通过可解释的 AI 界面、决策透明度和来源标注来建立用户信任的设计模式
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模式： 具备决策透明度、来源标注与信任构建模式的可解释 AI 界面，用于负责任的 AI 部署
原因： 建立用户信任、满足监管要求、支持知情决策并确保 AI 系统的问责
关键洞察： 带渐进披露的三层透明度框架（是什么/如何/为什么）：以理解而非盲信建立信任
Discover how Trust and Transparency Patterns relates to other patterns
Prerequisites, next steps, and learning progression
Foundation for displaying AI certainty and uncertainty levels
💡 Essential building block for transparent confidence communication
Gradual information revelation for complex explanations
💡 Required for managing cognitive load in explainable interfaces
Human oversight integration with transparent decision points
💡 Natural evolution to human-AI collaborative decision-making
Advanced monitoring with transparent operational oversight
💡 Scale transparency to enterprise monitoring and control systems
Privacy-focused patterns that may limit transparency
💡 Alternative approach when privacy concerns outweigh transparency needs
Personalized interfaces with implicit rather than explicit explanations
💡 Different approach focusing on adaptation rather than explanation
Explainable diagnostic AI with clinical decision support and patient transparency
Regulatory-compliant AI with transparent risk assessment and decision audit trails
Explainable legal AI with case reasoning, precedent analysis, and attorney decision support
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