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

arXiv:2403.13784v1 Announce Type: new
Abstract: 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. …

abstract arxiv bias components concerns cs.ai cs.cy cs.lg cs.se framework gai generative practice reproducibility restrictive safety transparency type understanding usability