Explainable AI (XAI)

Ethics and Safety

Techniques for making AI decisions understandable to humans - answering why the model decided what it decided.

Deep learning models are black boxes: they output a decision but not a reason. Explainable AI is the toolbox for opening the box - showing which inputs drove a decision, which parts of an image the model looked at, or what would need to change for a different outcome.This is not academic. A rejected loan applicant deserves a reason, a doctor cannot act on a diagnosis nobody can justify, and regulations like the EU AI Act increasingly demand explanations for high-stakes automated decisions.