Interpretability
The degree to which a human can understand the internal mechanics and causal relationships within an AI model's decision-making process.
In plain language
How easy it is to understand why an AI made a decision. A simple decision tree is very interpretable; you can follow each yes-no branch. A massive neural network is much harder to interpret.
Why this matters
Interpretability is essential for effective AI governance and regulatory compliance. Your organisation can only audit, validate and oversee AI systems if you can understand their reasoning. Poor interpretability hides risks and makes it difficult to demonstrate responsible AI practices to regulators or affected parties.
Relevance
GovernanceInterpretability enables your organisation to audit AI decisions, identify bias and meet transparency obligations under emerging AI regulation.
Related terms
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