When AI Knows It Doesn’t Know: Turning Uncertainty into Strategic Advantage
In AI circles, accuracy improvements are often the headline. But in high-stakes sectors—healthcare, finance, autonomous transport—the more transformative capability is an AI that knows when not to act. Stephan Rabanser’s PhD thesis on uncertainty-driven reliability offers both a conceptual foundation and an applied roadmap for achieving this. From Performance Metrics to Operational Safety Traditional evaluation metrics such as accuracy or F1-score fail to capture the asymmetric risks of errors. A 2% misclassification rate can be negligible in e-commerce recommendations but catastrophic in medical triage. Selective prediction reframes the objective: not just high performance, but performance with self-awareness. The approach integrates confidence scoring and abstention thresholds, creating a controllable trade-off between automation and human oversight. ...