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.

翻译：生成式人工智能（Gen AI）的应用预计将在从科学、医学到教育等多个不同领域引发革命性变革。这些颠覆性变化的潜力已引发关于该技术潜在风险的热烈讨论，并导致要求加强监管的呼声，特别是来自一些在人工智能开发领域处于领先地位的大型科技公司。此类监管可能危及新兴的开源生成式人工智能领域。通过采用生成式人工智能发展的三阶段框架（近期、中期和长期），我们分析了能力与当前可用模型相当（近期至中期）及能力更强（长期）的开源生成式人工智能模型的风险与机遇。我们认为，总体而言，开源生成式人工智能的益处大于其风险。因此，我们鼓励将模型、训练与评估数据开源，并提供一套管理开源生成式人工智能相关风险的建议与最佳实践。