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題名:人工智慧之著作權法律問題研究
作者:徐龍
作者(外文):XU, LONG
校院名稱:東吳大學
系所名稱:法律學系
指導教授:鄭冠宇
學位類別:博士
出版日期:2022
主題關鍵詞:人工智慧機器學習生成對抗網路法律地位著作人身分原創性著作權適格鄰接權權利歸屬著作權侵害著作權限縮合理使用轉化性使用强制授權法定授權思想表達二分論利益衡平Artificial Intelligence(AI)Machine LearningGenerative Adversarial NetworkLegal StatusAuthorshipOriginalityCopyrightableNeighboring RightsAttribution of RightCopyright InfringementThe Restriction of CopyrightFair UseTransformative UseCompulsory LicenseStatute LicenseIdea/Expression of Idea DichotomyBalance of Interests
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近年來,人工智慧技術飛速發展,已可快速且大量生成品質優良之創作内容,且於市場上獲得良好反饋,未來人工智慧勢必進一步加深對創作市場及產業所帶來之影響。然而,與此同時,法律對於人工智慧著作權議題之回應,依舊尚在探索而未有定案。
本文旨在針對人工智慧技術對當下法律之衝擊,兼具法律與技術層面之基礎,主要從四個核心層面,探索人工智慧之著作權法相關問題。第一,探討人工智慧之法律地位,即人工智慧能否成爲著作權法意義上之著作人。第二,探討人工智慧創作之法律屬性與保護,即人工智慧生成内容能否成爲著作、應該如何保護、其權利歸屬為何、以及現有法律應該如何調適。第三,探討機器閲讀之著作權法規制,即機器學習輸入階段之著作資料處理行爲可能涉及大量重製、改作或編輯他人之著作,人工智慧對著作資料之利用行爲是否構成對被利用資料著作權之侵害,現有法律應該如何調適。第四、探索機器模仿之著作權法因應,即機器學習輸出階段之成果在風格手法等特徵上模仿輸入資料時,是否構成對被利用資料著作權之侵害,現有法律應該如何因應。
人工智慧之法律地位部分。本文認爲,就目前而言,人工智慧依舊無法擺脫其工具屬性,賦予其法律主體地位與技術、倫理、法理以及現行制度皆有重大衝突,故而不應賦予其法律主體地位。因此,人工智慧僅為客體,不能成爲著作權法意義上之著作人。
人工智慧創作之法律屬性及保護部分。本文以著作權與鄰接權理論為基礎,探討人工智慧創作之法律屬性與保護,以因應法律適用之窘境,尋覓法制與科技之平衡。本文認爲,首先,人工智慧創作之本質係透過演算法對大量作品樣本進行解碼、學習與訓練,形成表徵作品集合之內在邏輯規律的概率模型,並依此進行模仿之結果。人工智慧所習得之作品集内在邏輯與規律可體現著作人對構成元素之原創性選擇與編排,具有可著作性,其著作人是對學習資料、生成模式風格等之選擇與編排具有原創性之人工智慧使用者;其次,對於不具原創性但需要大量資本、技術或勞力投入才能獲得的人工智慧創作,基於保護投資、激勵創造之目的,可參考歐盟資料庫鄰接權之規定,給與15年的鄰接權保護;再次,人工智慧創作之權利應歸屬於實際對於人工智慧創作具備控制、主宰能力者,通常而言為人工智慧之使用者,後續則可透過契約進行移轉,建立彈性之歸屬制度;最後,在法律保護制度上,應當綜合考量多元主體之參與貢獻,並兼顧公共利益,對投資者、研發者、使用者、資料庫者、消費者以及公共大眾進行利益分配,以達到激勵科技創新與進步,增進社會福祉之目的。
機器學習輸入階段著作資料處理行爲之著作權法規制部分。本文認爲,人工智慧技術之關鍵,係以資料訓練演算法為特徵的機器學習,需要蒐集、處理並輸入巨量資料供演算法訓練,因而一開始即可能涉及大量重製、改作或編輯他人之著作。人工智慧對著作資料之利用行爲,並不必然可以援引現行著作權法之限制規定而免責,使得企業為開展人工智慧研發與應用,需要對大量著作申請授權並支付費用,這不僅造成實踐之困難,亦嚴重阻礙人工智慧領域之科技發展。反觀美國、日本與歐盟等國家或地區已經提供合法化解決方案之背景下,為消除人工智慧發展之著作權障礙並提供國際競爭優勢,有必要制定合法化利用之特別規定。相比於透過著作權限縮、合理使用或強制授權制度,法定授權更有利於降低交易成本,衡平各方之利益,保障著作權人利益的同時,為人工智慧科技之應用與發展提供良好法制環境。故而,本文認爲應就機器學習制定法定授權制度,並客觀界定具體適用情形,完善相應配套措施。
機器學習輸出階段模仿輸入資料表達風格之著作權法因應部分。本文認爲,機器學習作爲人工智慧技術的核心,其顛覆了人類對創作自然規律的認知,打破了人類創作市場的一般法則。表達性機器學習透過輸入著作資料來訓練演算法,並輸出反映輸入資料表達特徵之新內容,會對被學習著作的潛在市場和價值造成不利影響,減損著作權人的利益,打擊著作人的創作熱情。然而,現行著作權法卻無法有效解釋和規制機器學習的全部過程,僅輸入階段的著作資料處理行為有著作權法上意義。表達性機器學習之核心並非重製或演繹,而是學習和生成,它是一種不同與以往的新型著作利用方式。對此,目前著作權法尚處於空白和缺失的狀態。為了避免表達性機器學習技術發展和應用對人類創作市場的破壞,保護著作權人利益,有必要創設一種新型著作權。同時,為了避免過於嚴苛的著作權保護對人工智慧技術發展和應用的阻礙,也有必要對於熱度下降保護需求較弱的著作做出適當限制,兼顧著作權人利益與科技發展,以達利益平衡之目標,追求社會效益最大化。
Artificial Intelligence (AI) is rising rapidly in recent years. It could generate a great quantity of works with high quality in a short time. It may bring some impacts to the creative industries in the future. However, the related laws and issues of AI-generated works haven’t come to a conclusion yet.
In order to respond to the legal implications caused by artificial intelligence, my doctoral dissertation bases on law and technology, mainly explores the copyright law from four core aspects. Firstly, it explores the legal status of artificial intelligence, that is, whether artificial intelligence can become the author in the sense of copyright law. Secondly, it discusses the legal attributes and protection of artificial intelligence creation, that is, whether the content generated by artificial intelligence can become a work, how it should be protected, and how existing laws should be adjusted. Thirdly, it discusses the copyright regulation of machine reading, that is, the data processing in the input stage of machine learning may involve a large number of remaking, modification or editing of others' works, whether the use of artificial intelligence constitutes the infringement of the copyright of the used data, and how the existing laws should be tested. Fourthly, it explores the copyright law of machine imitation, that is, whether the results of the output stage of machine learning imitate the input data in style and techniques, constitute the infringement of the copyright of the used data, and how to debug the existing laws.
Regarding to the subject matter issues of legal status of artificial intelligence, this article believes that, at present, artificial intelligence still cannot get rid of its tool attribute, and endows its subject status with the major conflict of technology, ethics, legal principle and the current system, so it should not be given its legal subject status. Therefore, artificial intelligence is only a object, and can not become an author in copyright law.
Regarding to the subject matter issues of copyright in AI-generated works, this article explores the legal status and protection of AI-generated works based on the theories of copyright and neighboring right, tries to solve the dilemma of legal application, and finds a balance between law and science. Firstly, the essence of AI-generated works is to decode, learn and train a large number of samples through algorithms to form a probability model that expresses the inherent logic and rules of the collection. The in-house logic and rules of the collection of works obtained by artificial intelligence can reflect the original selection and arrangement of the elements of the author, which is copyrightable. And the author is the artificial intelligence user with the minimal degree of creativity in the selection and arrangement of learning materials, modes and styles of generation, etc. Secondly, as for AI-generated works that are not original but require substantial investment to obtain, we can refer to the EU Database Directive 96/9/EC and give a 15-year protection of neighboring right based on the purpose of protecting investment and incenting creation. Thirdly, as far as the legal protection of AI-generated works, considering the contribution of multiple entities and the public interests, this article emphasizes that the rights and responsibilities among investors, researcher, users, digital owners, consumers and the public should be clarified, in order to incent the innovation and development of science, and enhance social welfare.
Regarding to the subject matter issues of copyright regulation on data processing in machine learning input stage, this article believes that machine learning is the key to artificial intelligence, which is characterized by data training algorithm. It requires to collect, process and input large amounts of data for algorithm training. Therefore, extensive copying, reworking or editing of other people’s work may inevitably be involved in the very beginning. However, the use of works by artificial intelligence would not necessarily exempt the limitation of the current copyright law, which makes enterprises need to apply for authorization and pay fees for a large number of works. It not only causes practical difficulties, but also seriously hinders the development of science and technology in the field of artificial intelligence. According to the present situation that the United States, Japan, the European Union and other countries or regions in the world have already provided legalized solutions for the problems above, it is necessary for Taiwan to formulate the special rules for the utilization of legalization in order to eliminate the copyright obstacles to the development of artificial intelligence and provide international competitive advantages. Consequently, this paper analyzed the business model as well as proposing four kinds of coping styles such as the restriction of the copyright, the fair use, compulsory license system and statute license system. In result, compared with the restriction of the copyright, fair use or compulsory license system, statute license system is more conducive to reducing transaction costs, balancing the interests of all parties, protecting the interests of copyright owners, providing a good environment for the application, and development of artificial intelligence technology. Therefore, this paper argued that the statute license system should be applied to machine learning, and the specific applicable situation should be scientifically defined to improve the corresponding supporting measures.
Regarding to the subject matter issues of copyright law response to the imitation of input data in machine learning output stage, this article believes that machine learning is the core of artificial intelligence technology, which subverts the human cognition of the natural law of creation and breaks the general law of the human work market. Expressive machine learning trains the algorithm by inputting data and output new content to reflect the characteristic value of data, which will adversely affect the potential market and value of the learned works, reduce the interests of the copyright owner and strike the author's creative enthusiasm. However, the current copyright law cannot effectively explain and regulate the whole process of machine learning. Only the data processing of works in the input stage has the significance of copyright law. In fact, the core of machine learning is not replication or interpretation, but learning and generation. It is a new-type utilization of works that differs from previous works. In this regard, the current copyright law is still in a blank and missing state. In order to avoid the damage of the development and application of machine learning technology to the market of human works and protect the interests of copyright owners, it is necessary to create a new-type copyright. At the same time, over-strict copyright protection could obstruct the development and application of AI technology, it is also necessary to make appropriate restrictions on works with declining heat and weak demand for protection, take into account the interests of copyright owners and the development of science and technology, so as to achieve the goal of balancing interests and pursue the maximization of social benefits.
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謝銘洋,我國著作權法中「創作」概念相關判決之研究,收錄於國際比較下我國著作權法制總檢討(上冊),中研院法律學研究所,2014年,頁57-89。
顏上詠,人工智慧商業時代及智慧財產權研究,收錄于智慧財產權與法律風險析論:人工智慧商業時代的來臨,初版,五南,2019年,頁95-127。

