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    题名: 專利法關於人工智慧發明重要議題之研究
    A study on the Core Issues of Invention Related to Artificial Intelligence in Patent Law
    作者: 鄭禕寧
    Cheng, Yi-Ning
    贡献者: 沈宗倫
    Shen, Chung-Lun
    鄭禕寧
    Cheng, Yi-Ning
    关键词: 人工智慧
    軟體專利
    專利適格性
    權利主體
    先前技術
    進步性
    Artificial intelligence
    Software patent
    Patent eligibility
    Subject of rights
    Inventive step
    Non-obviousness
    日期: 2019
    上传时间: 2019-09-05 16:31:34 (UTC+8)
    摘要: 從人臉、語音識別到自動駕駛汽車，人工智慧已經跳脫科幻電影的虛構，逐漸走入並且遍佈我們的生活。雖然就目前已知的技術來說，人工智慧尚未具備思考能力，然而科學家不斷地希望能夠突破限制，讓人工智慧不僅能夠成為生活上的輔助、協助人類進行研究發明，甚至是由人工智慧獨立完成發明。
    為了鼓勵創作與發明，我國制定了智慧財產權相關法律如專利法、商標法及著作權法，惟因其保護之前提為精神上創作，目前的保護對象即權利歸屬主體，皆僅限於自然人。隨著人工智慧越來越接近人類，開始能夠進行創作甚至思考，進而可能成為真正有貢獻之發明人時，現有的智慧財產權相關法制規範，將會面臨包含權利主體、專利要件等適用上之困境，。
    事實上，人工智慧之本質與電腦軟體極為相似，其對於現行法制造成的衝擊，除了上述權利歸屬即要件認定問題外，另一方面則再次喚起了電腦軟體於智慧財產法上的適格性議題。就此，本文將討論範圍限縮在專利法，先從技術角度剖析介紹人工智慧之內涵與發展，再從專利法立法目的切入，綜合各國規範見解與近期發布之相關審查指南分析其發明適格性，進一步討論當由人工智慧產生衍生之發明時，應如何進行權利主體之認定，以及其對於相關產業造成之利弊影響。
    Artificial intelligence (A.I.) such as face recognition, voice recognition, autopilot, etc., has become not only the sci-fi movie plots but been all over our lives. Although A.I. hasn’t been capable of thinking like a real human-being yet according to the technology known so far, scientists still keep working on breaking through the restrictions, making the artificial intelligence become an important assistant role in human life. It helps people during the research process, and can even become the independent inventor.
    Intellectual property law such as patent law, trademark law, and copyright law are enacted to encourage creation and invention. While the premise of the law protection above currently should be mental activity of human, in other words, “natural person” is the only subject of rights of creator and inventor. It may cause problems when A.I. starts to act like human and even be able to make the substantive features of the invention. Thus, it is essential to decide whether to enable the eligibility of subject of right of artificial intelligence in advance.
    In fact, the essence of A.I. is very similar to computer software. Besides the problems of subject of right mentioned above, the impact of A.I. on the current law system also evoked the issue of eligibility of computer software on intellectual property law once again. In this regard, this article limits the scope of discussion to the patent law, and introduce the connotation and development of A.I. from the technical point of view. After that, it will cut through the legislative purpose of the patent law, analyze the opinions and guidelines issued recently in different countries, and also the identification of the subject of rights and the pros and cons of related industries.
