Undergraduate student specializing in data annotation and AI response evaluation (2024–Present)
Conducted AI content evaluation by reviewing AI-generated text for correctness, logic consistency, and compliance with strict annotation guidelines. Identified critical logic flaws and checked outputs against multi-layered constraints to ensure safety and truthfulness requirements were met. Provided clear, objective feedback to support model improvement and maintain high labeling accuracy across large volumes of work. • Reviewed AI-generated text for rule adherence and factual consistency • Assessed reasoning and logic to detect critical flaws • Tracked label consistency, truthfulness, and safety requirements • Delivered human-authored explanations for necessary data corrections