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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 黃銘傑(Ming-Jye Huang) | |
dc.contributor.author | Wen-I Chang | en |
dc.contributor.author | 張文憶 | zh_TW |
dc.date.accessioned | 2021-05-20T00:51:02Z | - |
dc.date.available | 2020-08-21 | |
dc.date.available | 2021-05-20T00:51:02Z | - |
dc.date.copyright | 2020-08-21 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-08-11 | |
dc.identifier.citation | 參考文獻 一、 中文部分 (一) 書籍 邱文聰(2018),⟨初探人工智慧中的個資保護發展趨勢與潛在的反歧視難題⟩,載於劉靜怡(主編),《人工智慧相關法律議題芻議》(152-180頁)。臺北:元照。 財團法人金融聯合徵信中心(2017),《歐盟個人資料保護規則》。臺北:金融聯合徵信。 張陳弘,莊植寧(2019),《新時代之個人資料保護法制:歐盟GDPR與臺灣個人資料保護法的比較說明》。臺北:新學森。 黃繼兒(2017),《注意!這是我的個人資料隱私》。香港:香港城市大學。 羅伯特‧席爾(著),林麗雪(譯)(2020),《隱私危機》。臺北:好優文化。(原著出版年:2016年) (二) 期刊 王志誠(2006),〈美國金融隱私權保護法制之發展〉,《台灣金融財務季刊》,7輯1期,頁71-90。 何明諠(2016),〈數位時代的隱私邊界:以健保資料庫與 ETC 交通資料庫為例〉,《台灣人權學刊》,3卷4期,頁139-153。 林其樺(2016),〈個人資料保護、利用與匿名化-歐盟法制趨勢觀察〉,《科技法律透析》,28卷6期,頁35-42。 林其樺(2017),〈數位浪潮:由歐盟個人資料管理制度與英國匿名化探索資料合理使用〉,《科技法律透析》,29卷1期,頁17-25。 林錦郎、卓麗香、張松山(2017),〈資訊隱私機制與信任對Facebook社群網站使用者行為意圖影響之研究〉,《全球商業經營管理學報》,9期,頁13-25。 范姜真媺(2016),〈網路時代個人資料保護之強化–被遺忘權利之主張〉,《興大法學》,19期,頁61-106。 翁清坤(2013),〈告知後同意與消費者個人資料之保護〉,《臺北大學法學論叢》,87 期,頁217-322。 張志偉(2016),〈記憶或遺忘,抑或相忘於網路——從歐洲法院被遺忘權判決,檢視資訊時代下的個人資料保護〉,《政大法學評論》,148期,頁1-68。 張志偉(2017),〈從資訊自決與資訊隱私的概念區分,檢視被遺忘權的證立問題〉,《萬國法律》,211期,頁2-15。 張陳弘(2018),〈新興科技下的資訊隱私保護:「告知後同意原則」的侷限性與修正方法之提出〉,《臺大法學論叢》,47卷1期,頁201-297。 許炳華(2016),〈大數據時代下隱私權之保護-可能之影響暨對策〉,《興大法學》,20期,頁129-191。 郭戎晉(2012),〈論數位環境下個人資料保護法制之發展與難題–以「數位 足跡」之評價為核心〉,《科技法律透析》,24卷4 期,頁18-40。 郭明煌、廖鴻圖、蕭麗齡、王亭雅(2014),〈資訊隱私顧慮對社群網站使用者使用意圖影響之研究-以Facebook為例〉,《資訊管理學報》,21卷4期,頁341-363。 葉志良(2016),〈大數據應用下個人資料定義的檢討:以我國法院判決為例〉,《資訊社會研究》,31期,頁1-36。 葉志良(2018),〈因應物聯網發展資料保護法制的革新──歐盟法制的發展與啟示〉,《中原財法學》,40期,頁61-127。 詹文凱(1999),〈美國法上個人資訊隱私權的相關判決〉,《律師雜誌》,233期,頁30-40。 劉定基(2013),〈析論個人資料保護法上「當事人同意」的概念〉,《月旦法學雜誌》,218期,頁146-167。 劉定基(2017),〈大數據與物聯網時代的個人資料自主權〉,《憲政時代》,42 卷3 期,頁265-308。 劉靜怡(2002),〈網際網路時代的資訊使用與隱私權保護規範:個人、政府與市場的拔河〉,《資訊管理研究》,4卷3期,頁137-161。 劉靜怡(2010),〈雲端運算趨勢與個人資訊隱私保護〉,《全國律師》,14 卷,2 期,頁1-14。 劉靜怡(2012),〈社群網路時代的隱私困境:以 Facebook 為討論對象〉,《台大法學論叢》,41卷1期,頁1-70。 賴祥蔚(2010),〈商業言論與憲法的言論自由保障〉,《台灣政治學刊》,14卷1期,頁159-199。 簡奕寬(2018),〈資料隱私市場與管制政策方向初探〉,《科技法律透析》,30 卷 7期,頁33-38。 顏于嘉(2017),〈由美國資訊隱私法制觀察被遺忘權在美國的發展〉,《萬國法律》,211期,頁25-33。 羅鈺珊(2018),〈數據經濟下共融成長的挑戰:大數據的兩面刃〉,《經濟前瞻》,178期,頁87-93。 蘇慧婕(2016),〈歐盟被遺忘權的概念發展–以歐盟法院 Google Spain v. AEPD 判決分析為中心〉,《憲政時代》,41卷4期,頁473-516。 (三) 論文 李誠偉(2015)。《巨量資料產生的刑事爭議-以資訊隱私權為核心》。私立東吳大學法律學系法律專業組碩士論文。 張幼文(2018)。《健康資料之個人資料類別屬性研究—以 IoT 設備之蒐集、處理或利用為中心》。國立政治大學科技管理與智慧財產研究所碩士論文。 張容涵(2018)。《從比較法觀點探討我國個資保護制度之轉型》。國立臺灣大學法律學研究所碩士論文。 陳裕涵(2013)。《網路空間中之隱私權保–以社群網站為中心》。國立台灣大學法律學研究所碩士論文。 黃亦莙(2017)。《物聯網時代隱私權問題探討以平衡科技發展與個人資料保護為中心》。國立中央大學產業經濟研究所碩士論文。 劉翛然(2018)。《論社交軟體個人資料之權利性質及其保護》。私立東吳大學法學院法律學系碩士論文。 賴羿慈(2017)。《個人資料保護法制中研究例外規定之比較分析》。國立清華大學科技法律研究所碩士論文。 謝怡均(2018)。《個資法上被遺忘權之研究─從歐盟法出發》。國立中興大學法律學系碩士班學位論文。 鍾孝宇(2017)。《巨量資料與隱私權—個人資料保護機制的再思考》。國立政治大學法律學系碩士班碩士論文。 