Sandeep's Quicktake: Getting teams to not just look at wrong labels in ML data Journeys to Democratize Data+AI

Democratize is not one big strategy but 100s of small things that you put in place. Quicktake is a series of short practical tips to get you started towards making data and AI widely accessible and self-service within your organization.

This tip covers an important myth: To improve model accuracy, start by verifying the correctness of labels. Typically, there is only a small percentage of miss predictions that are related to wrong labels. Often times the biggest reason for model inaccuracies is the poor quality of data samples. Train the team just that instead of jumping to fix the incorrect labels, start by analyzing a sample of results that were misclassified and make a judgment call on whether to invest in fixing the labels going back and looking at opus deposit useful.