🛡️ AI Ethics Monitoring Dashboard

Advanced AI Ethics Command Center for real-time bias detection, fairness enforcement, and congressional compliance oversight in healthcare AI systems.

🚀 🔗 Launch The demo AI Ethics Command Center

🌟 Features

🎯 Executive Overview

• Real-time Risk Assessment: Predictive ethical risk scoring (0-10 scale)
• Critical Alerts System: Priority-based notifications with financial impact estimates
• Interactive Network Visualization: AI model ecosystem mapping with relationship analysis
• Demographic Bias Heatmap: Live bias scoring across protected demographics

📊 Advanced Analytics

• Multi-dimensional Bias Detection: Racial, gender, age, and socioeconomic bias monitoring
• Fairness Metrics: Demographic parity, equalized odds, calibration error tracking
• Performance Monitoring: Precision, recall, F1-score, AUC analysis
• Regulatory Compliance: GDPR, HIPAA, CCPA, EU AI Act compliance tracking

🏛️ Congressional Oversight

• Civil Rights Compliance: Systematic violation detection and reporting
• Legislative Action Items: Priority-ranked recommendations with timelines
• Report Generation: Comprehensive ethics reports for congressional briefings
• Subpoena & Hearing Tools: Direct integration for congressional action

⚡ Enterprise Features

• Real-time Monitoring: Live prediction analysis with WebSocket-like updates
• Advanced Search & Filtering: Multi-parameter model filtering and search
• Interactive Visualizations: Animated charts, network graphs, and heatmaps
• Professional Reports: JSON/PDF export for executive and congressional use

🚀 Quick Start

Prerequisites

• Node.js 16.0.0 or higher
• npm 8.0.0 or higher
• Modern web browser with ES6+ support

Installation

1. Clone the repository

   git clone https://github.com/eaglepython/ai-ethics-monitoring-dashboard.git
   cd ai-ethics-monitoring-dashboard

2. Install dependencies

   npm install

3. Start development server

   npm run dev

4. Open your browser

   http://localhost:5173
   

📁 Project Structure

ai-ethics-monitoring-dashboard/
├── public/
│   ├── vite.svg
│   └── index.html
├── src/
│   ├── components/
│   │   └── AIEthicsMonitoringDashboard.jsx
│   ├── data/
│   │   ├── aiModels.js
│   │   ├── ethicsMetrics.js
│   │   └── alerts.js
│   ├── utils/
│   │   ├── biasCalculations.js
│   │   ├── reportGenerator.js
│   │   └── animations.js
│   ├── styles/
│   │   └── index.css
│   ├── App.jsx
│   └── main.jsx
├── docs/
│   ├── DEPLOYMENT.md
│   ├── API.md
│   └── CONTRIBUTING.md
├── .github/
│   └── workflows/
│       └── deploy.yml
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── .gitignore
├── .eslintrc.js
└── README.md

🎨 Dashboard Sections

1. Executive Overview

• High-level KPIs and risk assessment
• Network visualization of AI model relationships
• Critical alerts requiring immediate attention
• Stakeholder confidence and transparency metrics

2. Real-time Monitoring

• Live prediction stream analysis
• Model status grid with expandable details
• Performance metrics and uptime monitoring
• Anomaly detection and alerting

3. Advanced Bias Analysis

• Demographic bias breakdown by protected classes
• Fairness metrics with pass/fail thresholds
• Historical trend analysis
• Confidence intervals and statistical significance

4. Regulatory Compliance

• Multi-jurisdiction compliance tracking
• Legislative requirement mapping
• Audit trail and certification status
• Risk mitigation recommendations

5. Predictive Analytics

• Ethical drift detection algorithms
• Future risk trend predictions
• Intervention recommendation engine
• ROI analysis for bias mitigation

6. Congressional Oversight

• Civil rights violation tracking
• Legislative action recommendations
• Automated report generation
• Hearing and subpoena management tools

🔧 Configuration

Environment Variables

Create a .env file in the root directory:

# Application Configuration
VITE_APP_TITLE="AI Ethics Monitoring Dashboard"
VITE_APP_VERSION="1.0.0"

# API Configuration (if using real APIs)
VITE_API_BASE_URL="https://api.yourcompany.com"
VITE_API_KEY="your-api-key-here"

