Opaque AI models, particularly deep learning systems, can inadvertently harbor implicit biases, making it difficult to identify or understand their decision-making processes. Adopting transparent and explainable AI architectures facilitates the identification of biases within the system. Explainable AI can help developers and users understand how decisions are made, offering insights into potential bias and providing clearer avenues for mitigation.

Opaque AI models, particularly deep learning systems, can inadvertently harbor implicit biases, making it difficult to identify or understand their decision-making processes. Adopting transparent and explainable AI architectures facilitates the identification of biases within the system. Explainable AI can help developers and users understand how decisions are made, offering insights into potential bias and providing clearer avenues for mitigation.

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