🔍 Why It Matters
Responsible AI prevents:
- Bias or misleading outputs
- Misinterpretation of predictions
- Privacy risks
- Over-reliance on automated decisions
Clear communication and transparent model behavior help users trust the system.
🧠 Responsible AI in SmartFactCheckBot
- Transparent limitations: Trained on news from 2015–2020, predictions rely on older patterns. Users are encouraged to verify important claims with official sources.
- Privacy-first design: No user identity or text content is stored; only minimal anonymous telemetry is collected.
- Ethical datasets: Uses publicly available research datasets.
- Clear disclaimers: Communicates the probabilistic nature of AI predictions.
⚙️ Responsible AI in SmartOps
- Uses anonymized or synthetic data.
- Provides confidence scores and interpretability for every prediction.
- Human approval required for any automated operational decision.
🚀 Building AI for Public Benefit
Both systems are free, open, and community-oriented. Responsible AI ensures they remain safe, transparent, and useful for real-world applications.
