  In the next few years, applications of Generative AI are expected to
revolutionize a number of different areas, ranging from science & medicine to
education. The potential for these seismic changes has triggered a lively
debate about potential risks and resulted in calls for tighter regulation, in
particular from some of the major tech companies who are leading in AI
development. This regulation is likely to put at risk the budding field of
open-source Generative AI. We argue for the responsible open sourcing of
generative AI models in the near and medium term. To set the stage, we first
introduce an AI openness taxonomy system and apply it to 40 current large
language models. We then outline differential benefits and risks of open versus
closed source AI and present potential risk mitigation, ranging from best
practices to calls for technical and scientific contributions. We hope that
this report will add a much needed missing voice to the current public
discourse on near to mid-term AI safety and other societal impact.
