Reproducibility
The ability to consistently recreate the same AI model results given the same data, code and computational environment, a foundational requirement for trustworthy and auditable AI systems.
In plain language
The ability to get the same AI results when you run the same experiment again. This is crucial for trust; if you cannot reproduce results, you cannot verify them or prove how the AI made a decision.
Why this matters
Reproducibility is a governance and compliance requirement. If regulators or auditors ask you to demonstrate how an AI system reached a decision, you need to be able to reproduce the result. Your governance framework should mandate reproducibility standards and version control practices for all AI systems.
Relevance
GovernanceReproducible AI systems enable organisations to satisfy regulatory audit requirements, support legal defence if decisions are challenged and maintain confidence that system behaviour is deterministic and understood.
Related terms
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