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題名：從GDPR論AI時代下的當事人有效同意與實務建議
作者：李沛宸
作者(外文)：LEE, PEI-CHEN
校院名稱：中國文化大學
系所名稱：法律學系
指導教授：施光訓
何曜琛
學位類別：博士
出版日期：2020
主題關鍵詞：個人資料保護規章；同意；具體；透明度；自由給予；人工智慧；GDPR；Consent；Specific；Transparency；Freely Given；AI
原始連結：連回原系統網址new window
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歐盟個人資料保護規章第6條中明訂了合法處理當事人個人資料的不同依據，例如當事人的知情同意、基於契約履行所必要、或為了保護資料當事人或他人的重大利益所必須者等各款不同情形，而當事人同意，即為GDPR第6條合法處理個資的其中一項要件。原則上，只要事先向資料當事人清楚說明蒐集資料之用途及目的等相關資訊，並取得當事人的明確同意，即可對當事人的資料進行使用，亦即基於當事人同意將可突破法規限制，對個資進行最彈性化的處理與使用。
因此，為降低當事人資料遭濫用之情事發生，GDPR第6條針對當事人同意取得規定了「自由給予」、「具體」、「知情」、「不含糊」、「可被撤回」等幾項要件必須被滿足，並規定符合這些要件下所獲得之同意才視為有效同意。倘若取得之同意欠缺前述要件，不僅同意取得可能無效，還將有可能面臨對GDPR高額罰款。
而為促進社會進步，隨著科技不斷創新，人工智慧的發展及應用將與隱私權的基本保護間產生衝擊，未來，我們將面臨一系列的法律與道德問題。儘管基於通知及選擇制度的同意是個資及隱私權保護的核心，但，人工智慧系統中是否需要同意、何時需要同意、為何需要同意、如何滿足同意要件等，都是值得探討的議題。
人工智慧在透過數位環境方式蒐集、處理、利用當事人個人資料，一直存在著些許問題，尤其在是否充分提供資料當事人通知及相關資訊揭露、選擇管道及退出機制是否適當等。與傳統取得當事人同意處理其個資方式相比較，透過人工智慧系統將使當事人知情、明確同意更加充滿挑戰。
Article 6 of the General Data Protection Regulation (GDPR) enumerates the different grounds on which the data processing will be lawful such as in order to protect the vital interests, the performance of a contract or for the purposes of the legitimate interests pursued by the controller.
Consent is one of the six conditions for the lawfulness of processing personal data as stipulated in Article 6 of the GDPR. And, it allows you to do just about anything with the data, provided you clearly explain what you are going to do and obtain explicit permission from the data subject.
Under the GDPR, consent of the data subject regarding personal data means any freely given, specific, informed, unambiguous and can be withdraw. To obtain valid consent from the data subject will avoid huge GDPR fines.
In the future we will face a range of legal and ethical dilemmas in the search for a balance between considerable social advances in the name of AI and fundamental privacy rights. Although consent is central to data protection and privacy laws based on a notice and choice regime around the world, it is worth questioning where, why, and when consent is required in AI systems.
Therefore, AI systems collect, process, and generate data in ways that further exacerbate many long-documented problems with online consent, most notably issues of providing adequate notice, choice, and withdrawal to users. From a practical perspective, decision-making by machine-learning algorithms and other AI systems is not as straightforward as that of traditional systems - making the issue of informed, explicit consent a sticky issue.
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