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https://ah.lib.nccu.edu.tw/handle/140.119/137301| 題名: | 大數據分析對個人資料保護法制之衝擊 —以個人資料保護影響評估制度為中心 The Impact of Big Data Analysis Technology on the Data Protection Law Focusing on the Data Protection Impact Assessment |
作者: | 林芯瑜 Lin, Chin-Yu |
貢獻者: | 劉定基 Liu, Ting-Chi 林芯瑜 Lin, Chin-Yu |
關鍵詞: | 資料保護影響評估 隱私影響評估 大數據 告知後同意 行政管制 風險評估 個人資料保護 新冠肺炎 Data Protection Impact Assessment Privacy Impact Assessment Big data Informed consent Risk assessment Personal data protection Big data analysis technology Covid-19 |
日期: | 2021 | 上傳時間: | 1-十月-2021 | 摘要: | 大數據資料處理技術的研發與應用如同蘊含無限可能與想像的藍海，相關應用著實為當代社會帶來諸多的方便與創新，因而造就政府乃至企業對於大數據資料分析趨之若鶩的景象；然這項轉變卻也悄悄衝擊傳統個人資料保護法制設計的前提假設，使其日漸喪失掌控危險與風險的有效地位，故而有必要探尋個人資料保護領域的新規範模式。\n面對大數據資料處理技術對於個人資料保護領域造成的震盪，各國(或地區)政府與學者分別對於個人資料保護領域的新規範模式該如何設計提出不同的構想，綜觀實務與學說的發展可以發現資料保護影響評估制度具有承上啟下的作用，在個人資料保護法制未來發展上亦位居關鍵要角，因此有必要就資料保護影響評估在制度設計及具體落實層面進行詳細介紹。\n本文選擇歐盟GDPR、英國DPA以及美國電子政府法下的資料保護/隱私影響評估制度作為主要觀察的對象，並選擇兩份於歐盟與英國針對和新冠肺炎相關的資料處理程序所做成的資料保護影響評估進行詳細觀察，整理新型態的規範模式如何解決傳統告知後同意模式所遭逢的困境。最後回歸我國法，參考先前對於歐盟、英國以及美國資料保護/隱私影響評估法制以及實踐層面的討論，提出我國未來規劃個人資料保護影響評估制度的建議。 The development and application of big data analysis technology is like a blue ocean of infinite imagination and possibilities. Related applications of big data analysis have brought many conveniences and innovations to our society, and both government and enterprises are eager to harness the benefits of the technology. This change, however, has also impacted the longstanding design and basic principles of personal data protection laws, which are gradually losing their effectiveness in protecting individuals’ rights and controlling risks. There is thus a need to explore new norms of personal data protection laws.\nIn the face of the turbulence created by big data analysis technology on personal data protection laws, governments and scholars of various countries (or regions) have put forward different ideas on how to design new norms. When we look at the current developments of relevant practices and doctrines, it can be found that Data Protection Impact Assessments (DPIAs) have allowed a relatively smooth transition from the traditional regimes to the new ones, and will play a crucial role in future data protection laws. It is therefore necessary to look deeper into the design and implementation of DPIAs.\nThis study will focus on the DPIAs/PIAs under the EU GDPR, the UK DPA and the US Electronic Government Act, and follow with a close examination on two DPIAs conducted respectively in the EU, and the UK regarding data processing related to Covid-19. Finally, the study will return to domestic law. By reference to previous discussions on the legal and practical aspects of DPIAs/PIAs in the EU, the UK and the US, this study will offer advice on the future establishment of DPIA in Taiwan. |
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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Broadway Books.〕\n\n(八) 網路資料\n王允翬 (2020)，在全民健保之外──各國健康照護制度簡介(二)，陽明醫聲，第21期，網址：https://ymmedmagazine.blogspot.com/2015/04/blog-post_92.html。\n台灣人權促進會 (2019)，台權會針對個人資料保護法的修法建議（國發會公聽會發言單），網址：https://www.tahr.org.tw/news/2486。\n吳奕靖 (2020)，夫收「細胞簡訊」被妻趕出門…吵架整夜睡不著 醫轟：亂槍打鳥造成恐慌，Ettoday新聞雲，網址：https://www.ettoday.net/news/20200421/1696898.htm。\n劉致昕 (2020)，專訪前「劍橋分析」業務總監：只要臉書的生意繼續，民主就有危機，報導者，網址：https://www.twreporter.org/a/information-warfare-business-interview-cambridge-analytica-brittany-kaiser.。\n\n二、外文文獻\n(一) 專書\nAri Ezra Waldman. 2018. Privacy as Trust Information Privacy for an Information Age. New York: Cambridge University Press.