二、 外文部分 (一) 書籍 Bamberger, K. A. Mulligan, D. K. (2015). Privacy on the Ground. Massachusetts: MIT Press. Bok, S. (1983). Secrets: On The Ethics of Concealment and Revelation. New York: Vintage Books. Ghezzi, A. et al. (2014). The Ethics of Memory in a Digital Age: Interrogating the Right to be Forgotten. London, UK: Palgrave Macmillan. Goffman, E. (1959). The Presentation of Self in Every Day Life. New York: Doubleday. Golbeck, J. (2020). Taking Control of Your Personal Data. Virginia: The Teaching Company. Greenleaf, G. (2014). Asian Data Privacy Laws: Trade Human Rights Perspectives. Oxford, England: Oxford University Press. Retrieved 28 Jun. 2020, from https://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199679669.001.0001/acprof-9780199679669 Hoofnagle, C. J. (2016). Federal Trade Commission Privacy Law and Policy. Cambridge, UK: Cambridge University Press. Mayer-Sho ̈nberger, V. (2011). Delete: The Virtue of Forgetting in the Digital Age. New Jersey: Princeton University Press. O’Brien, D. M. (1979). Privacy, Law, And Public Policy. New York: Praeger Publishers. OECD (2002). OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data. Paris, France: OECD Publishing. Ricoeur, P. (2004). Memory, History, Forgetting, Chicago. Illinois: The University of Chicago Press. Rosen, J. (2000). The Unwanted Gaze: The Destruction of Privacy in America. New York: Vintage Books. Rosen, J. (2012). Privacy, Property, and Free Speech: Law and the Constitution in the 21st Century. Virginia: The Teaching Company. Rosenzweig, P. (2016). The Surveillance State Big Data, Freedom, and You, The Great Courses. Virginia: The Teaching Company. Smith, H. J. (1994). Managing Privacy: Information Technology and Corporate America. North Carolina: The University of North Carolina Press. Solove, D. J. Schwartz, P. M. (2011). Information Privacy Law (4th ed.). Illinois: Aspen Publishers. Solove, D. J. Schwartz, P. M. (2017). Privacy Law Fundamentals (4th ed.). New Hampshire: International Association of Privacy Professionals. Solove, D. J. (2004). The Digital Person. New York: NYU Press. Available at SSRN: https://ssrn.com/abstract=2899131 Waldman, A. E. (2018). Privacy as Trust: Information Privacy for an Information Age. (1st ed.). Cambridge, UK: Cambridge University Press. Waldman, A. F. (2018). Privacy as Trust: Information Privacy for an Information Age, New York: Cambridge University Press. Westin, A. F. (1967). Privacy and Freedom. New York: Atheneum. Zetonny, D. (2019). California Consumer Privacy Act (CCPA) Practical Guide, Bryan Cave Leighton Paisner LLP. (二) 期刊 Bagnoli, V. (2015). Competition for the Effectiveness of Big Data Benefits. International Review of Intellectual Property and Competition Law, 46(6), 629-631. Balkin, J. M. (2016). Information Fiduciaries and the First Amendment. UC Davis Law Review, 49, 1183-1234. Ball, D. W. (1975). Privacy, Publicity, Deviance and Control. Pacific Sociological Review, 18(3), 259-278. Bates, A. P. (1964). Privacy – A Useful Concept? Social Forces, 42, 429-434. Ben-Shahar, O. Schneider, C. E. (2011). The Failure of Mandated Disclosures. University of Pennsylvania Law Review, 159, 647-749. Bruening, P. J. Mary J. Culnan, M. J. (2016). Through a Glass Darkly: From Privacy Notices to Effective Transparency. North Carolina Journal of Law and Technology, 17(4), 515-580. Chirica, S. (2017). The Main Novelties and Implications of the New General Data Protection Regulation. Perspective Business Law Journal, 6(1), 159-176. Cohen, J. L. (2001). The Necessity of Privacy. Social Research, 68, 318-327. de Hert, P., Papakonstantinou, V. (2016). The new general data protection regulation: Still a sound system for the protection of individuals. Computer Law and Security Review, 32, 179–194. Determann, L. (2018). No