    參考文獻: 壹、 中文資料（按作者姓氏筆劃排序）
    一、 書籍
    1. 三宅陽一郎、森川幸人，從人到人工智慧：破解AI革命的68個核心概念，2017年5月。
    2. 李友專，AI醫療大未來：台灣第一本智慧醫療關鍵報告，2018年9月。
    3. 楊智傑，專利法，3版，2014年9月。
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    5. 鄭捷，自然語言處理：用人工智慧看懂中文， 2018年1月。
    6. 謝銘洋，智慧財產權法，8版，2018年9月。
    二、 專書論文
    1. 沈宗倫，人工智慧科技與智慧財產權法制的交會與調和，載：人工智慧相關法律議題芻議，頁177-214，2018年11月。
    三、 期刊論文
    1. 曲建仲，機器是如何學習與進步？人工智慧的核心技術與未來，科學月刊，580期，2018年4月。
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    6. 莊智惠，進步性判斷方式及論理之探討―以發明專利進步性審查基準修訂為例，智慧財產權月刊，225期，2017年9月。
    7. 陳龍昇，「自然法則」運用與個人化醫療診斷方法專利適格性判斷—從美國Mayo v, Prometheus案判決談起，高大法學論叢，11卷1期，2015年9月。
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    9. 謝銘洋，專利新穎性之認定—智慧財產法院行政判決98年度行專訴字第123號解析，法令月刊，61卷9期，2010年9月。
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    四、 學位論文
    1. 邱亮儒，由美國Alice v. CLS Bank案探討電腦軟體相關發明之專利適格性，國立中興大學科技法律研究所碩士論文，2016年6月。
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    五、 法院判決
    1. 智慧財產法院101年度民專上更(二)字第5號民事判決。
    2. 智慧財產法院102年度民專上字第23號民事判決。
    3. 智慧財產法院102年度民專上字第25號民事判決。
    4. 智慧財產法院105年度行專更(一)字第4號行政判決。
    5. 智慧財產法院106年度民專訴字第60號民事判決。
    6. 智慧財產法院106年度行專訴字第76號行政判決。
    7. 智慧財產法院98年度民專上字第39號民事判決。
    8. 最高行政法院103年度判字第406號判決。
    9. 最高行政法院105年度判字第503號行政判決。
    六、 官方文件
    1. 入出國自動查驗通關系統績效評估之研究－以臺灣桃園國際機場為例，內政部入出國及移民署自行研究報告，101年8月。
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    七、 網路資料
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    貳、外文資料（按作者首字母排序）
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    II. Book Chapters
    1. Abbott, Ryan, Hal the Inventor: Big Data and Its Use by Artificial Intelligence, in BIG DATA IS NOT A MONOLITH, 187 (Cassidy R. Sugimoto, Hamid Ekbia & Michael Mattioli eds., 2016).
    2. McCarthy, John. Programs with Common Sense, in COMPUTATION & INTELLIGENCE 479 (1995).
    3. Rumelhart, D.E. & Hinton, G.E. & Williams, R.J., 1 Learning internal representations by error propagation, in PARALLEL DISTRIBUTED PROCESSING: EXPLORATIONS IN THE MICROSTRUCTURE OF COGNITION 318 (1985).
    III. Conference Papers
    1. Bahdanau, Dzmitry & Cho, Kyunghyun & Bengio, Yoshua, Neural Machine Translation by Jointly Learning to Align and Translate, INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS (2015).
    2. Bakker, Bram, Reinforcement Learning with Long Short-Term Memory, ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS (2002).
    3. Baldi, Pierre, Autoencoders. Unsupervised Learning, and Deep Architectures, INTERNATIONAL CONFERENCE ON MACHINE LEARNING WORKSHOP ON UNSUPERVISED AND TRANSFER LEARNING (2012).
    4. Bengio, Yoshua & Courville, Aaron & Vincent, Pascal, Representation Learning: A Review and New Perspectives, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013).
    5. Ding, Yiming et al., A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain, 290 RADIOLOGY (2018).
    6. Goodfellow, Ian et al., Generative Adversarial Nets, 2014 NEURAL INFORMATION PROCESSING SYSTEMS (2014).
    7. Hochreiter, Sepp & Schmidhuber, Jürgen, Long Short-Term Memory, NEURAL COMPUTATION (1997).
    8. Kurach, Karol et al., The GAN Landscape: Losses, Architectures, Regularization, and Normalization, INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS (2019).
    9. Lu, Chaochao & Tang, Xiaoou, Surpassing Human-Level Face Verification Performance on LFW with GaussianFace, PROCEDDING OF THE 29TH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (2014).
    10. Mikolov, Tomas et al., Distributed Representations of Words and Phrases and Their Compositionality, ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS (2013).
    11. Moore, Gordon E., Progress in Digital Integrated Electronics, INTERNATIONAL ELECTRON DEVICES MEETING 11 (1975).
    12. Park, Taesung et al., Semantic Image Synthesis with Spatially-Adaptive Normalization, COMPUTER VISION AND PATTERN RECOGNITION (2019).
    13. Ting, DSW et al., Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes, JAMA (2017).
    14. Zhu, Jun-Yan et al., Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks, COMPUTER VISION AND PATTERN RECOGNITION (2018).
    15. Zoph, Barret & Le, Quoc V., Neural Architecture Search with Reinforcement Learning, INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS (2017).
    IV. Journal Papers
    1. Abbott, Ryan, I Think, Therefore I Invent: Creative Computers and the Future of Patent Law, 57 B.C. L. REV. 4, 10979 (2016).
    2. Abbott, Ryan, Patenting the output of autonomous inventive machine, 10 LANDSLIDE 16. (2017)
    3. Darrach, Brad., Meet Shakey, the First Electronic Person, LIFE MAGAZINE 58 (1970).
    4. Davies, Colin, An Evolutionary Step in Intellectual Property Rights - Artificial Intelligence and Intellectual Property, 27 COMPUTER LAW & SECURITY REVIEW 6, 601 (2011).
