Transparency involves making AI systems understandable and providing clear information about how they operate. This principle highlights the need for openness about AI decision making processes, including that users ought to be informed about how AI systems work, the data they utilize, and the algorithms they employ. Transparency fosters trust and accountability.

In the financial sector, AI algorithms are often used for credit scoring. Adhering to transparency principles might cause a bank to provide customers with detailed explanations of how their credit scores are calculated, including the factors considered and their respective weights. This helps customers understand and trust the AI workload and its underlying infrastructure, models, and grounding data.