One Owns Data. Hastings Law Journal, 70(1), 1-44. Dobkin, A. (2018). Information Fiduciaries in Practice: Data Privacy and User Expectations. Berkeley Technology Law Journal, 33(1), 1-50. Parker, E. S., Cahill, L., Mcgaugh, J. L. (2006). A Case of Unusual Autobiographical Remembering. Neurocase, 12(1), 35-49. Everson, E. (2016). Privacy by Design: Taking Control of Big Data. Cleveland Stata Law Review, 65, 27-43. Fried, C. (1968). Privacy. The Yale Law Journal, 77(3), 475-493. Gleibs I. H. (2014). Turning Virtual Public Spaces Into Laboratories: Thoughts On Conducting Online Field Studies Using Social Network Sites. Analyses of Social Issues and Public Policy, 14(1), 352-370. Gleibs I. H. (2014). Turning virtual public spaces into laboratories: thoughts on conducting online field studies using social network sites. Analyses of Social Issues and Public Policy, 14(1), 352-370. Harold, D. (2006). The Implied Covenant of Good Faith in Contract Interpretation and Gap-Filling: Reviling a Revered Relic. St. John's Law Review, 80(2), 559–620. Hartzog, W. Selinger, E. (2013). Big Data in Small Hands. Stanford Law Review Online, 66, 81-88. Hirsch, D. (2011). The Law and Policy of Online Privacy: Regulation, Self- Regulation, or Co-Regulation? Seattle University Law Review, 34, 439-480. Hoecke, M. V. (2015). Methodology of Comparative Legal Research. Retrieved from https://www.bjutijdschriften.nl/tijdschrift/lawandmethod/2015/12/RENM-D-14-00001 Jennings, M. (2012). To Track Or Not To Track: Recent Legislative Proposals To Protect Consumer Privacy. Harvard Journal on Legislation, 49(1), 193-206. Available at SSRN: https://ssrn.com/abstract=2074376 Jerome, J. (2015). Big Data: Catalyst for a Privacy Conversation. Indiana Law Review, 48, 213-242. Joh, E. E. (2016). The New Surveillance Discretion: Automated Suspicion, Big Data, and Policing. Harvard Law Policy Review, 10, 15-42. Joyce, D. (2015). Privacy in the Digital Era: Human Rights Online. Melbourne Journal of International Law, 16(1), 270-285. Kateb, G. (2001). On Being Watched and Known. Social Research, 68, 269-298. Kerr, O. S. (2012). The Mosaic Theory of the Fourth Amendment. Michigan Law Review, 111(3), 311-354. Matthews, S. (2010). Anonymity and The Social Self. American Philosophical Quarterly, 47(4), 351-363. Nissenbaum, H. (2004). Privacy as Contextual Integrity. Washington Law Review, 79, 101-139. Nissenbaum, H. (2011). A Contextual Approach to Privacy Online. Daedalus, 140(4), 32-48. Pagallo, U. (2017). The Legal Challenges of Big Data: Putting Secondary Rules First in the Field of EU Data Protection. European Data Protection Law Review, 3(1), 36-46. Penn, J. (2012). Behavioral Advertising: The Cryptic Hunter and Gatherer of the Internet. Federal Communications Law Journal, 64(3), 599-616. Politou, E., Alepis, E., Patsakis, C. (2018). Forgetting Personal Data and Revoking Consent Under The GDPR: Challenges And Proposed Solutions. Journal of Cybersecurity, 4(1), 1-20. Radin, M. J. (2006). A Comment on Information Propertization and Its Legal Milieu. Cleveland State Law Review, 54, 23-39. Reiman, J. H. (1976). Privacy, Intimacy and Personhood. Philosophy and Public Affairs, 6(1), 26-44 (1976). Richards, N. Hartzog, W. (2016). Taking Trust Seriously in Privacy Law. Stanford Technology Law Review, 19, 