    5. DeCosta III, Frank A., Intellectual Property Protection for Artificial Intelligence, 24 WESTLAWESTLAW J. INTELLNTELL. PROPROP. 1 (2017).
    6. Denicola, Robert C., Ex machina: Copyright protection for computer-generated works, 69 RUTGERSUTGERS U. L. REVEV. 251 (2016)..
    7. Fraser, Erica, Computers as Inventors – Legal and Policy Implications of Artificial Intelligence on Patent Law, 13 SCRIPTed 3, 305 (2016).
    8. Gelernter, H. L. & Rochester N., Intelligent behavior in problem-solving machines, 2 IBM JOURNAL OF RESEARCH AND DEVELOPMENT 336 (1958).
    9. Hattenbach, Ben & Glucoft, Joshua, Patents in an Era of Infinite Monkeys and Artificial Intelligence, 19 STAN. TECH. L. REV. 32 (2015).
    10. Hodgkin, A. L. & Huxley, A. F., Action potentials recorded from Inside a nerve fibre, 144 NATURE 710 (1939).
    11. Hopfield, John, Neural networks and physical systems with emergent collective computational abilities, 79 PROC. NAT’L ACAD. SCI. U. S. A. 2554 (1982).
    12. Kohlhepp, Peter M., Note When the Invention Is an Inventor: Revitalizing Patentable Subject Matter to Exclude Unpredictable Processes, 93 MINN. L. REV. 795 (2008).
    13. LeCun, Y. et al., Backpropagation applied to handwritten zip code recognition, 1 NEURAL COMPUTATION 541 (1989).
    14. Lederberg, Joshua, How Dendral Was Conceived and Born, A HISTORY OF MEDICAL INFORMATICS 14 (1987).
    15. Lee, Edward, Digital Originality, 14 VAND. J. ENT. & TECH. L. 940 (2012).
    16. McCulloch, Warren S. & Pitts, Walter,. A Logical Calculus of the Ideas Immanent in Nervous Activity, 5 BULLETIN OF MATHEMATICAL BIOPHYSICS 115 (1943).
    17. Mnih, Volodymyr et al., Human-Level Control through Deep Reinforcement Learning, 518 NATURE 529 (2015).
    18. Pearlman, Russ, Recognizing Artificial Intelligence (AI) as Authors and Investors under U.S. Intellectual Property Law, 24 RICH. J. L. & TECH. 21 (2018).
    19. Ravid, Shlomit Y. & Liu, Xiaoqiong, When artificial intelligence systems produce inventions: an alternative model for patent law at the 3A era, 39 CARDOZO L. REV. 2215 (2018).
    20. Robinson, W. Keith & Smith, Joshua T., Emerging Technologies Challenging Current Legal Paradigms, 19 MINN. J.L. SCI. & TECH. 2, 355 (2018)..
    21. Rosenblatt, Frank., The perceptron: A probabilistic model for information storage and organization in the brain, 65 PSYCHOLOGICAL REVIEW 386 (1958).
    22. Samuelson, Pamela, Allocating Ownership Rights in Computer-Generated Works, 47 U. PITT. L. REV. 1185, 1207 (1985).
    23. Schuster, W. Michael, Artificial Intelligence and Patent Ownership, 75 WASH. & LEE L. REV., 1945 (2018).
    24. Searle, John,. Minds, Brains, and Programs, 3 BEHAVIORAL AND BRAIN SCIENCES 417 (1980).
    25. Shannon, Claude E., A Symbolic Analysis of Relay and Switching Circuits, 57 ELECTRICAL ENGINEERING 471 (1937).
    26. Silver, David et al., Mastering the game of Go with deep neural networks and tree search, 529 NATURE 484 (2016).
    27. Slagle, James R., A heuristic program that solves symbolic integration problems in freshman calculus: symbolic automatic integrator, 10 JOURNAL OF THE ACM 507 (1963).
    28. Smith, Gerald F., Beyond critical thinking and decision making: teaching business students how to think, 27 JOURNAL OF MANAGEMENT EDUCATION 24 (2003).
    29. Stern, Richard H., Alice v CLS Bank: US Business Method and Software Patents Marching towards Oblivion?, 36 EUR. INTELL. PROP. REVEV. 619 (2014)..
    30. Turing, Alan,. On Computable Numbers, with an Application to the Entscheidungs problem, 42 PROCEEDINGS OF THE LONDON MATHEMATICAL SOCIETY 230 (1937).