(三)期刊論文
王利明,人工智慧時代對民法學的新挑戰,東方法學,第3期,2018年5月,頁4-9。
王遷,論人工智慧生成的內容在著作權法中的定性,法律科學(西北政法大學學報),第5期,2017年9月,頁148-155。
李安,機器學習作品的著作權法分析——非作品性使用、合理使用與侵權使用,電子知識產權,第6期,2020年6月,頁60-70。
呂群蓉,在人與非人之間徘徊——以民法「自然人」概念為基礎分析克隆人,法學雜誌,第12期,2011年12月,頁118-120。
沈宗倫,論數位暫時性重製於著作權法制法律評價——兼以重製權的新詮釋評價我國相關立法,東吳大學法律學報,第19卷第4期,2008年4月,頁31-74。
林利芝,初探人工智慧的著作權爭議——以「著作人身分」為中心,智慧財產權,第237期,2018年9月,頁61-78。
林秀芹、遊凱傑,著作權制度應對人工智慧創作物的路徑選擇——以民法孳息理論為視角,電子知識產權,第6期,2018年6月,頁13-19。
徐小奔、楊依楠,論人工智慧深度學習中著作權的合理使用,交大法學,第3期,2019年7月,頁32-42。
徐龍,論人工智慧創作之法律屬性與保護,東吳法律學報,第33卷第1期,2021年7月,頁139-182。
徐龍,機器學習的著作權困境及制度方案,東南學術,第2期,2022年3月,頁237-246。
吳柏憑,人工智慧對於著作權概念的衝擊——日本著作權的新政策發展方向,科技法律透析第,第28卷12期,2016年12月,頁26-31。
吳漢東,人工智慧時代的制度安排與法律規制,法律科學(西北政法大學學報),第5期,2017年9月,頁128-136。
吳漢東,人工智慧生成作品的著作權法之問,中外法學,第3期,2020年6月,頁653-673。
房紹坤、林廣會,人工智慧民事主體適格性之辨思,蘇州大學學報(哲學社會科學版),第5期,2018年9月,頁64-72、191.。
易繼明,人工智慧創作物是作品嗎?,法律科學,第5期,2017年9月,頁137-147。
郭少飛,「電子人」法律主體論,東方法學,第3期,2018年5月,頁38-49。
孫占利,智慧機器人法律人格問題論析,東方法學,第3期,2018年5月,頁10-17。
高佳佳,類型化視角下機器學習的合理使用分析,電子知識產權,2021年5月,第5期,頁18-28。
陳吉棟、向夢涵譯,尼爾·M·理查茲、威廉·D·斯馬特著,法律如何看待機器人,法治社會,第1期,2019年1月,頁54-65。
梁志文,論人工智慧創造物的法律保護,法律科學(西北政法大學學報),第5期,2017年9月,頁156-165。
梁志文、李忠誠,論算法創作,華東政法大學學報,2019年11月,第6期,頁46-59。
常紀文,動物有權利還是僅有福利?——「主、客二分法」與「主、客一體化法」的爭論與溝通,環球法律評論,2008年11月,第6期,頁61-73。
黃銘傑,資料庫著作原創性之所在及其侵權疑義——與一般編輯著作之比較,法學新論,第24期,2010年7月,頁41-57。
馮震宇,從人類創作到AI創作:智財權利主體與權利歸屬之挑戰,月旦法學教室,第212期,2020年6月,頁34-43。
馮曉青、潘柏華,人工智慧「創作」認定及其財產權益保護研究——兼評「首例人工智慧生成內容著作權侵權案」,西北大學學報(哲學社會科學版),第50卷第2期,2020年3月,頁39-52。
章忠信,表演人權利之保護,智慧財產權月刊,50期,2003年2月,頁17-36。
章忠信,「表演」於我國著作權法之保護,律師雜誌,第258期,2001年3月,頁36-47。
張力、陳鵬,機器人「人格」理論批判與人工智慧物的法律規制,學術界,總第247期,2018年12月,頁53-75。
張金平,人工智慧作品合理使用困境及其解決,環球法律評論,第3期,2019年3月,頁120-132。
張建文,格裏申法案的貢獻與侷限,華東政法大學學報,第2期,2018年8月,頁32-41。
張瑞星,論音樂著作抄襲類型化的「模糊界線」,科技法律評析,第10期,2018年6月,頁53-96。
張瑞星,從美國法院案例談著作權合理使用的轉化利用測試,科技法律評析,第2期,2009年6月,頁155-202。
張嘉麟,論我國著作權法之強制授權授權機制——以強制授權授權之結構分析為中心,智慧財產權月刊,第45期,2002年9月,頁71-89。
華劼,合理使用制度運用於人工智慧創作的兩難及出路,電子知識產權,2019年4月,第4期,頁29-39。
楊立新,人工類人格:智能機器人的民法地位——兼論智能機器人致人損害的民事責任,求是學刊,第4期,2018年7月,頁84-96。
楊立新、張莉,連體人的法律人格及其權利衝突協調,法學研究,第5期,2005年9月,頁27-40。
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蔡達智,機器人法律地位及其應有規範取向,興大法學,第25期,2019年5月,頁1-41。
熊琦,人工智慧生成內容的著作權認定,知識產權,第3期,2017年3月,頁3-8。
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龍文懋,人工智慧法律主體地位的法哲學思考,法律科學(西北政法大學學報),第5期,2018年8月,頁24-31。
劉洪華,論人工智慧的法律地位,政治與法律,第1期,2019年1月,頁11-21。
劉憲權,人工智慧時代機器人行為道德倫理與刑法規制,比較法研究,第4期,2018年7月,頁40-54。
劉友華、魏遠山,機器學習的著作權侵權問題及其解決,華東政法大學學報,第2期,2019年3月,頁68-79。
鄭戈,人工智慧與法律的未來,探索與爭鳴,第10期,2017年11月,頁78-84。

