global
What It Means
A global explanation is a simplified model that mimics how a complex AI system makes decisions across all possible inputs. Instead of explaining individual predictions, it creates an overall map of how the AI behaves, showing the general patterns and rules the system follows.
Why Chief AI Officers Care
Global explanations help CAIOs demonstrate to regulators and stakeholders that their AI systems operate according to understandable business logic rather than unpredictable black boxes. They're essential for meeting regulatory requirements like the EU AI Act and for identifying potential bias or unfair decision patterns that could create legal or reputational risks.
Real-World Example
A bank uses a complex neural network for loan approvals but creates a global explanation using a simpler decision tree that shows the system generally prioritizes credit score above 650, employment history over 2 years, and debt-to-income ratio below 40%. This allows executives to verify the AI aligns with their lending policies and explain the approach to regulators.
Common Confusion
People often confuse global explanations with local explanations, which explain individual decisions rather than overall system behavior. Global explanations show the forest while local explanations show individual trees.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare AI, global explanations reveal how diagnostic or treatment recommendation models behave across entire pati...
Finance: In finance, global explanations help Chief AI Officers understand how AI models make decisions across entire portfolios ...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"A global explanation produces a model that approximates the non-interpretable model."Source: NISTIR_8312_Full
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