AI transparency refers to the ability to understand and explain how an AI system makes decisions. Requirements vary by jurisdiction. Under CPRA, businesses using ADMT must provide consumers with information about how automated decisions are made. The NIST AI RMF addresses transparency under the Govern and Measure functions. Verify current regulatory requirements in your jurisdiction.
Transparency requirements generally cover three areas. Algorithmic transparency means documenting how a model was built, what data it was trained on, and its known limitations. Process transparency means having defined procedures for when and how AI is used in decisions. Outcome transparency means providing affected individuals with meaningful information about AI-driven decisions that affect them.
For organizations operating in the EU, the EU AI Act imposes transparency requirements on high-risk AI systems that may extend to US-based organizations whose AI outputs are used in Europe - verify current EU AI Act timelines and applicability.
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