Explainability Techniques for Black Box Models

Imagine entrusting critical decisions, such as medical diagnoses, loan approvals, or autonomous vehicle operations, to an AI system that provides answers without offering any insight into how those conclusions were reached. This enigmatic behavior raises serious questions about accountability, transparency, and the ethical implications of AI-driven decision-making.

In this lesson, we’ll delve into the challenges posed by black box AI systems, understand the need for diverse explainability approaches, and study some of the popular XAI approaches used in the pursuit of responsible and ethical AI-driven solutions.