Explainable AI (XAI) is a design challenge, not just a data science problem¶
Insight: XAI is fundamentally about answering the user's question "Why?" — why was I shown this, why was my request denied. For users to adopt and rely on AI, they must trust it, built on perceptions of Ability, Benevolence, Integrity, and Predictability. When AI makes opaque decisions, these trust pillars shatter. The article provides concrete design patterns for building explainability into real products, bridging the gap between algorithmic decision-making and human understanding.