When building open-source AI, the choice of a license is crucial as it defines how AI models, datasets, and code can be used, modified, and shared. For example, permissive licenses, like Apache 2.0 and MIT, encourage innovation with minimal restrictions, while AI-specific licenses, such as RAIL, address ethical concerns by restricting harmful uses. Data-specific licenses on the other hand safeguard datasets, thereby ensuring responsible sharing and use.