探索可協助建置更安全且值得信任之 AI 應用程式的新功能。 工具組 負責任 AI 儀表板 存取工具套件以協助建立自訂、端對端的負責任 AI 體驗。 1 上一張投影片 下一頁投影片 返回[推動 AI 原則] 區段 上一頁投影片 下一張投影片 返回[讓負責任 AI 得以實現] 區段 關注Microsoft 最新...
Toolkit Responsible AI Dashboard Access a suite of tools to help you create a customized, end-to-end responsible AI experience. 1 Previous Slide Next Slide Back to Advancing AI policy section Previous Slide Next Slide Back to Making responsible AI attainable section Follow Microsoft Wh...
2017 年,Microsoft (Aether) 成立了 AI、道德和工程和研究效果顾问委员会。 委员会的核心职责是就负责任的 AI 的问题、技术、流程和最佳做法提供建议。 若要了解详细信息,请参阅了解 Microsoft 治理模型 - Aether + Office of Responsible AI。 问责制 ...
了解負責任 AI 準則在教育環境中非常重要,可確保公平、安全且透明地使用 AI 系統,為所有學習者提供協助。 在此影片中,您會了解負責任 AI 的六個指導準則,包括公平性、可靠性與安全、隱私權與安全性、包容性、透明度和責任。 既然您已大致了解六個負責任 AI 準則,讓我們來...
What is responsible AI? As Artificial intelligence (AI) plays a larger role in our daily lives, it's more important than ever that AI systems are built to provide a helpful, safe, and trustworthy experience for everyone. This is why Microsoft develops and deploys technology using Responsible...
Using the responsible AI dashboard, evaluate with reproducible and automated workflows to assess model fairness, causal analysis, exploratory data analysis, and more.
Watch this webinar with a guest speaker from IDC and Microsoft experts to learn how to approach building responsible AI solutions to cultivate trust in machine learning. We’ll include a demo on model interpretability. You’ll learn how to: Understand, protect, and control your data and models...
Microsoft developed aResponsible AI Standard. It's a framework for building AI systems according to six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. For Microsoft, these principles are the cornerstone of a responsible and trustworthy...
AI 系统应该公平对待所有人。 例如,假设你创建了一个机器学习模型来为银行的贷款审批应用程序提供支持。 该模型应在不考虑任何基于性别、种族或其他因素的偏见的情况下,对是否应批准贷款做出预测,这些偏见可能导致特定的申请人群遭受不公平的差别待遇。机器学习系统的公平性是时下研究热点,我们可以借助...
Responsible Artificial Intelligence (Responsible AI) is an approach to developing, assessing, and deploying AI systems in a safe, trustworthy, and ethical way. AI systems are the product of many decisions made by those who develop and deploy them. From system purpose to how people interact with...