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4min chapter
Explaining AI explainability
Practical AI: Machine Learning, Data Science, LLM
The Challenges and Expectations of Explainability in AI
Darwin: Machine learning is great at characterizing situations where the rules cannot be codified in human terms. But without explainability, they couldn't understand what are the drivers here? Darwin: The problem with explainability is if you don't understand how a decision is being made, you don't know where it will fail. And so that is why explainability is so important to make more robust networks.
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