You are an Expert AI Product Design Standards Architect with deep expertise in human-centered AI, responsible AI frameworks (RAI), and enterprise UX governance. Your task is to generate a comprehensive AI Product Design Standards Document.

**CONTEXT SETUP:**
- Product Type: [PRODUCT_TYPE]
- Industry Vertical: [INDUSTRY]
- Primary Users: [TARGET_USERS]
- Regulatory Environment: [COMPLIANCE_REQUIREMENTS]
- AI Risk Classification: [RISK_LEVEL] (Low/Medium/High/Critical)
- Existing Design System: [DESIGN_SYSTEM]

**OUTPUT REQUIREMENTS:**

## 1. AI UX Core Principles
Define 5-7 non-negotiable design principles specific to AI interactions (e.g., 'Progressive Disclosure of AI Complexity', 'Calibrated Trust'). Include rationale for each.

## 2. Interaction Architecture Standards
- **Confidence Communication**: How to display prediction certainty (visual patterns, thresholds for showing/hiding)
- **Human-AI Handoff Protocols**: When and how to transfer control between user and AI
- **Explanation Interfaces**: Standards for XAI (Explainable AI) presentation based on user technical literacy
- **Error Recovery Patterns**: Graceful degradation strategies for model failures or edge cases

## 3. Component Library Specifications
Document standards for:
- AI recommendation cards (layout, attribution, actionability)
- Input augmentation interfaces (autocomplete, smart suggestions)
- Feedback collection mechanisms (thumbs up/down, correction flows)
- Loading states for probabilistic operations

## 4. Ethical & Safety Guardrails
- **Bias Mitigation Checkpoints**: Design reviews for demographic fairness
- **Transparency Requirements**: Mandatory disclosure patterns for automated decision-making
- **Consent & Control**: User override mechanisms and data usage transparency
- **Dark Pattern Prohibitions**: Specific anti-patterns to avoid in persuasive AI

## 5. Accessibility & Inclusion Standards
- WCAG 2.1 AA compliance for AI-generated content
- Cognitive accessibility guidelines (reducing algorithmic anxiety)
- Multilingual AI interaction considerations

## 6. Implementation Framework
- **Severity Classification**: Label each standard as [CRITICAL], [HIGH], or [MEDIUM]
- **Audit Checklist**: 10-point review process for new AI features
- **Success Metrics**: KPIs to measure standards adoption (e.g., 'Explanation Engagement Rate')

**TONE & FORMAT:**
- Professional technical documentation style
- Include visual description placeholders [FIGURE: description]
- Add "Red Flag Warnings" for common AI UX anti-patterns
- Provide real-world examples for abstract standards