Intermediate · Safety

Explainable AI (XAI)

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. A set of techniques that allow humans to understand the output of AI models, especially deep learning models.

Technical Definition

A set of techniques that allow humans to understand the output of AI models, especially deep learning models.

How it works

Explainable AI (XAI) refers to methods and techniques that enable human users to comprehend and trust the results and output of machine learning algorithms. As AI models become more complex ('black boxes'), XAI aims to make their decision-making processes transparent and interpretable. This is crucial for applications in critical domains like healthcare and finance.

Related Concepts

• Interpretability — Understanding why a model makes the predictions it does, by inspecting its internals.
• Black box model — A model whose internal workings are opaque and difficult for humans to understand, despite knowing its inputs and outputs.