10 Lessons Learned for Assessing and Mitigating Unexpected Patterns in AI Models (Part 1 of 3)

Getting to trustworthy AI is not simple. It takes a lot of moving parts and collective resources (well beyond a data science team) to get every element right, from people and culture to governance to data and processes. But that’s true of most worthy endeavors. In this 3 part series, author Sheri Feinzig and Phaedra Boinodiris walk you through the top 10 lessons learned for both assessing and mitigating for unexpected patterns in AI models.

Phaedra BoinodirisPhaedra BoinodirisFebruary 28, 2022lessons learned, bias, patterns, ai models, systemic empathy, AI ethics