Measuring the predictability of life outcomes with a scientific mass collaboration
Date
2020-04
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
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.
Description
Keywords
Citation
Salganik, Matthew J., Ian Lundberg, Alexander T. Kindel, Caitlin E. Ahearn, Khaled Al-Ghoneim, Abdullah Almaatouq, Drew M. Altschul, et al. “Measuring the Predictability of Life Outcomes with a Scientific Mass Collaboration.” Proceedings of the National Academy of Sciences 117, no. 15 (March 30, 2020): 8398–8403. doi:10.1073/pnas.1915006117.
Collections
Endorsement
Review
Supplemented By
Referenced By
Creative Commons license
Except where otherwised noted, this item's license is described as © This published version is made available under the CC-BY-NC-ND 4.0 license.