Ebook
![Black-Box vs. Explainable AI: How to Reduce Business Risk and Infuse Transparency]()
Black-Box vs. Explainable AI: How to Reduce Business Risk and Infuse Transparency
A key challenge on the journey to Enterprise AI will be figuring out how to balance model performance and interpretability stemming from the difference between black-box and white-box models.As organizations scale their data science, machine learning, and AI efforts, they are bound to reach this impasse, learning when to prioritize white-box models over black-box ones (because there is a time and a place for those) and how to infuse explainability along the way.
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In this ebook, we’ll describe the trade-offs between white-box and black-box models, break down what these concepts really mean, and highlight the rise of explainable AI as a powerful mitigating force that enables modelers, regulators, and laypeople to have more trust and confidence in their models.
