Feedback Loop Debt: An Executive Playbook to Detect, Quantify & Control Self‑Reinforcing AI Failures

Adaptive models and live interventions can create feedback loops that silently amplify bias, inflate costs, or erode customer trust—often long before monitoring alarms ring. This episode opens with a short C‑suite vignette where a personalization engine’s recommendations altered customer behavior and produced a runaway cohort drift that doubled churn. Mirko then delivers a pragmatic, non‑technical executive playbook: a taxonomy of feedback‑loop types (instrumentation, behavioral, economic), lightweight detection signals executives can demand (population elasticity, treatment‑response drift, uplift erosion), a simple method to translate loop dynamics into dollars and runway risk, and prioritized remediation lanes (contain, compensate, retrain, redesign). Listeners leave with a 30–90 day pilot blueprint to instrument one adaptive flow, board‑ready KPIs to track loop exposure, and concrete governance and procurement clauses to ensure vendors and teams cannot unknowingly weaponize product adaptivity. Practical, decision-focused steps so leaders keep adaptive AI an accelerant—not a liability. Subscribe to DataScience.Show to get the one‑page Feedback Loop register.

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