    31. Turing, Alan., Computing Machinery and Intelligence, 49 MIND 433 (1950).
    32. Vertinsky Liza & Rice, Todd M. (2002),. Thinking About Thinking Machines: Implications Of Machine Inventors For Patent Law, 8 B.U. J. SCI. & TECH. L., 574 (2002).
    33. Weizenbaum, Joseph,. ELIZA--A Computer Program For the Study of Natural Language Communication Between Man and Machine, 9 COMMUNICATIONS OF THE ACM 36 (1966).
    34. Wu, Andrew J. (1997),. From Video Games to Artificial Intelligence: Assigning Copyright Ownership to Works Generated by Increasingly Sophisticated Computer Programs, 25 AIPLA Q. J. 131 (1997).
    35. Young, Tom et al., Recent Trends in Deep Learning Based Natural Language Processing, IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2018).
    V. Cases
    1. Alice Corp. v. CLS Bank Int`l, 134 S. Ct. 2347 (2014);.
    2. BASCOM Global Internet Services v. AT&T MOBILITY, 827 F. 3d 1341 (Fed. Cir. 2016).
    3. BASCOM Global Internet Servs., Inc. v. AT&T Mobility LLC, 107 F.Supp.3d 650 (N.D. Tex. 2015)
    4. Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018).
    5. Berkheimer v. HP, Fed. Cir. No. 2017-1437 (May. 31, 2018);
    6. Bilski v. Kappos, 130 S. Ct. 3221 (2010).
    7. Blue Spike v. Google Inc., No. 2016-1054, 2016 U.S. App. LEXIS 20371 (Fed. Cir. 2016).
    8. Burroughs Wellcome Co. v. Barr Labs., Inc., 40 F.3d 1223, 1228 (Fed. Cir. 1994).
    9. CLS Bank Int’l v. Alice Corp., 685 F. 3d at 1352 (Fed. Cir. 2012).
    10. CLS Bank Int’l v. Alice Corp., 717 F. 3d 1269 (Fed. Cir. (2013)
    11. CLS Bank Int’l v. Alice Corp., 768 F. Supp.2d at 225 (2011).
    12. Core Wireless Licensing S.A.R.L. v. LG Electronics, Inc., 880 F.3d (Fed. Cir. 2018).
    13. DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245 (Fed. Cir. 2014).
    14. Enfish, LLC v. Microsoft Corp., 56 F.Supp.3d 1167 (C.D. Cal. 2014).
    15. Enfish, LLC v. Microsoft Corp., 822 F. 3d 1327 (Fed. Cir. 2016).
    16. EPO Case Number T 0489/14 (Feb. 22, 2019).
    17. EPO Case Number T 1358/09 (Nov. 21, 2014).
    18. Finjan, Inc. v. Blue Coat Systems, Inc., 879 F.3d (Fed. Cir. 2018).
    19. Glasswall Solutions Ltd. v. ClearSwift Ltd., 754 Fed. Appx. 996 (Fed. Cir. 2018).
    20. Gottschalk v. Benson, 409 U.S. (1972).
    21. Hybritech Inc. v. Monoclonal Antibodies, Inc., 802 F.2d 1367, 1376 (Fed. Cir. 1986),
    22. Iln re Bilski, 545 F.3d 943 (2008).
    23. Interval Licensing LLC v. AOL, Inc., Fed. Cir. No. 2016-2502 (Jul. 20, 2018);
    24. Mayo Collaborative v. Prometheus Labs., 132 S. Ct. 1289 (2012).
    25. McRO, Inc. v. Bandai Namco Games America Inc., 837 F. 3d 1314 (2016)
    26. Naruto v. Slater, 888 F.3d 418 (2018).
    27. Parker v. Flook, 437 U.S. (1978).
    28. PurePredictive, Inc., v. H2O.AI, Inc., Case No. 17-cv-03049-WHO. (N.D. Cal. Aug. 29, 2017).
    29. Smart Systems Innovations, LLC v. Chicago Transit Authority, Fed. Cir. No. 2016-1233 (Oct. 18, 2017).
    30. Vanda Pharmaceuticals Inc. v. West-Ward Pharmaceuticals, 887 F.3d 1117 (Fed. Cir. 2018).
    VI. Official Documents
    1. 2018 European Patent Convention Guidelines for Examination.
    2. European Patent Office, Case Law of the Boards of Appeal, 8th edition, 24, available at http://documents.epo.org/projects/babylon/eponet.nsf/0/5148B6F13CBE8990C1258017004A9EF6/$File/case_law_of_the_boards_of_appeal_2016_en.pdf (Last visited: 2019/06/17).
