XAI (Explainable AI)

What is Explainable AI (XAI)?

Explainable AI (XAI) refers to methods and techniques aimed at making the decision-making processes of artificial intelligence (AI) models more transparent and understandable to humans. Traditional AI, especially deep learning models, often function as ‘black boxes’, making it difficult to understand why a specific output was generated. XAI seeks to open this black box, providing insights into the reasoning behind AI’s conclusions. This is crucial for building trust, accountability, and for ensuring fairness and ethical considerations in AI applications. Examples include visualizing the internal workings of a model or providing human-readable explanations for predictions.

Q&A

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