。 zh_TW dc.description.abstract (摘要) This thesis delves into the intersection between generative artificial intelligence (AI) and the US copyright law, exploring the profound impact of AI advancements on creative expression and intellectual property rights. This thesis aims to provide a comprehensive overview of the conflictual influence of generative AI and process possible mechanisms to reach a balance between the interests of copyright owners, AI developers, and the public. In the first part, it explains the technical foundations of generative AI. It traces the path of its development and clarifies the operational mechanics of prominent generative AI models. It contextualizes the profound implications of generative AI on traditional notions of creativity and authorship. This sets the stage for a nuanced examination of its legal consequences. The following part focuses on the legal disputes that arise from the increasing use of generative AI, specifically the issue of copyright infringement. Through analyzing the training progresses, US copyright law along with recent upcoming lawsuits, the thesis underscores the high potential of copyright infringement. The thesis then discusses whether the legal mechanisms, such as the fair use doctrine, can help resolve these conflicts. Additionally, flexible methods are examined as viable options for reducing tensions and promoting collaborative problem-solving in mediating conflicts. The fair use doctrine and prevailing industry practices are analyzed. However, the thesis also highlights the complex dynamics involved in this area, including the diversity of the generative AI models and their applications. In conclusion, this thesis posits that reliance solely on existing copyright laws is inherently limited, emphasizing the imperative for proactive negotiation and collaboration between AI developers and copyright holders. By fostering dialogue and embracing innovative partnerships, stakeholders can chart a course toward equitable resolutions that uphold the rights and interests of all parties involved. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究動機與問題意識 1 第一項 研究動機 1 第二項 問題意識－權益的衝突與調和 3 第二節 研究架構 4 第三節 研究方法與限制 5 第二章 生成式AI之背景介紹 7 第一節 生成式AI發展背景與訓練過程 7 第一項 AI的定義與發展背景 7 第二項 生成式AI與其訓練過程 10 第二節 生成式AI現今發展與影響 16 第三節 小結 19 第三章 生成式AI之著作權侵權問題 21 第一節 美國著作權侵權制度介紹 21 第一項 「著作權」之發展背景 21 第二項 美國著作權侵權要件與法院判斷 23 第二節 生成式AI的侵權問題 25 第一項 前階段：蒐集資料 25 第二項 中階段：訓練過程中的中間副本 26 第三項 後階段：AI模型的最終輸出 27 第三節 相關案例 28 第一項 Getty Images, Inc. v. Stability AI, Inc. 29 第二項 New York Times Co. v. Microsoft Corp. 31 第三項 Disney Enterprises, Inc. v. Midjourney, Inc. 36 第四節 小結 38 第四章 著作權人權益與AI發展之調和 41 第一節 是否通過合理使用的檢視？ 41 第一項 合理使用 42 第二項 合理使用之要件 45 第三項 合理使用的挑戰 52 第二節 調和機制之建立 55 第一項 實務上授權人授權之案例 56 第二項 其他機制之選擇 59 第三節 小結 63 第五章 結論：在未來的平衡 64 參考文獻 65 zh_TW dc.format.extent 2312634 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110364210 en_US dc.subject (關鍵詞) 生成式人工智慧 zh_TW dc.subject (關鍵詞) 美國著作權法 zh_TW dc.subject (關鍵詞) 著作權侵權 zh_TW dc.subject (關鍵詞) 合理使用原則 zh_TW dc.subject (關鍵詞) Generative AI en_US dc.subject (關鍵詞) US Copyright Law en_US dc.subject (關鍵詞) Copyright Infringement en_US dc.subject (關鍵詞) Fair Use Doctrine en_US dc.title (題名) 生成式AI對著作權侵權的挑戰與補償機制之研究 zh_TW dc.title (題名) Copyright Challenges in Generative AI: A Study of Compensation Mechanisms en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 【中文書籍】 陳家駿、許正乾、林宜柔（2024），《AI/ ChatGPT v.智慧財產權──美國生成式AI案例評析》，初版，元照。 謝銘洋（2021），《智慧財產權法》，11版，元照。 Clifford A. 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