AI Model Development and Evaluation Framework

This document is a guide detailing the framework for developing and evaluating AI models. It outlines the purpose and goals of the model, emphasizing the importance of defining the problem being solved and the guiding objectives. The document specifies various model types, including AI/NLP, AI/ML, and GenAI, and discusses the significance of knowing whether a model is trained from scratch or based on a pre-trained version. Additionally, it addresses the training data sources, time periods, and languages involved, highlighting the implications for data usage and security. The guide also covers model performance and validation, detailing the importance of intermediate and final outputs, as well as data security measures. Furthermore, it describes the model's scope and limitations, including known biases and the necessity of guardrails to prevent negative outcomes. The document emphasizes the importance of thorough evaluation from both computational and human impact perspectives.