Explanation:
The scenario describes a core issue associated with complex AI and machine learning systems: their "black box" nature. Model explainability refers to the ability to understand and interpret how an AI model arrives at its decisions or recommendations. When compliance officers find it challenging to determine whether a recommendation is based on sound financial principles or spurious correlations, they are facing a lack of model explainability, making validation, auditing, and regulatory compliance difficult.
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Q.68 A financial institution is developing a new customer-facing application that uses generative AI to provide tailored financial planning recommendations. During internal reviews, compliance officers raise concerns about the difficulty in validating the recommendations generated by the AI, particularly in complex or edge-case scenarios. They find it challenging to determine whether a recommendation is based on sound financial principles or is a result of spurious correlations learned by the AI. What key challenge associated with generative AI is the institution primarily facing?
A
Model robustness.
B
Data privacy.
C
Model explainability.
D
Computational resource requirements.