analyze the conditional probability of predicting “poverty”given that the average light intensity is zero: The lightsmodel predicts “poverty” almost 100% of the time, thoughonly 51% of groups with zero average intensity are actu-ally below the poverty line. Furthermore, only 6% of groupswith nonzero average light intensity are below the povertyline, explaining the high recall of the lights model. In con-trast, the transfer model predicts “poverty” in 52% of groupswhere the average nighttime light intensity is 0, more accu-rately reﬂecting the actual probability. The transfer modelfeatures (visualized in Figure 2) clearly contain additional,meaningful information beyond what nighttime lights canprovide. The fact that the transfer model outperforms thelights model indicates that transfer learning has succeeded.