How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

While significant scholarship has documented the prevalence of racial discrimination in hiring, less is known about the forces that exacerbate or mitigate it. In this article, we develop a theoretical argument about the ability of customers to influence racial discrimination in hiring, highlighting the role of direct customer communication and its intersection with online review systems. We deploy a novel method to test our argument. Specifically, we draw on original data from a two-part field experiment that first randomly assigned restaurants to receive one of three different email messages from customers and then audited the restaurants to test for racial discrimination in hiring. While our data collection effort was cut short and disrupted by the coronavirus pandemic, making our findings more exploratory than initially anticipated, our data provide evidence that customer communication can reduce racial discrimination under certain conditions. We discuss the implications of these findings for scholarship on organizational decision-making, discrimination, and methodological approaches for studying these topics.

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