431-472. Rubinstein, I.S., Lee, R.D., Schwartz, P.M. (2008). Data Mining and Internet Profiling: Emerging Regulatory and Technological Approaches. The University of Chicago Law Review, 75, 261-285. Schaar, P. (2010). Privacy by Design. Identity in The Information Society, 3, 267-274. Schwartz, P. M. (2019). Global Data Privacy: The EU Way, Forthcoming. New York University Law Review, 94, 771-818. Selbst, A. D. Powles, J. (2017). Meaningful Information and the Right to Explanation. International Privacy Law, 7(4), 233-242. Solove, D. J. Hartzog, W. (2014). The FTC and the New Common Law of Privacy. Columbia Law Review, 114, 583-676. Spiekermann, S. Novotny, A. (2015). A Vision for Global Privacy Bridges: Technical and Legal Measures For International Data Markets. Computer Law Security Review. Available at SSRN: https://ssrn.com/abstract=3599993 Volokh, E. (2000). Freedom of Speech and Information Privacy: The Troubling Implications of a Right to Stop People from Speaking About You. Stanford Law Review, 52, 1-65. Warren, S. D. Brandeis, L. D. (1890). The Right to Privacy. Harvard Law Review, 4(5), 193-220. White H. B. (1951). The Right to Privacy. Social Research, 18(2), 171-202. Yanisky-Ravid, S. Hallisey, S. K. (2019). Equality and Privacy by Design: A New Model of Artificial Intelligence Data Transparency via Auditing, Certification, and Safe Harbor Regimes. Fordham Urban Law Journal, 46(2), 428-486. 三、 網路資料 32nd Int’l Conference of Data Prot. Privacy Comm’rs, Resolution on Privacy by Design 1-2 (2010). Retrieved from https://secure.edps.europa.eu/EDPSWEB/webdav/site/mySite/shared/Documents/Cooperation/Conference_int/10-10-27_Jerusalem_Resolutionon_PrivacybyDesign_EN.pdf. Kramer, A. D., Guillory, J. E. Hancock, J. T. (2014). Experimental Evidence Of Massive-Scale Emotional Contagion Through Social Networks. Proceedings of the National Academy of Sciences, PNAS, 111(24), 8788-8790. Retrieved from https://www.pnas.org/content/pnas/111/24/8788.full.pdf Cavoukian, A. (2009). Privacy by Design: The 7 Foundational Principles. Retrieved from https://www.ipc.on.ca/wp-content/uploads/resources/7foundationalprinciples.pdf Article 29 Data Protection Working Party (WP29), Opinion 10/2004 on More Harmonised Information Provisions, v (Nov. 25, 2004), available at www.statewatch.org/news/2004/dec/wp100.pdf. Malle, B., Kieseberg, P., Weippl, P. Holzinger, A. (2016). The Right to Be Forgotten: Towards Machine Learning on Perturbed Knowledge Bases. International Conference on Availability, Reliability, and Security (CD-ARES), Aug 2016, Salzburg, Austria. pp.251-266, ff10.1007/978-3-319-45507-5_17ff. ffhal-01635002f. Retrieved from https://hal.inria.fr/hal-01635002/document Blasé Ur it al. (July, 2012). Smart, Useful, Scary, Creepy: Perceptions of Online Behavioral Advertising. Retrieved from https://cups.cs.cmu.edu/soups/2012/proceedings/a4_Ur C.G. Lynch, A Wake-Up Call for Users in Facebook-Beacon Controversy, CIO. https://www.cio.com/article/2437512/a-wake-up-call-for-users-in-facebook-beacon-controversy.html CyLab Usable Privacy and Security Laboratory. Retrieved from http://cups.cs.cmu.edu/ Castro, D. and McQuinn A. (2018). AI Offers Opportunity to Increase Privacy for Users, International Association of Privacy Professionals. Retrieved from https://iapp.org/news/a/ai-offers-opportunity-to-increase-privacy-for-users/ Dastin, J. (October 9, 2018). Amazon Scraps Secret AI Recruiting Tool That Showed Bias against Women. Reuters. Retrieved from https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the Legal Protection of Databases, 1996 O.J. (L 77) 20. https://op.europa.eu/en/publication-detail/-/publication/b48976b5-b31a-4dba-a052-87133e17d65e/language-en. European Charter of Fundamental Rights. Article 8 Protection of Personal Data states, “Everyone has the right to the protection of personal data concerning him or her.” https://www.europarl.europa.eu/charter/pdf/text_en.pdf European Commission, ARTICLE 29 DATA PROTECTION WORKING PARTY. (2018). Guidelines on Consent under Regulation 2016/679. Retrieved from https://ec.europa.eu/newsroom/article29/item-detail.cfm?item_id=623051 European Commission, ARTICLE 29 DATA PROTECTION WORKING PARTY. (2017). Guidelines on Automated Individual Decision-making and Profiling for the Purposes of Regulation 2016/679, Retrieved from https://ec.europa.eu/newsroom/article29/item-detail.cfm?item_id=612053 European Commission, ARTICLE 29 DATA PROTECTION WORKING PARTY. (2014). Statement on the Role of a Risk-based Approach in Data Protection Legal Frameworks. Retrieved from https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/file s/2014/wp218_en.pdf European Commission, ARTICLE 29 DATA PROTECTION WORKING PARTY. (2017). Guidelines on Data Protection Impact Assessment (DPIA) and Determining whether Processing is “likely to result in a high risk” for the Purposes of Regulation 2016/679. Retrieved from https://ec.europa.eu/newsroom/article29/itemdetail.cfm?item_id=611236 FTC (2010). Protecting Consumer Privacy in an Era of Rapid Change: A Proposed Framework for Business and Policymakers. Retrieved from https://www.ftc.gov/sites/default/files/documents/reports/federal-trade-commission -bureau-consumer-protection-preliminary-ftc-staff-report-protecting-consumer/101 201privacyreport.pdf FTC (2000). Privacy Online: Fair Information Practices in the Electronic Marketplace, A Report to Congress. Retrieved from https://www.ftc.gov/sites/default/files/documents/reports/privacy-online-fair-infor mation-practices-electronic-marketplace-federal-trade-commissionreport/privacy2 000text.pdf Nietzsche, F. (1874), On The Use And Abuse Of History For Life. (Translated by Ian Johnston, Vancouver Island University, Nanaimo, BC, Canada). Retrieved from https://pdfs.semanticscholar.org/6784/b376131703bcfa6458f48ee005ae75b8f4fa.pdf?_ga=2.226574301.1793891829.1593310936-1947095177.1593310936 http://la.utexas.edu/users/hcleaver/330T/350kPEENietzscheAbuseTableAll.pdf FTC, Big Data: A Tool For Inclusion Or Exclusion?: Understanding The Issues (2016), available at https://www.ftc.gov/system/files/documents/reports/big-data-tool-inclusion-or-exclusion-understanding-issues/160106big-data-rpt.pdf. Gentry, C. (2009). Fully Homomorphic Encryption Using Ideal Lattices. In Proceedings of The Forty-First Annual ACM Symposium on Theory of Computing (STOC ’09). Association for Computing Machinery, New York, NY, USA, 169–178. Retrieved from https://dl.acm.org/doi/10.1145/1536414.1536440 Fowler, G. A. (May 28, 2019). It’s the Middle of the Night. Do You Know Who Your iPhone Is Talking To? The Washington Post. Retrieved from