(四)法院判決
(1)臺灣
臺灣高等法院臺南分院106年上易字第256號刑事判決。
智慧財產法院107年民公訴字第4號民事判決。
智慧財產及商業法院110年度行專訴字第3號判決。
最高法院97年度臺上字第1587號刑事判決。
智慧財產法院109年度民著訴字第4號民事判決。
智慧財產法院107年度民公訴字第4號民事判決。
最高法院97年度臺上字第1587號刑事判決。
智慧財產法院98年度民訴字第2號民事判決。
智慧財產法院97年度刑智上訴字第41號刑事判決。
臺灣臺北地方法院109年度智簡字第19號刑事判決。
智慧財產法院107年度刑智上易字第45號刑事判決。
智慧財產法院104年度刑智上易字第90號刑事判決。
智慧財產法院104年度民著訴字第50號民事判決。
智慧財產法院100年度民著上易字第1號民事判決。
智慧財產法院99年度民著訴字第85號民事判決。
智慧財產法院99年度民著訴字第36號民事判決。
智慧財產法院103年度民著上字第26號民事判決。
智慧財產法院102年度民著訴字第57號民事判決。
智慧財產法院102年度民著上字第19號民事判決。
臺灣新北地方法院101年度智字第2號民事判決。
智慧財產法院101年度民著訴字第27號民事判決。
智慧財產法院100年度民著訴字第31號民事判決。
智慧財產及商業法院110年度民著訴字第129號民事判決。
臺灣臺中地方法院110年度聲判字第16號刑事裁定。
智慧財產法院107年度民著訴字第68號。
智慧財產法院104年度民著上字第5號民事判決。
智慧財產法院103年28度民著上更(一)字第2號民事判決。
智慧財產法院106年度民著上更(一)字第1號民事判決。
臺灣臺中地方法院94年度訴字第1865號刑事判決。
臺灣高等法院臺中分院96年度上訴字第2208號刑事判決。
智慧財產及商業法院110年度民著訴字第129號民事判決。
臺灣臺中地方法院110年度聲判字第16號刑事裁定。
智慧財產法院104年度民著上更(一)字第2號民事判決。
智慧財產法院104年度刑智上訴字第47號刑事判決。
智慧財產法院98年度民著訴字第2號民事判決。
最高法院106年度台上字第1726號民事判決。
臺灣高等法院94年度智上字第45號民事判決。
臺灣高等法院94年度智上字第53號民事判決。

(2)中國大陸
北京互联网法院(2018)京0491民初239號民事判决。
廣東省深圳市南山區人民法院(2019)粵0305民初14010號民事判決。
北京市第一中級人民法院(2011)一中民初字第1321號民事判決。
北京市高級人民法院(2013)高民終字第1221號民事判決。

(五)函示意見
(1)台灣
經濟部智慧財產局109年12月2日經訴字第10906311620號訴願決定。
經濟部智慧財產局109年6月29日(109)智專一(二)15173字第10940948310號函。
經濟部智慧財產局109年5月5日(109)智專一(二)15173字第10940658750號函。
經濟部智慧財產局108年11月11日(108)智專一(二)15179字第10841663060號函。
經濟部智慧財產局95年7月28日智著字第09500070820號函。
經濟部智慧財產局89年7月7日(八九)智著字第89005709號函。
經濟部智慧財產局100年4月13日電子郵件1000413b號函。

(2)中國大陸
中國大陸最高人民法院「關於加強著作權和與著作權有關的權利保護的意見」法發〔2020〕42號。


(六)官方文件
臺灣行政院:「AI小國大戰略」, https://www.ey.gov.tw/Page/5A8A0CB5B41DA11E/50a08776-e33a-4be2-a07c-a6e523f5031b(最後瀏覽日:2022/9/11)。
臺灣行政院:「臺灣AI行動計劃」, https://digi.ey.gov.tw/File/4C622B6A10053DAD (最後瀏覽日:2022/8/20)。
臺灣科技部:「人工智慧科研發展指引」,2019年9月版,https://www.most.gov.tw/most/attachments/53491881-eb0d-443f-9169-1f434f7d33c7(最後瀏覽日:2022/9/2)。
中國大陸國務院:「國務院關於印發新一代人工智慧發展規劃的通知」,http://big5.www.gov.cn/gate/big5/www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm(最後瀏覽日:2022/8/27)。
中國大陸國家標準化管理委員會、中央網信辦、國家發展改革委、科技部、工業和資訊化部:「國家新一代人工智慧標準體系建設指南」,http://www.gov.cn/zhengce/zhengceku/2020-08/09/5533454/files/bf4f158874434ad096636ba297e3fab3.pdf (最後瀏覽日:2022/8/27)。
中國大陸國務院:「新一代人工智慧發展規劃」,http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm(最後瀏覽日:2022/5/22)。
中國大陸國家新一代人工智慧治理專業委員會:「新一代人工智慧倫理規範」,http://www.most.gov.cn/kjbgz/202109/t20210926_177063.html(最後瀏覽日:20225/22)。

