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EPISODE · Sep 8, 2026 · 10 MIN

How Data Teams Build Explainable AI Systems

from The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations · host Fexingo

We explore why black box models are failing enterprise trust and how data teams are shifting toward inherently interpretable architectures. Using a specific case from a major fintech lender, we look at the trade-off between raw predictive power and regulatory compliance. The episode breaks down three practical techniques for building models that explain themselves without sacrificing accuracy. #ExplainableAI #XAI #ModelInterpretability #DataScience #MachineLearning #FexingoBusiness #BusinessPodcast #TechTrends2026 #RegulatoryCompliance #FinTech #AlgorithmicBias #TrustInAI #DataEthics #LucasAndLuna #AIGovernance #ModelTransparency #EnterpriseAI #DataDriven Keep every episode free: buymeacoffee.com/fexingo

Episode metadata supplied by the publisher feed · Published Sep 8, 2026

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How Data Teams Build Explainable AI Systems

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This episode is 10 minutes long.

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This episode was published on September 8, 2026.

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