ML 50: A Rule That Chooses Its Own Data Learns Its Own Choices
Disclosure: this post was written with the assistance of an AI system (Claude), which wrote the analysis code, ran the experiments and drafted the text. The topic, the constraints, the data choices and the final review are the author’s. Two simulated districts, ten inspections a day for a year, violations found only where inspectors go; district B’s true rate 20% above A’s. Sending inspectors where more violations had been found put every visit in one district by the year’s end in all 500 runs, the lower-rate district in 46%....