https://www.washingtonpost.com/technology/2019/05/28/its-middle-night-do-you-know-who-your-iphone-is-talking/ Haskins, C. (December 20, 2018). Amazon Sent 1,700 Alexa Recordings to the Wrong Person. VICE. Retrieved from https://www.vice.com/en_us/article/pa54g8/amazon-sent-1700-alexa-recordings-to-the-wrong-person Helft, M. (July 4, 2008). Google Told to Turn Over User Data of YouTube. The New York Times. Retrieved from https://www.nytimes.com/2008/07/04/technology/04youtube.html?searchResultPosition=2 Item No.141 of European Data Protection Supervisor, “Opinion of the EDPS on the data protection reform package”. Retrieved from https://edps.europa.eu/sites/edp/files/publication/12-03-07_edps_reform_package_en.pdf Kaye, J., Curren, L., Anderson, N., Edwards, K., Fullerton, S. M., Kanellopoulou, N., Lund, D., MacArthur, D. G., Mascalzoni, D., Shepherd, J., Taylor, P. L., Terry, S. F., Winter, S. F. (2012). From patients to partners: participant-centric initiatives in biomedical research. Nature reviews. Genetics, 13(5), 371–376. Retrieved from https://pubmed.ncbi.nlm.nih.gov/22473380/ Meyer, R. (June 28, 2014). Everything We Know about Facebook’s Secret Mood Manipulation Experiment. The Atlantic. Retrieved from https://www.theatlantic.com/technology/archive/2014/06/everything-we-know-about-facebooks-secret-mood-manipulation-experiment/373648/ Malle, B. et al. (2016). The right to be forgotten: towards machine learning on perturbed knowledge bases. International Conference on Availability, Reliability, and Security, 251–266 (2016). Retrieved from file:///Users/brian15/Downloads/PAML.pdf Wallace, N. and Castro, D. (2018). The Impact of the EU’s New Data Protection Regulation on AI. Center For Data Innovation. Retrieved from http://www2.datainnovation.org/2018-impact-gdpr-ai.pdf President’s Council of Advisors on Science and Technology, Big Data and Privacy: A Technological Perspective (2014). Retrieved from https://bigdatawg.nist.gov/pdf/pcast_big_data_and_privacy_-_may_2014.pdf Privacy Online: Fair Information Practices in Electronic Marketplace: Prepared Statement of the Fed. Trade Comm’n Before the S. Comm. On Commerce, Sci., Transps. (May 25, 2000). Retrieved from https://www.ftc.gov/sites/default/files/documents/reports/privacy-online-fair-information-practices-electronic-marketplace-federal-trade-commission-report/privacy2000.pdf Records, Computers and the Rights of Citizens: Report of the Secretary’s Advisory Committee on Automated Personal Data Systems, U.S. Department of Health Education and Welfare. Retrieved from http://epic.org/privacy/hew1973report/default.html Center for Democracy and Tech (Jan. 28, 2010). The Role of Privacy by Design in Protecting Consumer Privacy. Retrieved from https://cdt.org/insights/the-role-of-privacy-by-design-in-protecting-consumer-privacy-1/ 國家發展委員會,⟪歐盟個人資料保護規則本文部分⟫,載於: https://ws.ndc.gov.tw/Download.ashx?u=LzAwMS9hZG1pbmlzdHJhdG9yLzEwL3JlbGZpbGUvMC8xMTY5MS9iNGZiZTA0OS1jYWQ1LTQ3MGEtYjhlMy00ZGU0NjhmOWIxMGMucGRm n=5q2Q55uf5YCL5Lq66LOH5paZ5L%2bd6K236KaP5YmH5pys5paH6YOo5YiGLnBkZg%3d%3d icon=..pdf 國家發展委員會,⟪歐盟個人資料保護規則前言部分⟫,載於: https://ws.ndc.gov.tw/Download.ashx?u=LzAwMS9hZG1pbmlzdHJhdG9yLzEwL3JlbGZpbGUvMC8xMTY5MS8wNzMwYmJkZC0yNTVjLTRhN2MtYjc5NS1hMWQ5ODY3OTEwYTYucGRm n=5q2Q55uf5YCL5Lq66LOH5paZ5L%2bd6K236KaP5YmH5YmN6KiA6YOo5YiGKFJlY2l0YWxzKS5wZGY%3d icon=..pdf | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8269 | - |
