負責任 AI 的隱私權做法，包括考量使用私密資料時可能產生的影響。這不僅指要遵循法律和法規要求，也要考量社會規範和一般個人期望。舉例來說，考量到機器學習模型可能會記住或揭露他們接觸過的資料，我們需要採取哪些防護措施來確保個人隱私權？為確保使用者能充分掌握資料的資訊公開透明度和控制權，需要採取哪些步驟？
[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["缺少我需要的資訊","missingTheInformationINeed","thumb-down"],["過於複雜/步驟過多","tooComplicatedTooManySteps","thumb-down"],["過時","outOfDate","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["示例/程式碼問題","samplesCodeIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-02-25 (世界標準時間)。"],[[["Responsible AI privacy practices involve respecting legal and regulatory requirements, social norms, and individual expectations regarding sensitive data."],["Safeguards are crucial to ensure individual privacy, as ML models can retain and potentially reveal aspects of the data used in training."],["Transparency and user control over their data are essential considerations in responsible AI development."],["Google's PAIR Explorables offer interactive learning experiences to deepen your understanding of ML privacy concepts like randomized response, federated learning, and data leakage."]]],[]]
