Calling It 'Open Source' Doesn't Make It Open. It Makes It Marketable.

Meta releases model weights and calls it "open source." The OSI publishes a definition. Half the AI industry objects. The other half co-opts the language. Welcome to the most consequential branding fight in technology.

The term "open source" carries enormous goodwill — decades of community-built software, from Linux to Firefox, grounded in genuine rights to use, modify, and redistribute. When Meta calls Llama "open source" while restricting commercial use above a user threshold and withholding training data, it's borrowing that goodwill without honoring the obligations. The Open Source Initiative spent months crafting an AI-specific definition that requires access to training data and code, not just model weights. Most "open" AI releases fail that standard.

This isn't pedantry. The distinction has material consequences. "Open weights" means you can run the model and fine-tune it — if you have the compute, which means you need the budget. You cannot reproduce the training, audit the data for bias or copyright issues, or verify safety claims independently. It's the difference between being given a car and being given the blueprints, factory, and supply chain. One makes you a user. The other makes you a participant.

The companies pushing "open" AI models have clear incentives. Meta's Llama strategy builds an ecosystem on its architecture, driving adoption and influence without bearing the full cost of a closed API business. It's a platform play wearing community clothing. As Heather Meeker and others tracking open source licensing have noted, the economic logic is distribution, not liberation.

The redistribution angle: "Open" model releases concentrate power with organizations that control training data and compute while creating an appearance of democratization. Smaller developers and researchers get access to outputs, not inputs — they can build on top but not underneath. The real openness question: who controls the means of production, not just the product?

If you can't see the training data, audit the process, or afford the compute to reproduce it — what exactly is "open" about it?

#OpenSourceAI #OpenWashing #AIAccess #Redistribution #LLMs