1) Ground-truth vs. predictive model selection differ under noisy and scarce data—for prediction, oversimplified models may work better in avoiding overfitting.
2) When humans decide between externally provided, prefitted predictive models, they're undersensitive to 1).
osf.io/preprints/ps...
People violate Occam's razor when selecting between predictive models. This is surprising given past research (including my own) showing a preference for simplicity.
1) Ground-truth vs. predictive model selection differ under noisy and scarce data—for prediction, oversimplified models may work better in avoiding overfitting.
2) When humans decide between externally provided, prefitted predictive models, they're undersensitive to 1).