ML Model Transparency & Logging

This question asks if you keep clear records of how your AI makes decisions and what information goes in and out of it. It's like having a flight recorder for your AI - you document what the system does, why it does it, and keep logs of every decision it makes. This transparency helps you explain AI decisions to customers, regulators, or your own team when questions arise.

Model transparency is increasingly required by regulations and enterprise procurement processes. Without proper documentation and logging, you can't debug problems, prove compliance, or defend against bias accusations. This capability directly impacts your ability to sell to regulated industries like healthcare or finance. Companies with transparent AI systems build stronger customer trust and can charge premium prices for explainable AI solutions.

Teams often log raw technical metrics without translating them into business-understandable documentation. Another mistake is implementing logging that slows down the model or generates so much data it becomes impossible to analyze. Many also forget to secure their logs, creating a new vulnerability while trying to improve transparency.