\nAldous Huxley. 2014. Brave new world. London: Vintage Books.\nCass R. Sunstein. 2018. #Republic: Divided Democracy in the Age of Social Media. New Jersey: Princeton University Press.\nCathy O`Neil. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Broadway Books.\nDaniel Kahneman. 1973. Attention and Effort. New Jersey: Prentice Hall.\nGeorge Orwell. 2017. Nineteen Eighty-Four. New York: Houghton Mifflin Harcourt.\nJon Elster. 1998. Deliberative Democracy. New York: Cambridge University Press.\nNational Research Council. 1983. Risk Assessment in the Federal Government: Managing the Process. Washington (DC): National Academies Press.\n\n(二) 專書論文\nFred H. Cate. 2006. The Failure of Fair Information Practice Principles. Pp.343-379 in Consumer Protection in the Age of the Information Economy, edited by Jane K. Winn. London: Routledge.\nWilliam Malcolm. 2017. Overseas or Cross-Border Transfers of Personal Data: Schrems, Brexit and the General Data Protection Regulation. Pp.143-167 in Guide to the General Data Protection Regulation: a companion to Data protection law and practice, edited by Rosemary Jay. London: Sweet & Maxwell.\n\n(三) 期刊論文\nDaniel J. Solove. 2002. Conceptualizing Privacy. California Law Review 90:1087-1155.\nDaniel J. Solove. 2013. Privacy Self-Management and the Consent Dilemma. Harvard Law Review 126:1880-1903.\nDaniel J. Solove. 2021. The Myth of the Privacy Paradox. George Washington Law Review 89:1-51.\nDavid M. Parker., Steven G. Pine., and Zachary W. Ernst. 2019. Privacy and Informed Consent for Research in the Age of Big Data. Penn State Law Review 123:703-733.\nDennis D. Hirsch. 2020. From Individual Control to Social Protection: New Paradigms for Privacy Law In The Age of Predictive Analytics. Maryland Law Review 79(2):439-505.\nEdward J. Janger, and Paul M. Schwartz. 2002. The Gramm-Leach-Bliley Act, Information Privacy, and the Limits of Default Rules. Minnesota Law Review 86:1219-1262.\nElizabeth Dubois, and Grant Blank. 2018. The echo chamber is overstated: the moderating effect of political interest and diverse media. Information, Communication & Society 21:729-745.\nHelen Norton. 2019. Powerful Speakers and Their Listeners. University of Colorado Law Review 90:441-473.\nHiba Jasim Hadi., Ammar Hameed Shnain., Hiba Jasim Hadi., and Sarah Hadishaheed. 2015. Big Data and Five V’s Characteristics. International Journal of Advances in Electronics and Computer Science 2(1):16-23.\nJack M. Balkin. 2016. Information Fiduciaries and the First Amendment. University of California at Davis Law Review 49:1183-1234.\nJohn S. Applegate. 2005. The Story of Reserve Mining: Managing Scientific Uncertainty in Environmental Regulation. Indiana Legal Studies Research Paper 16:1-43.\nJulia M. Brooks. 2019. Drawing the Lines: Regulation of Automatic License Plate Readers in Virginia. Richmond Journal of Law & Technology 25:1-32.\nMark A. Geistfeld. 2017. A Roadmap for Autonomous Vehicles:State Tort Liability, Automobile Insurance, and Federal Safety Regulation. California Law Review 105:1611-1694.\nMark Peasley. 2019. It`s Time for an American (Data Protection) Revolution, Akron Law Review 52:911-943.\nMichael Birnhack. 2012. Reverse Engineering Informational Privacy Law. Yale Journal of Law and Technology 15:24-91.\nNeil M. Richards, and Jonathan King. 2013. Three Paradoxes of Big Data. Stanford Law Review 66:41-46.\nNiva Elkin-Koren, and Michal S. Gal. 2019. The Chilling Effect of Governance-by-Data on Data Markets. The University of Chicago Law Review 86:403-431.