(七)網路資料
名畫檔案,皮格馬利翁和活雕像 Pygmalion and Galatea,https://www.ss.net.tw/paint-149_56-3176.html (最後瀏覽日:2022/9/11)。
昕立資訊,最聰明的AI智能客服機器人, https://www.thinkpower.com.tw/chatflex.html(最後瀏覽日:2022/8/26)。
和訊新聞,「柯潔烏鎮終敗」全盤回顧人類最後希望與圍棋上帝終極PK,http://news.hexun.com/2017-05-27/189387092.html(最後瀏覽日:2022/9/2)。
鳳凰網,全球首款性愛機器人要開賣,http://tech.ifeng.com/a/20170210/44541223_0.shtml#p=2(最後瀏覽日:2022/9/2)。
數位時代,跨越次元的愛!和虛擬偶像初音結婚的日本男子,https://www.bnext.com.tw/article/51885/akihiko-kondo-got-married-with-hatsune-miku?(最後瀏覽日:2022/9/2)。
數位時代,Uber自駕車致死車禍原因出爐:監督人員在看影集, https://www.bnext.com.tw/article/49620/uber-self-driving-cars-accident-report(最後瀏覽日:2022/9/2)。
iThome,深度直擊全球Amazon首家無人商店,Amazon Go維運關鍵大公開, https://www.ithome.com.tw/news/124133(最後瀏覽日:2022/9/2)。
INSIDE,史上最強Banner製造機!阿裏AI「魯班」每秒做8000張助力雙11!,https://www.inside.com.tw/article/11037-alibaba-ai-banner(最後瀏覽日:2022/9/10)。
CROSSING,人工智慧會寫詩了!什麼是靈魂?什麼是自由意志?,https://crossing.cw.com.tw/article/8259(最後瀏覽日:2022/9/2)。
iThome,新聞記者要失業了嗎?AI機器軟體一季能寫3千則新聞,https://www.ithome.com.tw/news/93868(最後瀏覽日:2022/9/3)。
iThome,中國法院宣判寫稿機器人Dreamwriter擁有著作權?,https://www.ithome.com.tw/news/135305(最後瀏覽日:2022/9/3)。
圖書館學與資訊科學大辭典,專家系統,https://terms.naer.edu.tw/detail/1678973/ (最後瀏覽日:2022/9/5)。
程式人生,[深度學習]深度自編碼器簡述,https://www.796t.com/content/1549737183.html(最後瀏覽日:2022/8/22)。
peter_tsao,分類(Classification), https://sls.weco.net/node/10936 (最後瀏覽日:2022/8/22)。
e-Cloud valley,你知道機器學習(Machine Learning),有幾種學習方式嗎? ,https://www.ecloudvalley.com/zh-hant/machine-learning/ (最後瀏覽日:2022/8/22)。
德國之生,机器人是公民?沙特敢为天下先,https://www.dw.com/zh/%E6%9C%BA%E5%99%A8%E4%BA%BA%E6%98%AF%E5%85%AC%E6%B0%91%E6%B2%99%E7%89%B9%E6%95%A2%E4%B8%BA%E5%A4%A9%E4%B8%8B%E5%85%88/a-41169697 (最後瀏覽日:2022/8/27)。
風傳媒,神聖河流》紐西蘭旺阿努伊河~~全世界第一條擁有「人權」的河,河與原住民的命運隨之改變,https://www.storm.mg/article/4484212?mode=whole (最後瀏覽日:2022/8/26)。
CSDN,邊框回歸,https://blog.csdn.net/zijin0802034/article/details/77685438 (最後瀏覽日:2022/6/27)。
每日頭條,恐怖!語音助手勸主人自殺,還發出詭異笑聲...,https://kknews.cc/news/k4qpa98.html (最後瀏覽日:2022/6/2)。
iThome,昕力資訊ChatFlex-AI智能客服機器人獲選Gartner 2018年亞太地區最酷AI交談供應商—臺灣唯一入選企業,https://www.ithome.com.tw/pr/128913(最後瀏覽日:2022/9/2)。
INSIDE,史上最強 Banner 製造機!阿裏 AI「魯班」每秒做 8000 張助力雙11!,https://www.inside.com.tw/article/11037-alibaba-ai-banner(最後瀏覽日:2022/9/2)。
CROSSING,人工智慧會寫詩了!什麼是靈魂?什麼是自由意志?,https://crossing.cw.com.tw/article/8259(最後瀏覽日:2022/6/20)。
iThome,新聞記者要失業了嗎?AI機器軟體一季能寫3千則新聞,https://www.ithome.com.tw/news/93868(最後瀏覽日:2022/9/3)。
iThome,中國法院宣判寫稿機器人Dreamwriter擁有著作權?,https://www.ithome.com.tw/news/135305(最後瀏覽日:2022/9/3)。
好奇心研究所,微軟的人工智慧小冰學會作詩了,我們試了一下,http://www.qdaily.com/articles/40870.html(最後瀏覽日:2022/6/25)。
極客公園,微軟小冰發佈了獨立完成的詩集,我們和專案負責人聊了聊它的現在和未來https://www.geekpark.net/news/219635 (最後瀏覽日:2022/6/25)。
壹讀,微軟李笛:為什麼說畫家小冰是最艱難的一次養成?https://read01.com/4GazA3J.html (最後瀏覽日:2022/6/27)。
好奇心研究所,微軟的 AI 會畫畫了,這可能意味著什麼?http://www.qdaily.com/articles/64052.html(最後瀏覽日:2022/6/27)。
CROSSING,人工智慧會寫詩了!什麼是靈魂?什麼是自由意志?,https://crossing.cw.com.tw/article/8259(最後瀏覽日:2022/9/10);
微軟AI小冰在中央美術學院舉辦首個畫展:名叫「或然世界」,https://read01.com/J8xggJD.html(最後瀏覽日:2022/9/10)。
CNEWS,Google用來管控仇恨言論的人工智慧竟然有「種族歧視」?, https://cnews.com.tw/140190829a05/(最後瀏覽日:2022/9/5)。
INSIDE,Google Photos 糗大了,誤將兩名人類標記為大猩猩, https://www.inside.com.tw/article/4747-google-mistakenly-tags-black-people-as-gorillas(最後瀏覽日:2022/9/5)。
知識力,谷歌圖書侵權一案歷時11年終落幕,https://www.zhichanli.com/p/526340970,(最後瀏覽日:2022/8/23)。
Dreamwriter官方視頻,https://v.qq.com/x/page/z071387ge88.html,(最後瀏覽日:2022/8/23)。

二 日文文獻
(一)日文專書
小泉直樹,アメリカ著作権制度,初版,弘文堂,1996。
小倉秀夫、金井重彥,著作権法コンメンタール,初版,レクシスネクシス.ジャパン,2013年。
中山信弘,ソフトウェアの法的保護,初版,有斐閣,1988年。
中山信弘,著作権法,2版,有斐閣,2014年。
加戸守行,著作権法逐条講義,5訂新版,著作権情報センター,2006年。
半田正夫,著作権法概説,13版,法学書院,2007年。
斉藤博,著作権法,3版,有斐閣,2004年。
茶園成樹,著作権法,初版,有斐閣,2014年。
高林龍,標準著作権法,2版,有斐閣,2013年。

(二)專書論文
上野達弘,人工知能による発明と創作AI生成物に関する知的財産権,PI×AI(特許情報×人工知能)~第四次産業革命が特許情報の未來をどう変えていくのか~特集,2017年,頁20-23。

(三)期刊論文
上野達弘,人工知能と機械學習をめぐる著作権法上の課題 日本とヨーロッパにおける近時の動向,法律時報,91巻8號,2019年,頁33-40。
上野達弘,著作権法改正が拓く日本の“機械學習パラダイス”,ビジネス法務,19巻2號,2018年,頁1-10。
中山信弘,著作権法の憂鬱,パテント,66巻1號,2013年,頁106-118。
出井甫,AI創作物に関する著作権法上の問題點とその対策案,パテント,69巻15號,2016年,頁35-45。
別所直哉,実務から見たAIがもたらす知的財産法へのインパクトと課題,法律時報,91巻8號,2019年,頁9-15。
奧邨弘司,人工知能が生み出したコンテンツと著作権,パテント,70巻2號,2017年,頁10-19。
橫山久芳,AIに関する著作権法・特許法上の問題,法律時報,91巻8號,2019年,頁50-56。
愛知靖之,AI 生成物・機械學習と著作権法,パテント,73巻8號,2020年,頁131-146。

(四)法院判決
東京地判昭和53·6·21判タ366号。
最一小判平成13年6月28日民集55巻4号。

(五)官方文件
文部科學省,著作権法の一部を改正する法律(案文·理由),2018年。
文部科學省,著作権法の一部を改正する法律(新舊對照條文),2018年。
文化庁,著作権審議會第9小委員會(コンピュータ創作物関係)報告書,1993年。
内閣府,知的財産戦略推進事務局,AIによって生み出される創作物の取扱い,2016年。
内閣府,內閣広報室,著作権法の一部を改正する法律案:概要説明資料,2018年。
内閣府,統合イノベーション戦略推進会議決定,び人間中心のAI社會原則,2019年。
知的財産戦略本部,検証・評価・企畫委員會、次世代知財システム検討委員會,次世代知財システム検討委員會報告書~デジタル・ネットワーク化に対応する次世代知財システム構築に向けて~,2016年。
知的財産研究所,AIを活用した創作や3Dプリンティング用データの産業財産権法上の保護に関する調査研究報告書,2017年。
知的財産戦略本部,検証・評価・企画委員会、新たな情報財検討委員会,新たな情報財検討委員会報告書-データ・人工知能(AI)の利活用促進による産業競争力強化の基盤となる知財システムの構築に向けて-,2017年。
知的財産戦略本部,知的財産推進計畫,2019年。
総務省情報通信政策研究所,AIネットワーク社会推進会議,報告書2017-AIネットワーク化に関する国際的な議論の推進に向けて-,2017年。
総務省情報通信政策研究所,AIネットワーク社会推進会議,報告書2018-AIの利活用の促進及びAIネットワーク化の健全な進展に向けて-,2018年。
総務省情報通信政策研究所,AIネットワーク社会推進会議,報告書2019, 2019年。
総務省情報通信政策研究所,AIネットワーク社会推進会議,報告書2020~「安心・安全で信頼性のある AI の社会実装」に向けて~,2020年。
総務省情報通信政策研究所,AIネットワーク社会推進会議,報告書2021~「安心・安全で信頼性のある AI の社会実装」の推進 ~,2021年。

