Measuring the predictability of life outcomes with a scientific mass collaboration
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8398.full.pdf
Description
Published version
Size
1.41 MB
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Unknown
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Author(s)
Almaatouq, Abdullah
Pentland, Alex
Suhara, Yoshihiko
Jahani, Eaman
Alhajri, Abdulla Abdulaziz
Date Issued
2020
Journal
Proceedings of the National Academy of Sciences of the United States of America
Publisher
Proceedings of the National Academy of Sciences
Version
Final published version
Abstract
© This open access article is distributed under Creative Commons Attribution-NonCommercialNoDerivatives License 4.0 (CC BY-NC-ND). 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.
MIT Department
Sloan School of Management
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1073/PNAS.1915006117
