Explainable AI vs Black Box AI: Understand the Key Differences 🤖

In this video, we break down the key differences between Explainable AI and Black Box AI. Explainable AI refers to AI systems designed to provide insights into how decisions are made, offering transparency and accountability. In contrast, Black Box AI operates with complex algorithms that make decisions without any explainable insights, making it challenging to understand the "why" behind the outcomes. Join us as we explore the pros, cons, and real-world applications of each approach, and discuss why explainability in AI is increasingly critical in fields like healthcare, finance, and autonomous vehicles.

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