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題名 人工智慧與個人資料保護:以監理框架的建構為中心
Artificial Intelligence and Data Protection: Eastablishing an Audit Framework
作者 劉定基
貢獻者 法律系
關鍵詞 人工智慧; 個人資料保護; 資料保護風險評估; 個人資料商店; 自動化決策
Artificial Intelligence; Personal Data Protection; Data Protection Impact Assessment; Personal Data Store; Automated Decision-making
日期 2021-11
上傳時間 31-Jul-2025 15:49:20 (UTC+8)
摘要 在2018年底至今的一年多期間,國際及歐洲權威的資料保護、人權保護機構(例如:國際資料保護及隱私保護官會議、歐洲理事會、英國資訊官),不約而同的針對人工智慧所涉及的資料保護問題,提出關鍵性的指引,希望在發展人工智慧技術的同時,能夠遵守一定的核心價值,以保障人權。在這些文件中,不但針對人工智慧與機器學習對於個人資料保護所可能產生的影響加以研究、分析,甚至對不同的「遵法工具」提出檢討,其中也包含了令人耳目一新的「個人資料商店」等新的嘗試。本計畫擬針對前述國際的新發展進行系統性的研究,除了詳細瞭解人工智慧對個人資料保護所可能帶來的各項衝擊外,也將嘗試建構一個專門針對人工智慧涉及個人資料保護問題的監理框架,使相關問題能夠獲得細緻的討論,並落實監理,使人工智慧能在人民信賴的環境下健全發展。
Since the end of 2018, International and European data protection and human rights protection organizations (such as ICDPPC, Council of Europe, UK's ICO) have successively released important guidelines on data protection issues in artificial intelligence (AI). The common goal of these organizations is to preserve certain core values while developing AI technology so as to protect basic human rights. In these documents, the potential impacts of AI on data protection principles have been thoroughly analyzed. Different compliance tools (including the newly developed practice of "personal data stores") have also been discussed. This research project aims to study these new international developments. In addition to comprehensively analyzing the potential influences of AI on traditional data protection principles, it will also try to develop an AI-specific audit framework, under which relevant issues can be carefully considered and discussed. The ultimate goal is to create a trust environment where AI technology can thrive while important individual and societal interests can be securely safeguarded at the same time.
關聯 科技部, MOST109-2410-H004-115, 109.08-110.07
資料類型 report
dc.contributor 法律系
dc.creator (作者) 劉定基
dc.date (日期) 2021-11
dc.date.accessioned 31-Jul-2025 15:49:20 (UTC+8)-
dc.date.available 31-Jul-2025 15:49:20 (UTC+8)-
dc.date.issued (上傳時間) 31-Jul-2025 15:49:20 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158235-
dc.description.abstract (摘要) 在2018年底至今的一年多期間,國際及歐洲權威的資料保護、人權保護機構(例如:國際資料保護及隱私保護官會議、歐洲理事會、英國資訊官),不約而同的針對人工智慧所涉及的資料保護問題,提出關鍵性的指引,希望在發展人工智慧技術的同時,能夠遵守一定的核心價值,以保障人權。在這些文件中,不但針對人工智慧與機器學習對於個人資料保護所可能產生的影響加以研究、分析,甚至對不同的「遵法工具」提出檢討,其中也包含了令人耳目一新的「個人資料商店」等新的嘗試。本計畫擬針對前述國際的新發展進行系統性的研究,除了詳細瞭解人工智慧對個人資料保護所可能帶來的各項衝擊外,也將嘗試建構一個專門針對人工智慧涉及個人資料保護問題的監理框架,使相關問題能夠獲得細緻的討論,並落實監理,使人工智慧能在人民信賴的環境下健全發展。
dc.description.abstract (摘要) Since the end of 2018, International and European data protection and human rights protection organizations (such as ICDPPC, Council of Europe, UK's ICO) have successively released important guidelines on data protection issues in artificial intelligence (AI). The common goal of these organizations is to preserve certain core values while developing AI technology so as to protect basic human rights. In these documents, the potential impacts of AI on data protection principles have been thoroughly analyzed. Different compliance tools (including the newly developed practice of "personal data stores") have also been discussed. This research project aims to study these new international developments. In addition to comprehensively analyzing the potential influences of AI on traditional data protection principles, it will also try to develop an AI-specific audit framework, under which relevant issues can be carefully considered and discussed. The ultimate goal is to create a trust environment where AI technology can thrive while important individual and societal interests can be securely safeguarded at the same time.
dc.format.extent 116 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) 科技部, MOST109-2410-H004-115, 109.08-110.07
dc.subject (關鍵詞) 人工智慧; 個人資料保護; 資料保護風險評估; 個人資料商店; 自動化決策
dc.subject (關鍵詞) Artificial Intelligence; Personal Data Protection; Data Protection Impact Assessment; Personal Data Store; Automated Decision-making
dc.title (題名) 人工智慧與個人資料保護:以監理框架的建構為中心
dc.title (題名) Artificial Intelligence and Data Protection: Eastablishing an Audit Framework
dc.type (資料類型) report