Description
Making AI Transparent: A Guide to Model Interpretability
In the era of enterprise AI, model interpretability has become as crucial as model performance. As AI systems make increasingly important decisions, stakeholders demand transparency and understanding of how these decisions are made. This requirement is not just about regulatory compliance—it’s about building trust, managing risk, and enabling effective human oversight.
The challenge lies in balancing sophisticated AI capabilities with clear explanations that business stakeholders can understand and trust. Modern interpretability approaches provide powerful tools to peek inside the “black box” of AI models, offering insights that are both technically rigorous and business-relevant.
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