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Explainable AI (XAI)
Explainable AI (XAI) is a set of methods and techniques that focus on making AI models more understandable and transparent to humans. It aims to reveal how an AI system arrived at a particular decision or prediction, rather than just providing the output. This involves providing insights into the model's internal workings, feature importance, and rationale.
In plain terms
It's like a doctor explaining the diagnosis and treatment plan, instead of just handing you a prescription.
Why it matters
XAI is crucial for building trust, ensuring fairness, debugging models, and complying with regulations, especially in critical applications like medicine or finance.
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