dc.description.abstract | 在傳統以自主、自治、自決理論為基礎的隱私規範下,各國資訊隱私法規紛紛以建置個資當事人「通知與選擇」機制為規範主軸,所規範者多著重於規定通知個資當事人之方式、應通知之內容、個資當事人選擇或同意的方式以及同意的範圍等。然而,隨著網路科技的快速發展,人民的基礎生活不但越來越依賴資訊網路,甚至在某些情形下因為產業趨勢或政府力推電子化政策的結果,人民的許多日常生活機能幾乎已離不開網路,那麼,人民是否真能自主「選擇」揭露其資訊呢?又在大數據與人工智慧AI技術的蓬勃發展下,資訊的應用透過程式演算法自動學習與擴大運用,同時業者間錯縱複雜的合縱連橫合作關係,導致個資當事人即使收悉資訊蒐集者的「通知」,他(她)不但無法即時消化冗長的隱私政策內容,也無法自行評估未來資訊應用所可能產生的實際風險,且由於營業秘密法的保護,人民並無法獲悉與監督資訊蒐集者對其資訊的實際利用狀況。有不少論者即推估,在現行的資訊隱私規範下,個資隱私的未來將往兩個極端的方向發展,一是未來將沒有個資隱私。這是因為當人民習慣性地揭露個資,習慣性地不審視與評估風險,科技的發展使大數據應用越見容易拼湊完整的個人資訊,並能輕易跨境跨領域的傳輸與利用,未來個資將無所不在;或者,二是未來AI大數據的發展將受到嚴重阻礙。因為當人民對資訊控制者的個資處理與保護失去信任,人民將傾向不揭露個資,導致資訊流通受到束縛,在沒有足夠的基礎資訊下,AI大數據分析亦將難以精確地運算與發展。 傳統隱私規範之目的是否真同於資訊隱私之規範目的?究竟人類社會應首重保護個資還是應以鼓勵資訊交流為目標?GDPR的硬性規定究是有益或有害資訊科技發展?軟性規範是否更適合資訊隱私所遇到的困境?本文藉由資訊揭露本質的分析討論,輔以大數據應用世代生活上的實際案例與經驗,以及資訊揭露者與蒐集者間存在長期被忽略的信任關係等討論,推導資訊蒐集者在資訊隱私議題所應當扮演的角色與應擔負的責任,並建議資訊隱私規範應以資訊信託的角度來立法,輔以設計隱私等軟性規範,俾能同時保護個資隱私與促進大數據與AI科技的發展,應用科技增進人類福祉。 | zh_TW |
dc.description.abstract | Based upon the traditional concept of privacy which derived from the theory of democracy, autonomy and self-determination, data privacy laws in most of modern countries emphasize on the establishment of a comprehensive notice-and-choice mechanism, which ordinarily include the ruling of means of notices, content of notices, meaningful ways of choices and agreements, the scope of agreements and so forth. However, as the speedy development in internet technologies, not only does people’s daily life heavily rely upon information technology, but also people in the modern age are more and more often forced to carry out their life tasks in electronic ways because of industrial trend or governmental policies of digitalization. In such circumstances, can people really discretionally “choose” to or not to disclose their personal information? Moreover, as quick development in big data and artificial intelligence (AI) technology, the ways of information application are sophistically adopted by AI algorithm which may learn and improve by itself. Accompanied by the complicated inter-industry data sharing scheme, data subjects usually are not capable of comprehending the actual utilization after and risk of information disclosure, even if they are noticed with lengthy information privacy policies by the data collectors. Furthermore, under the protection of trade secret laws, ordinary people don’t have the access to the big data analysis algorithms and application techniques adopted by data controllers, thus people cannot monitor the actual processing of their information. Consequently, many scholars predict that the future of data privacy will eventually either become no privacy at all, on the cause that people will gradually be used to reveal their personal information without trying to evaluate the risks, which provides the AI with the opportunities of easily analyzing big data to identify any person; or hinder AI and big data technology from further development, on the cause that when people lose trust on data collectors and begin to suspect that their interests may be harmed, people will cease providing their personal data, which will curtail free flow of data and AI technology won’t be able to rely upon precise raw data in developing useful functions for the benefit of our society in the future. Whether