Why Your AI Models Are Confidently Wrong
transcript
show notes
Most data scientists measure model success by accuracy, but accuracy is a trap when the cost of error is asymmetric. This episode explores why precision and recall matter more than raw correctness in high-stakes environments like credit scoring and medical diagnostics. We look at how leading firms are shifting from generic benchmarks to business-aligned metrics that reflect real-world consequences. You will learn how to calculate the true cost of false positives versus false negatives and why your current dashboard might be lying to you about performance.
#FexingoBusiness #BusinessPodcast #DataScience #MachineLearning #AIAnalytics #ModelMetrics #PrecisionAndRecall #FalsePositives #FalseNegatives #CreditScoring #RiskManagement #BusinessStrategy #TechLeadership #DataEthics #AlgorithmicBias #FinancialTechnology #HealthcareAI #OperationalExcellence
