Critical decisions like loan approvals, medical interventions, and college admissions are guided by predictions made in the presence of uncertainty. In this paper, we prove that uncertainty has a disparate impact. While it imparts errors across all demographic groups, the types of errors vary systematically: Groups with higher average outcomes are typically assigned higher false positive rates, while those with lower average outcomes are assigned higher false negative rates. We show that additional data acquisition can eliminate the disparity and broaden access to opportunity. The strategy, which we call Affirmative Information, could stand as an alternative to Affirmative Action.