三 英文文獻
(一)英文專書
ADAIR-TOTEFF, CHRISTOPHER, MAX WEBER’S SOCIOLOGY OF RELIGION, MOHR SIEBECK, TÜBINGEN, GERMANY (2016).
ALPAYDIN, ETHEM, MACHINE LEARNING: THE NEW AI, THE MIT PRESS, CAMBRIDGE, MASSACHUSETTS LONDON, ENGLAND, U.K. (2016)
ANGELO, LOULA, RICARDO GUDWIN & JOÃO QUEIROZ eds., ARTIFICIAL COGNITION SYSTEMS, IDEA GROUP PUBLISHING, HERSHEY, U.S.A. (2007).
APLIN, TANYA ed., RESEARCH HANDBOOK ON INTELLECTUAL PROPERTY AND DIGITAL TECHNOLOGIES, EDWARD ELGAR PUBLISHING, CHELTENHAM, U.K. & NORTHAMPTON, MA, U.S.A. (2020).
BODENHEIMER, EDGAR, JURISPRUDENCE: THE PHILOSOPHY AND METHOD OF THE LAW, HARVARD UNIVERSITY PRESS, U.S.A. (Revised ed.1974).
CADDICK, NICHOLAS, GILLIAN DAVIES & GWILYM HARBOTTLE, COPINGER AND SKONE JAMES ON COPYRIGHT (MAINWORK & 1ST SUPPLEMENT), SWEET & MAXWELL, U.K. (18th. ed. 2021).
CALO, RYAN, A MICHAEL FROOMKIN & IAN KERR. eds., ROBOT LAW, EDWARD ELGAR PUBLISHING, CHELTENHAM, U.K. & NORTHAMPTON, MA, U.S.A. (2016).
CHOPRA, SAMIR & LAURENCE F WHITE, A LEGAL THEORY FOR AUTONOMOUS ARTIFICIAL AGENTS, THE UNIVERSITY OF MICHIGAN PRESS, U.S.A. (2011).
CORMEN, THOMAS H. ET AL., INTRODUCTION TO ALGORITHMS, THE MIT PRESS, CAMBRIDGE, MASSACHUSETTS LONDON, ENGLAND, U.K. (3rd ed. 2009).
COOTER, ROBERT &THOMAS ULEN, LAW AND ECONOMIC, PEARSON EDUCATION, INC., U.S.A. (6th ed.2016).
CRAGLIA, MAX ed., ARTIFICIAL INTELLIGENCE: A EUROPEAN PERSPECTIVE, PUBLICATIONS OFFICE OF THE EUROPEAN UNION, LUXEMBOURG (2018).
DRASSINOWER, ABRAHAM, WHAT’S WRONG WITH COPYING?, HARVARD UNIVERSITY PRESS, U.S.A. (2015).
GOMPEL, STEF JOHAN VAN, FORMALITIES IN COPYRIGHT LAW: AN ANALYSIS OF THEIR HISTORY, RATIONALES AND POSSIBLE FUTURE, KLUWER LAW INTERNATIONAL, ALPHEN AAN DEN RIJN, THE NETHERLANDS (2011).
GOODFELLOW, IAN, YOSHUA BENGIO & AARON COURVILLE, DEEP LEARNING, THE MIT PRESS, CAMBRIDGE, MASSACHUSETTS, LONDON, ENGLAND, UK (2016).
GUIBAULT, LUCIE M. C. R., COPYRIGHT LIMITATIONS AND CONTRACTS: AN ANALYSIS OF THE CONTRACTUAL OVERRIDABILITY OF LIMITATIONS ON COPYRIGHT, KLUWER LAW INTERNATIONAL, THE HAGUE, THE NETHERLANDS (2002).
HOLMES, OLIVER WENCLELKL, THE COMMON LAW, UNIVERSITY OF TORONTO LAW SCHOOL TYPOGRAPHICAL SOCIETY, U.S.A. (Paulo J. S. Pereira & Diego M. Beltran eds 2011).
HURWITZ, JUDITH, HENRY MORRIS, CANDACE SIDNER & DANIEL KIRSCH, AUGMENTED INTELLIGENCE: THE BUSINESS POWER OF HUMAN-MACHINE COLLABORATION, AUERBACH PUBLICATIONS, NEW YORK, U.S.A. (2019).
KAPLAN, JERRY, ARTIFICIAL INTELLIGENCE: WHAT EVERYONE NEEDS TO KNOW, OXFORD UNIVERSITY PRESS, NEW YORK, U.S.A. (2016).
KLAUS SCHWAB, THE FOURTH INDUSTRIAL REVOLUTION, WORLD ECONOMIC FORUM, SWITZERLAND (2016).
MCCORDUCK, PAMELA, MACHINES WHO THINK : A PERSONAL INQUIRY INTO THE HISTORY AND PROSPECTS OF ARTIFICIAL INTELLIGENCE, A K PETERS/CRC PRESS, MASSACHUSETTS, U.S.A. (2nd ed.2004).
MARSLAND, STEPHEN, MACHINE LEARNING: AN ALGORITHMIC PERSPECTIVE, CHAPMAN & HALL (CRC PRESS), UK (2nd ed.2015).
MITCHELL, TOM M., MACHINE LEARNING, MCGRAW-HILL EDUCATION, U.S.A. (1997).
MINSKY, MARVIN, SEMANTIC INFORMATION PROCESSING, MIT PRESS, CAMBRIDGE, MASSACHUSETTS, AND LONDON, ENGLAND, UK (1968).
MUNZER, STEPHEN R. ed., NEW ESSAYS IN THE LEGAL AND POLITICAL THEORY OF PROPERTY, CAMBRIDGE UNIVERSITY PRESS, U.S.A. (2001).
NIELSEN, MICHAEL, NEURAL NETWORKS AND DEEP LEARNING, DETERMINATION PRESS (2015).
NIMMER, DAVID & MELVILLE B. NIMMER, NIMMER oN COPYRIGHT, LEXISNEXIS MATTHEW BENDER, NEW YORK, U.S.A. (2020).
PASQUALE, FRANK, THE BLACK BOX SOCIETY: THE SECRET ALGORITHMS THAT CONTROL MONEY AND INFORMATION, HARVARD UNIVERSITY PRESS, CAMBRIDGE, MASSACHUSETTS, LONDON, ENGLAND, UK (2015).
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RAMALHO, ANA, THE COMPETENCE OF THE EUROPEAN UNION IN COPYRIGHT LAWMAKING: A NORMATIVE PERSPECTIVE OF EU POWERS FOR COPYRIGHT HARMONIZATION, SPRINGER INTERNATIONAL PUBLISHING, SWITZERLAND (2016).
REGAN, TOM, THE CASE FOR ANIMAL RIGHTS,UNIVERSITY OF CALIFORNIA PRESS, BERKELEY AND LOS ANGELES, CALIFORNIA, U.S.A. (2004).
ROKACH, LIOR & ODED MAIMON, DATA MINING WITH DECISION TREES: THEORY AND APPLICATIONS, WORLD SCIENTIFIC PUBLISHING CO., INC.(WSPC), NEW JERSEY, U.S.A. (2ND 2014).
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SCHWAB, KLAUS, THE FOURTH INDUSTRIAL REVOLUTION, WORLD ECONOMIC FORUM, COLOGNY/GENEVA, SWITZERLAND (2016).
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(二)會議論文
Damer, Naser et al., The Effect of Wearing a Mask on Face Recognition Performance: An Exploratory Study, THE 2020 INTERNATIONAL CONFERENCE OF THE BIOMETRICS SPECIAL INTEREST GROUP (BIOSIG) 1, 1-6 (2020).
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(三)期刊論文
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Solum, Lawrence B., Legal Personhood for Artificial Intelligences, 70(4) N. C. L. REV. 1231, 1231-1288 (1992).
Teubner, Gunther, Rights of Non-humans Electronic Agents and Animals as New Actors in Politics and Law, 33(4) J. L. & SOC. 497, 497-521 (2006).
Turing, Alan M., Intelligent Machinery 107, 107-127 (1948).
Turing, Alan M., Computing Machinery and Intelligence, 49 MIND 433, 433-460 (1950).
Wu, Andrew J., From Video Games to Artificial Intelligence: Assigning Copyright Ownership to Works Generated by Increasingly Sophisticated Computer Programs, 25 AIPLA Q. J. 131, 131-177 (1997).
Yanisky-Ravid, Shlomit, Generating Rembrandt: Artificial Intelligence, Copyright, And Accountability in the 3a Era--The Human-Like Authors Are Already Here--A New Model, 2017 MICH. ST. L. REV. 659, 659-721 (2017).
Yanisky-Ravid, Shlomit & Luis Antonio Velez-Hernandez, Copyrightability of Artworks Produced by Creative Robots and Originality: the Formality-Objective Model, 19 MINN. J.L. SCI. & TECH. 1, 1-53 (2018).
Yen, Alfred C., Restoring the Natural Law: Copyright as Labor and Possession, 51 OHIO STATE L. J. 517, 517-559 (1990).
Yu, Robert, The Machine Author: What Level of Copy Right Protection Is Appropriate for Fully Independent Compute-Generated Works? 165 U. PA. L. REV. 1245, 1245-1269 (2017).

