Methods and design choices that make the outputs of an AI model understandable to the people who use, oversee or are affected by it.
Why it matters
Public decisions must be explainable to be lawful and contestable. Explainability is also how auditors find errors and bias.
We apply this in our AI Governance and Responsible Technology practice.