Explainable AI (XAI)
Explainable AI (XAI) refers to methods and techniques that allow human users to understand and interpret the predictions and decisions made by AI systems. It aims to make complex 'black box' models transparent, revealing why a particular outcome was reached. This helps build trust and identify potential biases or errors in AI models.
Think of Explainable AI as a brilliant, but formerly silent, chef now able to tell you exactly why they chose each ingredient and cooking step to create a dish, rather than just presenting the final meal.
XAI is critical for deploying AI in sensitive domains like healthcare or finance, where understanding the reasoning behind an AI's decision is as important as the decision itself for accountability and safety.
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