(四)未出版之論文
Ahmed, Elgammal et al., CAN: Creative Adversarial Networks, Generating “Art” by Learning About Styles and Deviating from Style Norms, arXiv:1706.07068 [cs.AI], [Submitted on 21 Jun 2017], https://arxiv.org/pdf/1706.07068.pdf.
Brown, Tom B. et al., Language Models are Few-Shot Learners, arXiv:2005.14165 [cs.CL], [Submitted on 28 May 2020 (v1), last revised 22 Jul 2020 (this version, v4)] , available at https://arxiv.org/pdf/2005.14165.pdf.
Cheng, Wen-Feng et al., Image Inspired Poetry Generation in XiaoIce, arXiv:1808.03090 [cs.AI], [Submitted on 9 Aug 2018], available at https://arxiv.org/pdf/1808.03090.pdf.
Goodfellow, Ian J. et al., Generative Adversarial Networks, arXiv:1406.2661v1
[stat.ML], [Submitted on 10 Jun 2014], available at https://arxiv.org/pdf/1406.2661v1.pdf.
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Samuelson, Pamela & Hashimoto, Kathryn, Is the U.S. Fair Use Doctrine Compatible with Berne and TRIPS Obligations? (August 7, 2018). Forthcoming,Tatiana Synodinou (ed.), UNIVERSALISM OR PLURALISM IN INTERNATIONAL COPYRIGHT LAW (KLUWER LAW INTERNATIONAL, INFORMATION LAW SERIES), UC BERKELEY PUBLIC LAW RESEARCH PAPER, available at SSRN: https://ssrn.com/abstract=3228052 or http://dx.doi.org/10.2139/ssrn.3228052.
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(五)法院判決
(1)美國
State v. Loomis. 881 Nw2d 749 (Wis. 2016).
Naruto v. Slater, 888 F.3d 418 (9th Cir. 2018).
Penguin Books U.S., Inc. v. New Christian Church of Full Endeavor, Ltd., 262 F.Supp.2d 251 (2003).
The Urantia Foundation v. Robert Burton, 1980 WL 1176 (1980).
Burrows-Giles Lithographic Co. v. Sarony, 111 U.S. 53 (1884).
Urantia Found. v. Kristen Maaherra, 114 F.3d 955 (9th Cir. 1997).
Naruto v. Slater, 888 F.3d 418 (9th Cir. 2018).
Kelley v. Chicago Park Dist., 635 F.3d 290 (7th Cir. 2011).
Eldred v. Ashcroft, 537 U.S. 186 (2003).
Burrow-Giles Lithographic Co. v. Sarony, 111 U.S. 53 (1884).
Trade-Mark Cases, 100 U.S. 82 (1879).
Mazer v. Stein, 347 U.S. 201 (1954).
Goldstein v. California, 412 U.S.546 (1973).
Urantia Found. v. Kristen Maaherra, 114 F.3d 955 (9th Cir. 1997).
Naruto v. Slater, 888 F.3d 418 (9th Cir. 2018).
Kelley v. Chicago Park Dist., 635 F.3d 290 (7th Cir. 2011).
Satava v. Lowry, 323 F.3d 805 (9th Cir. 2003).
Thaler v. Hirshfeld, 558 F. Supp. 3d 238 (E.D. Va. 2021).
Naruto v. Slater, 888 F.3d 418 (9th Cir. 2018).
Naruto v. Slater, 2016 WL 362231, (N.D. Cal. 2016).
Bleistein v. Donaldson Lithographing Co., 188 US. 239 (1903).
Feist Publications, Inc. V. Rural Telephone Service Co., Inc., 499 U.S. 340 (1991).
Authors Guild v. Google Inc., 954 F.Supp.2d. 282 (2013), affirmed by 804 F.3d 202 (2015), cert. denied, 136 S.Ct. 1658 (2016).
A.V. ex rel. Vanderhye v. iParadigms, LLC, 562 F.3d 630 (2009).
White v. West Pub. Corp., F.Supp.3d (2014).
Folsom v. Marsh, 6 Hunt Mer. Mag. 175 (1841).
Sony Corporation of America v. Universal City Studios, Inc., 464 U.S. 417 (1984).
Nunez v. Caribbean International News Corporation, 235 F.3d 18 (1st Cir. 2000).
Bill Graham Archives v. Dorling Kindersley, 448 F.3d 605 (2nd Cir. 2006).
Kelly v. Arriba Soft Corporation, 336 F.3d 811 (9th Cir. 2003).
Perfect 10 v. Amazon.com, 508 F.3d 1146 (9th Cir. 2007).
Suntrust v. Houghton Mifflin Company, 268 F.3d 1257 (11th Cir. 2001).
Authors Guild v. Google Inc., 804 F.3d 202 (2015).
A.V. ex rel. Vanderhye v. iParadigms, LLC, 562 F.3d 630 (2009).
White v. West Publishing Corp., 29 F. Supp. 3d 396 (2014).
Baker v. Selden, 101 U.S. 99 (1879).
Mazer v. Stein, 347 U.S. 201 (1954).
Nichols v. Universal Pictures Corp., 45 F.2d 119 (2d Cir. 1930).
Computer Associates International, Inc. v. Altai, Inc., 982 F.2d 693 (2d Cir. 1992).
Roth Greeting Cards v. United Card Co. , 429 F.2d 1106 (9th Cir. 1970) .
Sid & Marty Krofft Television Productions Inc. v. McDonald's Corp. (1977).
Morrissey v. Procter & Gamble Co., 379 F.2d 675 (1st Cir. 1967).
Data East USA, Inc. v. Epyx, Inc., 862 F.2d 204 (9th Cir. 1988).
Cain v. Universal Pictures Co., 47 F. Supp. 1013 (S.D. Cal. 1942).
Walker v. Time Life Films, Inc., 784 F.2d 44 (2d Cir. 1986).
Gates Rubber Co. v. Bando Chemical Industries, Ltd., 9 F.3d 823 (10th Cir. 1993).

(2)英國
Gyles v Wilcox (1740) 26 ER 489.
Millar v Taylor (1769) 4 Burr. 2303, 98 ER 201.
Donaldson v Beckett (1774) 2 Brown's Parl. Cases 129, 1 Eng. Rep. 837; 4 Burr. 2408, 98 Eng. Rep. 257 ; 17 Cobbett's Parl. Hist. 953 (1813).
The Bold Buccleugh (1852) 7 Moo PC 267.
Donoghue v. Allied Newspapers Limited (1938) Ch 106.
Nova Productions Ltd v. Mazooma Games Ltd [2007] EWCA Civ 219,[2006] EWCA Civ 1044

(3)澳洲
Victoria Park Racing and Recreation Grounds Co. Ltd v. Taylor (1937) 58 CLR 479.
Thaler v Commissioner of Patents [2021] FCA 879.

(4)印度
RG Anand v. M/S Deluxe Films & Ors (1978).

(六)官方文件
(1)國際組織(WIPO、WTO、UNESCO等)
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WIPO, Revised Issues Paper on Intellectual Property Policy and Artificial Intelligence (2020), https://www.wipo.int/meetings/en/doc_details.jsp?doc_id=499504 (last visited 2022/9/12).
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United Nations Educational, Scientific and Cultural Organization (UNESCO), Culture, Platforms and Machines: The Impact of Artificial Intelligence on The Diversity
of Cultural Expressions (2018), https://en.unesco.org/creativity/sites/creativity/files/12igc_inf4_en.pdf (last visited 2022/9/17).

