Introduction to Testing AI-Powered Systems (Signed NDA not to mention Company Name but AI Training for a AI Enabled Browser)
On a Project dealing with an AI-enabled browser (signed NDA to not reveal company name), I am still involved in the end to end AI feature training and testing for an AI-powered browser assistant. My responsibilities include reviewing and labeling user-AI interaction logs, annotating intents and entities, tagging both correct and incorrect responses, and classifying edge cases to improve the model accuracy and safety. I also evaluate and refine prompt/response pairs for clarity, adherence to product guidelines, and relevance. This ongoing project covers thousands of conversation samples across multiple use cases and continues to expand, requiring high - volume labeling within tight timelines. I follow strict quality standards using detailed labeling guidelines, performing cross-checks and peer reviews, maintaining high inter-annotator agreement scores, and reporting ambiguities not limited to only text data type but images and audio as well for guideline updates, while collaborating with QA leads and developers to validate AI behaviour and ensure model updates are thoroughly tested before release.