# Feature Flags
VITE_ENABLE_REAL_TIME="true"
VITE_ENABLE_EXPORT="true"
VITE_ENABLE_NOTIFICATIONS="true"

# Analytics (optional)
VITE_ANALYTICS_ID="your-analytics-id"

# Deployment
VITE_PUBLIC_URL="https://eaglepython.github.io/ai-ethics-monitoring-dashboard"

Customization

1. Model Data: Edit src/data/aiModels.js to add your AI models
2. Metrics: Modify src/data/ethicsMetrics.js for your organization's KPIs
3. Alerts: Configure src/data/alerts.js for your alert system
4. Branding: Update colors and styling in tailwind.config.js

📈 Deployment

🚀 Vercel (Recommended)

1. Connect your GitHub repository to Vercel

   • Go to vercel.com
   • Import your GitHub repository
   • Vercel automatically detects Vite configuration

2. Configure build settings

   Build Command: npm run build
   Output Directory: dist
   

3. Deploy

   • Every push to main branch triggers automatic deployment
   • Preview deployments for pull requests

🔥 Netlify

1. Connect repository

   • Go to netlify.com
   • Connect your GitHub repository

2. Build settings

   Build Command: npm run build
   Publish Directory: dist
   

📦 GitHub Pages

1. Configure package.json (already done)

   "homepage": "https://eaglepython.github.io/ai-ethics-monitoring-dashboard"

2. Deploy

   npm run deploy

3. Enable GitHub Pages

   • Go to repository Settings > Pages
   • Select gh-pages branch as source

🐳 Docker

# Dockerfile (create this file)
FROM node:18-alpine

WORKDIR /app

COPY package*.json ./
RUN npm ci --only=production

COPY . .
RUN npm run build

FROM nginx:alpine
COPY --from=0 /app/dist /usr/share/nginx/html

EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]

🔒 Security Considerations

• Data Privacy: No sensitive data is stored in browser localStorage
• HTTPS Only: Ensure all deployments use HTTPS
• Content Security Policy: Implement CSP headers for production
• Authentication: Add authentication layer for production use
• Rate Limiting: Implement API rate limiting for real data sources

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Workflow

1. Fork the repository
2. Create a feature branch

   git checkout -b feature/your-feature-name

3. Make changes and commit

   git commit -m "Add your feature description"

4. Push to your fork

   git push origin feature/your-feature-name

5. Create a Pull Request

Code Style

• ESLint: Follow the configured ESLint rules
• Prettier: Code formatting is handled automatically
• Conventional Commits: Use conventional commit messages
• Component Structure: Follow React best practices

📊 Data Sources

Mock Data (Current)

The dashboard currently uses realistic mock data for demonstration purposes:

• 4 AI healthcare models with comprehensive metrics
• Real-time simulation with WebSocket-like updates
• Historical trend data (30-day rolling window)
• Alerts and compliance tracking

Real Data Integration

To connect real data sources:

1. Update API endpoints in src/utils/api.js
2. Configure authentication in environment variables
3. Modify data transformers in src/utils/dataTransformers.js
4. Test with real data using development environment

🛠️ Tech Stack

• Frontend: React 18, Vite, Tailwind CSS
• Icons: Lucide React
• Charts: Canvas-based custom visualizations
• Animations: CSS animations + Canvas animations
• Deployment: Vercel, Netlify, GitHub Pages compatible
• Build Tool: Vite (faster than Webpack)
• Styling: Tailwind CSS with custom components

📋 Browser Support

• Chrome 90+
• Firefox 88+
• Safari 14+
• Edge 90+

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• Documentation: Check the docs/ folder
• Issues: Open an issue on GitHub
• Discussions: Use GitHub Discussions for questions
• Email: aiglevision35@gmail.com
• LinkedIn: joseph-bidias
• GitHub: @eaglepython

🎯 Roadmap

Version 1.1

• Real-time WebSocket integration
• PDF report generation
• Multi-language support
• Mobile responsive improvements

Version 1.2

• Machine learning bias prediction
• Integration with popular ML platforms
• Advanced analytics dashboard
• API for third-party integrations

Version 2.0

• Multi-tenant support
• Role-based access control
• Audit logging system
• Compliance automation tools

🙏 Acknowledgments

• React Team for the amazing framework
• Tailwind CSS for the utility-first CSS framework
• Lucide for the beautiful icons
• Vite for the lightning-fast build tool
• Open Source Community for inspiration and tools

---

Live Demo • Documentation • Contributing • Report Bug

Made with ❤️ for ethical AI development

Contact: Joseph Bidias | aiglevision35@gmail.com | @eaglepython

Specializing in Congressional consulting, AI governance platforms, and antitrust policy discussions