(2)研究機構(IEEE、LIBER、MPI等)
IEEE, Ethically Aligned Design: A Vision for Prioritizing Human Well-being with
Autonomous and Intelligent Systems (2nd ed. 2019), https://standards.ieee.org/wp-content/uploads/import/documents/other/ead_v2.pdf (last visited 2022/8/26).
LIBER, THE HAGUE DECLARATION ON KNOWLEDGE DISCOVERY IN THE DIGITAL AGE. https://libereurope.eu/the-hague-declaration/ (last visited 2022/9/15).
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(3)美國(國會、著作權局、國會研究服務處、人工智慧國家安全委員會、圖書館研究協會等)
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U.S. National Security Commission on Artificial Intelligence(NSCAI), Final Report:
National Security Commission on Artificial Intelligence, https://www.nscai.gov/wp-content/uploads/2021/03/Full-Report-Digital-1.pdf (last visited 2022/8/27).
Executive Office of the President, National Science and Technology Council, & Committee on Technology, Preparing for the Future of Artificial Intelligence
(2016), https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf (last visited 2022/9/2).
H.Res.153 - 116th Congress (2019-2020): Supporting the development of guidelines for ethical development of artificial intelligence, H.Res.153, 116th Cong. (2019), https://www.congress.gov/bill/116th-congress/house-resolution/153 (last visited 2022/8/22).
H.R.4625 - 115th Congress (2017-2018): FUTURE of Artificial Intelligence Actof 2017, H.R.4625, 115th Cong. (2018), https://www.congress.gov/bill/115th-congress/house-bill/4625?q=%7B%22search%22%3A%22FUTURE+of+Artificial+Intelligence+Act+2017%22%7D&s=2&r=1 (last visited 2022/8/31).
H.R.5356 - 115th Congress (2017-2018): National Security Commission Artificial
Intelligence Act of 2018, H.R.5356, 115th Cong. (2018), https://www.congress.gov/bill/115th-congress/house-bill/5356?q=%7B%22search%22%3A%22National+Security+Commission+Artificial+Intelligence+Act+of+2018%22%7D&s=3&r=2 (last visited 2022/8/31).
H.R.827 - 116th Congress (2019-2020): AI JOBS Act of 2019, H.R.827, 116thCong. (2019), https://www.congress.gov/bill/116th-congress/house-bill/827?q=%7B%22search%22%3A%22AI+JOBS+Act+of+2019%22%7D (last visited 2022/8/31).
H.R.6216 - 116th Congress (2019-2020): National Artificial Intelligence Initiative Act
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H.R.7559 - 116th Congress (2019-2020): FUTURE of Artificial Intelligence Actof 2020, H.R.7559, 116th Cong. (2020), https://www.congress.gov/bill/116th-congress/house-bill/7559?q=%7B%22search%22%3A%22FUTURE+of+Artificial+Intelligence+Act+2020%22%7D&r=1&s=8 (last visited 2022/8/31).
S.3891 - 116th Congress (2019-2020): Advancing Artificial Intelligence Research Act
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H.R.7339 - 116th Congress (2019-2020): AI Careers Act of 2020, H.R.7339, 116th
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S.1776 - 117th Congress (2021-2022): Artificial Intelligence for the Military Act of
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S.2904 - 117th Congress (2021-2022): Department of Defense Artificial Intelligence
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S.3035 - 117th Congress (2021-2022): GOOD AI Act of 2021, S.3035, 117th
Cong. (2022), https://www.congress.gov/bill/117th-congress/senate-bill/3035?q=%7B%22search%22%3A%22Government+Ownership+and+Oversight+of+Data+in+Artificial+Intelligence+Act+2021%22%7D (last visited 2022/8/31).
S.3175 - 117th Congress (2021-2022): Advancing American Artificial Intelligence
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H.R.6553 - 117th Congress (2021-2022): AI JOBS Act of 2022, H.R.6553, 117th
Cong.(2022), https://www.congress.gov/bill/117th-congress/house-bill/6553?q=%7B%22search%22%3A%22Artificial+Intelligence+Job+Opportunities+and+Background+Summary+Act+of+2022%22%7D (last visited 2022/8/31).
H.R.7296 - 117th Congress (2021-2022): GOOD AI Act of 2022, H.R.7296, 117th
Cong. (2022), https://www.congress.gov/bill/117th-congress/house-bill/7296?q=%7B%22search%22%3A%22Government+Ownership+and+Oversight+of+Data+in+Artificial+Intelligence+Act+2022%22%7D (last visited 2022/8/31).
House of Representatives Report No. 94-1476 (1976), Copyright Law Revision,https://www.copyright.gov/history/law/clrev_94-1476.pdf (last visited 2022/9/16).
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U.S. COPYRIGHT OFFICE, COMPENDIUM OF U.S. COPYRIGHT OFFICE PRACTICES
(3d ed. 2021). available at https://www.copyright.gov/comp3/docs/compendium.pdf.
U.S. COPYRIGHT OFFICE, COMPENDIUM OF U.S. COPYRIGHT OFFICE PRACTICES (2d ed. 1984), available at https://copyright.gov/history/comp/compendium-two.pdf
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(4)歐盟(執委會、法律事務委員會、公民與憲政事務委員會、科學與新科技倫理委員會、資通訊網絡暨科技總署等)
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European Commission (High-Level Expert Group on Artificial Intelligence), Ethics
Guidelines for Trustworthy AI, https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai (last visited 2022/8/27).
Committee on Legal Affairs, Proposal for a Regulation of The European Parliament and of The Council: Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts,
Brussels, 21.4.2021 COM, (2021) 206 final, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0206 (last visited 2022/9/12).
Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions on Artificial Intelligence for Europe, Brussels,
25.4.2018 COM, (2018) 237 final. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018DC0237&from=EN (last visited 2022/8/22).
European Commission, Directorate-General for Research and Innovation, European Group on Ethics in Science and New Technologies (EGE), Statement on Artificial Intelligence, Robotics and ‘Autonomous’ Systems: Brussels, 9 March
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Committee on Legal Affairs, Draft Report with Recommendations to the Commission
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Policy Department C: Citizens’ Rights and Constitutional Affairs, European Civil
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European Commission, Directorate-General of Communications Networks, Content & Technology, Final Report: Study in Support of the Evaluation of Directive
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(5)英國(國會、上議院、智慧財產局、人工智慧特別會員會等)
UK Parliament, House of Lords, Select Committee on Artificial Intelligence, AI in the
UK: Ready, Willing and Able, https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf (last visited 2022/8/22).
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HARGREAVES, IAN, DIGITAL OPPORTUNITY: A REVIEW OF INTELLECTUAL PROPERTY
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(6)法國
Cédric Villani Mathematician and Member of the French Parliament, For a Meaningful Artificial Intelligence: Towards a French and European Strategy, https://www.aiforhumanity.fr/pdfs/MissionVillani_Report_ENG-VF.pdf (last visited 2022/8/22).

(7)澳洲
Dave Dawson, Emma Schleiger, Joanna Horton, John McLaughlin, Cathy Robinson, George Quezada, Jane Scowcroft & Stefan Hajkowicz, Artificial Intelligence: Australia’s Ethics Framework - A Discussion Paper, Commonwealth Scientific and Industrial Research Organisation (CSIRO) & Department of Industry,
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Department of Industry Innovation and Science, Artificial Intelligence: Australia’s
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(8)新加坡
Intellectual Property Office of Singapore, Understanding the Copyright Act 2021
Updating Copyright for the Digital Age (2021), https://www.ipos.gov.sg/docs/default-source/resources-library/copyright/copyright-act-factsheet.pdf (last visited 2022/9/10).

(9)南非
South Africa, Patent Designs Trade Marks and Copyright Office, PATENT JOURNAL: INCLUDING TRADE MARKS, DESIGNS AND COPYRIGHT IN CINEMATOGRAPH FILMS, Vol 54, No. 07, July, Part II of II, 255 (2021), available at https://iponline.cipc.co.za/Publications/PublishedJournals/E_Journal_July%202021%20Part%202.pdf.

