AI Ground Truth & RLHF Practitioner (Senior Technical Advisor & Resilience Architect)
Text
RLHFI have spent 30 years in the field practicing the core principle now known in AI as RLHF (Reinforcement Learning from Human Feedback) by providing ground truth validation to AI and mathematical models. My work bridges the gap between digital outputs and real-world physical and social realities, ensuring model outputs are not only technically correct but practically survivable and defensible. This ongoing process involves validating, annotating, and correcting outputs from both digital and field data to prevent catastrophic errors in humanitarian and crisis response domains. • Ensured high-stakes life-critical decisions are driven by verified, annotated, and field-tested data. • Embedded human-in-the-loop feedback protocols for continuous model improvement. • Trained local staff and Water Committees in hands-on digital asset management, functioning as both annotators and validators in HITL systems. • Created frameworks for ongoing validation and evaluation of AI models based on community-derived ground truth data.