\nOliver Wendell Holmes. 1946. Learning and Science. North Carolina Law Review 24:102-103.\nOmer Tene, and Jules Polonetsky. 2013. Big Data for All: Privacy and User Control in the Age of Analytics. Northwestern Journal of Technology and Intellectual Property 11(5):239-273.\nRagnar E. Lofstedt. 2011. Risk versus Hazard – How to Regulate in the 21st Century. European Journal of Risk Regulation 2:149-168.\nRaphaël Gellert. 2015. Understanding Data Protection As Risk Regulation. Journal of Internet Law 18(11):3-15.\nRick Swedloff. 2014. Risk Classification`s Big Data (R)evolution. Connecticut Insurance Law Journal 21:339-374.\nRonen Avraham, Kyle D. Logue, and Daniel Schwarcz. 2014. Understanding Insurance Antidiscrimination Laws. Southern California Law Review 87:195-274.\nRyan L. Garner. 2017. Evaluating Solutions to Cyber Attack Breaches of Health Data: How Enacting a Private Right of Action for Breach Victims Would Lower Costs. Indiana Health Law Review 14:127-171.\nSamuel D. Warren., and Louis D. Brandeis. 1890. The Right to Privacy. Harvard Law Review 4:193-220.\nSandra Wachter, Brent Mittelstadt, and Chris Russell. 2018. Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR. Harvard Journal of Law & Technology 31:841-887.\nSolon Barocas, and Andrew D. Selbst. 2016. Big Data`s Disparate Impact. California Law Review 104:671-732.\nTim Wu. 2018. Is The First Amendment Obsolete? Michigan Law Review 117:547-581.\nWen-Ta Chiu, Ronald P. Laporte, and Jonathan Wu. 2020. Determinants of Taiwan’s Early Containment of COVID-19 Incidence. American Journal of Public Health 110:943-944.\nZohar Efroni, Jakob Metzger, Lena Mischau and Marie Schirmbeck. 2019. Privacy Icons: A Risk-Based Approach to Visualisation of Data Processing. European Data Protection Law Review 5(3):352-366.\n\n(四) 國際組織文件和各國政府相關文書、報告\nAmerican Civil Liberties Union. 2012. Eight Problems With “Big Data” Available at https://www.aclu.org/blog/privacy-technology/surveillance-technologies/eight-problems-big-data\nAmerican Civil Liberties Union. 2014. Written Submission of the American Civil Liberties Union on Racial Disparities in Sentencing Hearing on Reports of Racism in the Justice System of the United States. Available at https://www.aclu.org/sites/default/files/assets/141027_iachr_racial_disparities_aclu_submission_0.pdf\nArticle 29 Data Protection Working Party. 2017. Guidelines on Data Protection Impact Assessment (DPIA) (wp248rev.01) Available at https://ec.europa.eu/newsroom/article29/items/611236\nArticle 29 Data Protection Working Party. 2017. Guidelines on Data Protection Officers (‘DPOs’) Available at https://ec.europa.eu/newsroom/article29/items/612048\nCabinet Office, National security and intelligence, and Government Security Profession. 2018. Guidance on the IAO Role. Available at https://www.gov.uk/government/publications/information-asset-owner-role-guidance\nDepartment of Homeland Security. 2017. Privacy Impact Assessment for the United States - Mexico Entry/Exit Data Sharing Initiative. Available at https://www.dhs.gov/sites/default/files/publications/privacy-pia-cbp-usmexicoentryexitdatasharinginitiative-december2017.pdf.\nEuropean Commission. 2020. Data protection as a pillar of citizens’ empowerment and the EU’s approach to the digital transition - two years of application of the General Data Protection Regulation. Available at https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52020DC0264&from=EN\nEuropean Commission. 