(七)網路資料
BUSINESS INSIDER, Sophia that once said it would ‘destroy humans’, https://www.businessinsider.com/meet-the-first-robot-citizen-sophia-animatronic-humanoid-2017-10?r=UK (last visited 2022/9/12).
BUSINESS INSIDER, Microsoft Took Its New A.I. Chatbot Offline After It Started
Spewing Racist Tweets, https://slate.com/business/2016/03/microsoft-s-new-ai-chatbot-tay-removed-from-twitter-due-to-racist-tweets.html (last visited 2022/1/5).
ISIS, Artificial Intelligence: the Curious Case of Edmond De Belamy, https://isismagazine.org.uk/2019/03/art-ificial-intelligence-the-curious-case-of-edmond-de-belamy/ (last visited 2022/9/3).
THE VERGE, Musician Taryn Southern on composing her new album entirely with AI: How artificial intelligence simplifies music production for solo artists, https://www.theverge.com/2017/8/27/16197196/taryn-southern-album-artificial-intelligence-interview (last visited 2022/9/3).
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good—and completely mindless, https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/(last visited2022/9/6).
The New York Times, How Do You Know a Human Wrote This? Machines are gaining the ability to write, and they are getting terrifyingly good at it., https://www.nytimes.com/2020/07/29/opinion/gpt-3-ai-automation.html (last visited 2022/9/6).
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四 德文文獻
(一)德文專書
Cella, Johann Jakob, Freymüthige Aufsätze, 1. Aufl., 1784.
Ertel,Wolfgang, Grundkurs Künstliche Intelligenz: Eine praxisorientierte Einführung, 5. Aufl., 2021.
Grätz, Axel, Künstliche Intelligenz im Urheberrecht, 1. Aufl., 2021.
Gless, Sabine/ Seelmann, Kurt, Intelligente Agenten und das Recht: Zur Verantwortlichkeit beim Einsatz von Robotern, 1. Aufl., 2016
Huggenberger, Stefan/ Moser, Natasha/ Schröder, Hannsjörg/ Cozzi, Bruno/ Granato, Alberto/ Merighi, Adalberto, Neuroanatomie des Menschen, 1. Aufl. 2019.
Kant, Immanuel, Grundlegung Zur Metaphysik Der Sitten, 6. Aufl., 1952.
Käde, Lisa, Kreative Maschinen und Urheberrecht, 1. Aufl., 2021.
Köhler, Helmut/ Lange, Heinrich, BGB Allgemeiner Teil, 46. Aufl., 2022.
Verantwortlichkeit beim Einsatz von Robotern, 1. Aufl., 2016.

(二)專書論文
Hilgendorf, Eric, Automatisiertes Fahren als Herausforderung für Ethik und Rechtswissenschaft,2019第二屆人工智慧與法律國際學術研討會論文集, S.49-58.

(三)期刊論文
Apel, Simon/ Kaulartz, Markus, Rechtlicher Schutz von Machine Learning-Modellen, RDi 2020, S. 24-34.
Bilski, Mitarbeiter Nico/ Schmid, Thomas, Verantwortungsfindung beim Einsatz maschinell lernender Systeme, NJOZ 2019, S. 657-661.
Dettling, Heinz-Uwe/ Krüger, Stefan, Erste Schritte im Recht der Künstlichen Intelligenz, MMR 2019, S. 211-217.
Dornis, Tim W., Der Schutz künstlicher Kreativität im Immaterialgüterrecht, GRUR 2019, S. 1252-1264.
Gomille, Christian, Kreative künstliche Intelligenz und das Urheberrecht, JZ 2019, S. 969-975.
Hacker, Philipp, Europäische und nationale Regulierung von Künstlicher Intelligenz, NJW 2020, S. 2142-2147.
Herberger, Maximilian, „Künstliche Intelligenz“ und Recht, NJW 2018, S. 2825-2829.
Jakl, Bernhard, Das Recht der Künstlichen Intelligenz, MMR 2019, S. 711-715.
Lauber-Rönsberg, Anne, Autonome „Schöpfung“ - Urheberschaft und Schutzfähigkeit, GRUR 2019, S, 244-253.
Legner, Sarah, Erzeugnisse Künstlicher Intelligenz im Urheberrecht, ZUM 2019, S, 807-812.
Martini, Mario, Algorithmen als Herausforderung für die Rechtsordnung, JZ 2017, S. 1017-1025.
Ory, Stephan / Sorge, Christoph, Schöpfung durch Künstliche Intelligenz?, NJW 2019, S. 710-713.
Ruschemeier, Hannah, 9. Speyerer Forum zur digitalen Lebenswelt: Regulierung Künstlicher Intelligenz in der Europäischen Union zwischen Recht und Ethik, NVwZ 2020, S. 446-448.
SHetmank, ven / Lauber-Rönsberg, Anne, Künstliche Intelligenz – Herausforderungen für das Immaterialgüterrecht, GRUR 2018, S. 574-582.
Specht, Louisa, Zum Verhältnis von (Urheber-)Recht und Technik: Erfordernis eines Dualismus von techniksensitivem Recht und rechtssensitiven technischen Durchsetzungsbefugnissen, GRUR 2019, S. 253-259.
Specht, Louisa/ Herold, Sophie, Roboter als Vertragspartner: Gedanken zu Vertragsabschlüssen unter Einbeziehung automatisiert und autonom agierender Systeme, MMR 2018, S. 40-44.
Steege, Hans, Algorithmenbasierte Diskriminierung durch Einsatz von Künstlicher Intelligenz Rechtsvergleichende Überlegungen und relevante Einsatzgebiete, MMR 2019, S. 715-721.
Valta, Matthias / Vase, Johann Justus, Kommissionsvorschlag für eine Verordnung über Künstliche Intelligenz, ZRP 2021, S. 142-145.
von Westphalen, Friedrich Graf , Köln, Produkthaftungsrechtliche Erwägungen beim Versagen Künstlicher Intelligenz (KI) unter Beachtung der Mitteilung der Kommission COM(2020) 64 final, VuR 2020, S. 248-254.

(四)官方文件
Bundesministerium für Wirtschaft und Energie, das Bundesministerium für Bildung und Forschung und das Bundesministerium für Arbeit und Soziales erarbeitet,
Strategie Künstliche Intelligenzder Bundesregierung (2018), https://www.bmwk.de/Redaktion/DE/Publikationen/Technologie/strategie-kuenstliche-intelligenz-der-bundesregierung.pdf?__blob=publicationFile&v=10 (Letzter Abruf: 2022/8/22).
Bundesregierung, Strategie Künstliche Intelligenzder Bundesregierung (2020), https://www.bmwk.de/Redaktion/DE/Publikationen/Technologie/strategie-kuenstliche-intelligenz-fortschreibung-2020.pdf?__blob=publicationFile&v=12 (Letzter Abruf: 2022/8/22).
Gesetzgebung BGBl. I 1990 S. 1762. (Gesetz zur Verbesserung der Rechtsstellung des Tieres im bürgerlichen Recht).
BT-Drs. 18/12329, Gesetzentwurf der Bundesregierung: Entwurf eines Gesetzes zur Angleichung des Urheberrechts an die aktuellen Erfordernisse der Wissensgesellschaft (Urheberrechts-Wissensgesellschafts-Gesetz – UrhWissG). https://dserver.bundestag.de/btd/18/123/1812329.pdf (Letzter Abruf: 2022/8/22).
Gesetzgebung BGBl. I 2017 S. 3346. Gesetz zur Angleichung des Urheberrechts an die aktuellen Erfordernisse der Wissensgesellschaft (Urheberrechts- Wissensgesellschafts-Gesetz - UrhWissG).

(五)網路資料
Bundesministerium für Wirtschaft und Energie, das Bundesministerium für Bildung und Forschung und das Bundesministerium für Arbeit und Soziales erarbeitet,
Strategie Künstliche Intelligenzder Bundesregierung (2018), https://www.bmwk.de/Redaktion/DE/Publikationen/Technologie/strategie-kuenstliche-intelligenz-der-bundesregierung.pdf?__blob=publicationFile&v=10 (Letzter Abruf: 2022/8/22).

五 其他資料
№ 301924-7 В архиве, О внесении изменений в часть первую Гражданского кодекса Российской Федерации и статью 22 Федерального закона "О введении в действие части первой Гражданского кодекса Российской Федерации"(в части уточнения положений о самовольных постройках) https://sozd.duma.gov.ru/bill/301924-7 (最後瀏覽日:2022/9/3)。

 
 
 
 
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