    3. European Patent Office, Patenting Artificial Intelligence Conference Summary (May 30, 2018), available at https://e-courses.epo.org/pluginfile.php/23523/mod_resource/content/2/Summary%20Artificial%20Intelligence%20Conference.pdf (Last visited: 2019/03/11).
    4. Japan Patent Office, Examination Handbook for Patent and Utility Model –Annex A, available at https://www.jpo.go.jp/e/system/laws/rule/guideline/patent/handbook_shinsa/document/index/app_a_e.pdf (Last visited: 2019/06/17).
    5. United States Patent and Trademark Office, 2019 Revised Patent Subject Matter Eligibility Guidance, available at https://www.federalregister.gov/documents/2019/01/07/2018-28282/2019-revised-patent-subject-matter-eligibility-guidance
    6. United States Patent and Trademark Office, Manual of Patent Examining Procedure, available at https://www.uspto.gov/web/offices/pac/mpep/index.html (Last visited: 2019/06/17).
    7. United States Patent and Trademark Office, MEMORANDUM (Apr. 19, 2018), available at https://www.uspto.gov/sites/default/files/documents/memo-berkheimer-20180419.PDF (Last visited: 2019/06/17).
    8. United States Patent and Trademark Office, MEMORANDUM (June. 07, 2018), available at https://www.uspto.gov/sites/default/files/documents/memo-vanda-20180607.PDF (Last visited: 2019/06/17).
    9. United States Patent and Trademark Office, MEMORANDUM, available at https://www.uspto.gov/sites/default/files/documents/memo-recent-sme-ctdec-20180402.PDF (Last visited: 2019/06/17).
    10. United States Patent and Trademark Office, Subject Matter Eligibility Examples: Abstract Ideas (Jan. 7, 2019), available at https://www.uspto.gov/sites/default/files/documents/101_examples_37to42_20190107.pdf (Last visited: 2019/07/02).
    11. United States Patent and Trademark Office, USPTO Performance and Accountability Report, 2, available at https://www.uspto.gov/sites/default/files/documents/USPTOFY18PAR.pdf (Last visited: 2019/04/22).
    12. World Economic Forum, Artificial Intelligence Collides with Patent Law (Apr. 2018), available at http://www3.weforum.org/docs/WEF_48540_WP_End_of_Innovation_Protecting_Patent_Law.pdf (Last visited: 2019/06/28).
    13. World International Property Organization, WIPO Technology Trends 2019: Artificial Intelligence, 42, available at https://www.wipo.int/edocs/pubdocs/en/wipo_pub_1055.pdf (Last visited: 2019/04/26).
    VII. Internet Source
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    9. Definition of: programmable computer, available at https://www.pcmag.com/encyclopedia/term/63683/programmable-computer (Last visited: 2019/06/05).
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    14. Facebook taps `deep learning` giant for new AI lab (Dec. 2013), available at https://www.wired.com/2013/12/facebook-yann-lecun/ (Last visited: 2019/05/19)
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    16. General Problem Solver, available at http://www.instructionaldesign.org/theories/general-problem-solver.html (Last visited: 2019/04/23).
    17. Goldman, David ,Google will become Alphabet today (Oct. 2015), available at https://money.cnn.com/2015/10/02/technology/google-alphabet/ (Last visited: 2019/04/27).
    18. Google buys UK artificial intelligence start-up DeepMind (Jan 2014), available at https://www.bbc.com/news/technology-25908379;
    19. Google Has Bought A Startup To Help It Recognize Voices And Objects (Mar 2014), available at https://www.businessinsider.com/google-buys-dnnresearch-2013-3 (Last visited: 2019/05/19).
    20. Google`s AlphaGo clinches series win over Chinese Go master, REUTERS (May 25, 2017), available at https://www.reuters.com/article/us-science-intelligence-go/googles-alphago-clinches-series-win-over-chinese-go-master-idUSKBN18L0LH.
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    22. Hussain, Shadab, Use cases of Different Machine Learning Algorithms, available at https://blog.usejournal.com/machine-learning-algorithms-use-cases-72646df1245f (Last visited: 2019/05/19).
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    26. Korenberg, Alexander, Kilburn & Strode, Assessing the EPO’s new guidelines on AI (Dec. 03, 2018). available at https://www.ipstars.com/articles/assessing-the-epos-new-guidelines-on-ai/arjvptju. (Last visited: 2019/06/28).
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    描述: 碩士
    國立政治大學
    法律科際整合研究所
    1056520011
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G1056520011
    数据类型: thesis
    DOI: 10.6814/NCCU201900818
    显示于类别:[法律科際整合研究所] 學位論文

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