  Applications of Generative AI (Gen 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 the potential
risks of the technology, 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. Using a three-stage framework for Gen AI development
(near, mid and long-term), we analyze the risks and opportunities of
open-source generative AI models with similar capabilities to the ones
currently available (near to mid-term) and with greater capabilities
(long-term). We argue that, overall, the benefits of open-source Gen AI
outweigh its risks. As such, we encourage the open sourcing of models, training
and evaluation data, and provide a set of recommendations and best practices
for managing risks associated with open-source generative AI.