the purposes of traditional privacy regulations are identical to that of information privacy? Whether our society would be more beneficial by focusing on blind protection of personal data or by facilitating free data transmissions? Whether soft regulations would be a more appropriate resolution for issues of information privacy than hard, rigid regulations? Through the analysis of nature of information disclosure, accompanied by practical real life cases, experience in the era of big data application and the relations between information disclosers and receivers, this thesis suggests that data collectors shall act as the role of information trust, and information privacy regulations shall be re-designed from the perspective of information trust which may be practically implemented by privacy-by-design concept in order to achieve both goals of privacy protection and stimulating development of big data and AI technologies. Consequently, our society may well take advantage of big data and AI technologies in improving general welfare of humanity. | en |
dc.description.provenance | Made available in DSpace on 2021-05-20T00:51:02Z (GMT). No. of bitstreams: 1 U0001-1008202018211000.pdf: 2511987 bytes, checksum: 6af06868fa15e0ef1c97fa3ee37641f0 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 口試委員會審定書 I 中文摘要 II ABSTRACT III 目錄 V 第一章 緒論 1 第一節 研究動機 1 第二節 研究方法 5 第三節 研究架構 6 第四節 名詞定義及補充說明 7 第二章 傳統資訊隱私規範的立法基礎 9 第一節 社會對「隱私」的傳統定義影響「資訊隱私」規範的制定 9 第一項 視隱私為個人「私密而免於受干擾」的基本權(消極的保護) 11 第二項 視隱私權為確保個人對其資訊「主宰操控與自治」的權利(積極的保護) 14 第二節 對以「主宰控制、管理」為基礎資訊隱私權規範的批評 16 第三節 個資是否應以新財產權規範? 17 第一項 個資在傳統財產權下所受的保護程度 18 第二項 為個資創造專屬財產權可能產生的問題 22 第四節 言論自由與資訊隱私規範的衝突與調和 24 第一項 網路業者對個資的使用是否受言論自由的保護? 24 第二項 商業言論(Commercial Speech)論點 25 第三項 合約約束模式觀點 26 第四項 加諸個資控制者資訊受託義務責任是否即侵害其言論自由? 28 第五項 被遺忘權(Right to be Forgotten)與言論自由 30 第六項 保護智慧財產權規範對言論自由的挑戰 32 第五節 通知與選擇(notice-and-choice)規範主流的形成 33 第三章 美國與歐盟資訊隱私規範概述 37 第一節 美國資訊隱私規範 37 第二節 歐盟資訊隱私規範 41 第三節 美國與歐盟資訊隱私規範下產生的若干差異 48 第四節 歐盟式規範對大數據人工智慧產業發展的衝擊 51 第四章 資訊揭露的基礎來自對資訊蒐集者的「信任」 56 第一節 通知與選擇(notice-and-choice)機制的利與弊 56 第一項 個人無從判斷風險 58 第二項 選擇退出(Opt-Out)與選擇參加(Opt-in) 63 第三項 同意、撤回同意與刪除權所帶來的困窘 65 第四項 科技網路與大數據資訊利用的特性 67 第二節 社會社交觀點理論下的資訊隱私 72 第一項 人際社交與資訊隱私的關係 72 第二項 依據個資當事人與個資蒐集者的「關係」來辯識資訊的隱私性質 74 第三項 資訊隠私意識的本質應包含資訊揭露當下之背景條件 (Context) 75 第三節 資訊蒐集者建立個資當事人「信任」的意義 77 第四節 以「信任」為基礎建立資訊隱私規範 80 第一項 「侵害資訊隱私」在以「權力」及「信任」為基礎資訊隱私規範下的意義 80 第二項 以信任為基礎的資訊隱私 83 第三項 強化資料受託者的受託義務(Fiduciary Duty) 84 第四項 以信託為基礎規範資訊隱私的優勢 92 第五節 Privacy by Design 93 第一項 基本意義 93 第二項 國際資訊隱私法規範相關Privacy by Design概念之援引 96 第三項 Privacy by Design 的優勢與可解決的問題 99 第五章 結論 103 附件一、GDPR 與 CCPA 概要比較表 108 參考文獻 109 | |
dc.language.iso | zh-TW | |
dc.title | 大數據應用世代下的資訊隱私規範 | zh_TW |
dc.title | Information Privacy Regulations in The Era of Big Data | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 顏雅倫(Ya-Lun Yen),莊弘鈺(Hung-Yu Chuang) | |
dc.subject.keyword | 資訊隱私,設計隱私,大數據,通知與選擇,資訊信託,歐盟資料保護規則, | zh_TW |
dc.subject.keyword | Information Privacy,Privacy by Design,Big Data,Notice and Choice,Information Trust,GDPR, | en |
dc.relation.page | 122 | |
dc.identifier.doi | 10.6342/NTU202002857 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2020-08-11 | |
dc.contributor.author-college | 進修推廣學院 | zh_TW |
dc.contributor.author-dept | 事業經營法務碩士在職學位學程 | zh_TW |
顯示於系所單位: | 事業經營法務碩士在職學位學程 |
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