The Model Openness Framework: Promoting Completeness and Openness for Reproducibility, Transparency and Usability in AI

« Generative AI (GAI) offers unprecedented possibilities but its commercialization has raised concerns about transparency, reproducibility, bias, and safety. Many « open-source » GAI models lack the necessary components for full understanding and reproduction, and some use restrictive licenses, a practice known as « openwashing. » We propose the Model Openness Framework (MOF), a ranked classification system that rates machine learning models based on their completeness and openness, following principles of open science, open source, open data, and open access. (…) »

source >, Matt White, Ibrahim Haddad, Cailean Osborne, Xiao-Yang (Yanglet) Liu, Ahmed Abdelmonsef, Sachin Varghese, 20 mars 2024, arXiv:2403.13784v1,