Open source is not clearly defined for AI yet. A lot of companies are open washing their AI technology and not really open sourcing all elements of their AI. There are various efforts such as this one to define open source AI: https://opensource.org/ai/open-source-ai-definition.
The main arguments for open source AI are:
Transparency and collaboration allows for greater scrutiny, enabling researchers and developers to identify and address biases, vulnerabilities, or errors in models. It fosters innovation by enabling collaboration across organizations and reducing duplication.
Decentralization of power reduces the dominance of a few large organizations, encouraging healthy competition.
Access to models and training data speeds up scientific progress, allowing smaller entities to contribute.
The main risks stem from poor governance. If the governance doesn't promote a vibrant community of contributors from a broad array of sources in industry and academia to contribute, the projects tend to lose momentum. The most successful open source communities (e.g. Linux) are not dominated by one company or organization and are well governed by non for profit foundations.
National security risks were raised as a concern in the early days of open source software too. The same arguments were made around giving adversaries unrestricted access to powerful software. My view is that closed-source systems pose greater risks due to their opacity, making it harder to detect or prevent misuse. Insider threats are a far greater risk from closed source.
This nature article has a bit more background:
https://openuk.uk/wp-content/uploads/2024/06/Not-all-%E2%80%98open-source-AI-models-are-actually-open-heres-a-ranking-.pdf
https://www.reddit.com/r/OpenAI/comments/1dm2odz/not_all_open_source_ai_models_are_actually_open/