Explainable AI

Explainable AI (XAI) focuses on making machine learning models and their decisions understandable to humans. Instead of treating models as black boxes, XAI aims to provide insights into how a model arrives at a particular prediction or decision. This involves developing techniques that allow us to interpret the model's internal logic, identify the factors that influence its outputs, and assess its reliability and potential biases.

Visit the following resources to learn more:

• @article@What is Explainable AI (XAI)?
• @article@Explainable AI (XAI) | Giskard
• @video@Explainable AI: Demystifying AI Agents Decision-Making