2021. Proposal for a Regulation of the European Parliament and the Council laying down requirements for Artificial Intelligence. Available at https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0206\nEuropean Data Protection Board. 2018. THE EUROPEAN DATA PROTECTION BOARD. Available at https://edpb.europa.eu/sites/default/files/files/news/endorsement_of_wp29_documents_en_0.pdf\nEuropean Data Protection Board. 2019. Opinion 6/2019 on the draft list of the competent supervisory authority of Spain regarding the processing operations subject to the requirement of a data protection impact assessment (Article 35.4 GDPR) Available at https://edpb.europa.eu/sites/default/files/files/file1/201906_edpb_art.64_es_sas_dpia_list_en_0.pdf\nEuropean Data Protection Board. 2020. Guidelines 4/2019 on Article 25 Data Protection by Design and by Default Version 2.0. Available at https://edpb.europa.eu/sites/default/files/files/file1/edpb_guidelines_201904_dataprotection_by_design_and_by_default_v2.0_en.pdf\nEuropean Data Protection Board. 2021. EDPB-EDPS Joint Opinion 5/2021 on the proposal for a Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Available at https://edpb.europa.eu/our-work-tools/our-documents/edpbedps-joint-opinion/edpb-edps-joint-opinion-52021-proposal_en\nInformation Commissioner`s Office. 2021. Data Protection by Design and Default. Available at https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/accountability-and-governance/data-protection-by-design-and-default/#dpd9\nInformation Commissioner`s Office. 2021. Data Protection Impact Assessments (DPIAs) Available at https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/data-protection-impact-assessments-dpias/\nInformation Commissioner`s Office. 2021. Do we need to consult the ICO? Available at https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/data-protection-impact-assessments-dpias/do-we-need-to-consult-the-ico/\nInformation Commissioner`s Office. 2021. Examples of processing ‘likely to result in high risk’ Available at https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/data-protection-impact-assessments-dpias/examples-of-processing-likely-to-result-in-high-risk/\nInformation Commissioner`s Office. 2021. How do we do a DPIA? 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Available at https://www.bbc.com/news/explainers-54195827\nPerelman School of Medicine at the University of Pennsylvania. HIPAA Security Risk Management Process. Available at https://www.med.upenn.edu/psom/results.html?query=HIPAA&search=%2F%2Fwww.med.upenn.edu&form_submit\nScience News. 2019. Echo chambers may not be as dangerous as you think, new study finds. Available at https://www.sciencedaily.com/releases/2019/05/190513155629.htm\nSvetlana Sicular. 2013. Gartner’s Big Data Definition Consists of Three Parts, Not to Be Confused with Three “V”s. Available at https://blogs.gartner.com/svetlana-sicular/gartners-big-data-definition-consists-of-three-parts-not-to-be-confused-with-three-vs/\nThe Open File Blog. 2013. TX: Study Finds Harris County Prosecutors Sought Death Penalty 3-4 Times More Often against Defendants of Color. Available at https://www.prosecutorialaccountability.com/2013/03/15/tx-study-finds-harris-county-prosecutors-sought-death-penalty-3-4-times-more-often-against-defendants-of-color/ | 描述: | 碩士 國立政治大學 法律學系 106651043 |
資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0106651043 | 資料類型: | thesis |
| Appears in Collections: | 學位論文 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 104301.pdf | 6.43 MB | Adobe PDF2 | View/Open |
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