Measuring the predictability of life outcomes with a scientific mass collaboration

Date
2020-04Author
Salganik, Matthew J.
Lundberg, Ian
Kindel, Alexander T.
Ahearn, Caitlin E.
Al-Ghoneim, Khaled
Almaatouq, Abdullah
Altschul, Drew M.
Brand, Jennie E.
Carnegie, Nicole B.
Compton, Ryan James
Datta, Debanjan
Davidson, Thomas
Filippova, Anna
Gilroy, Connor
Goode, Brian J.
Jahani, Eaman
Kashyap, Ridhi
Kirchner, Antje
McKay, Stephen
Morgan, Allison
Pentland, Alex
Polimis, Kivan
Raes, Louis
Rigobon, Daniel E.
Roberts, Claudia V.
Stanescu, Diana M.
Suhara, Yoshihiko
Usmani, Adaner
Wang, Erik H.
Baer-Bositis, Livia
Buchi, Moritz
Chung, Bo-Ryehn
Eggert, William
Faletto, Gregory
Fan, Zhilin
Freese, Jeremy
Gadgil, Tejomay
Gagne, Josh
Gao, Yue
Halpern-Manners, Andrew
Hashim, Sophia P.
Hausen, Sonia
He, Guanhua
Higuera, Kimberly
Hogan, Bernie
Horwitz, Ilana M.
Hummel, Lisa M.
Jain, Naman
Jin, Kun
Jurgens, David
Kaminski, Patrick
Karapetyan, Areg
Kim, E. H.
Leizman, Ben
Liu, Naijia
Moser, Malte
Mack, Andrew E.
Mahajan, Mayank
Mandell, Noah
Marahrens, Helge
Mercado-Garcia, Diana
Mocz, Viola
Mueller-Gastell, Katariina
Musse, Ahmed
Niu, Qiankun
Nowak, William
Omidvar, Hamidreza
Or, Andrew
Ouyang, Karen
Pinto, Katy M.
Porter, Ethan
Porter, Kristin E.
Qian, Crystal
Rauf, Tamkinat
Sargsyan, Anahit
Schaffner, Thomas
Schnabel, Landon
Schonfeld, Bryan
Sender, Ben
Tang, Jonathan D.
Tsurkov, Emma
van Loon, Austin
Varol, Onur
Wang, Xiafei
Wang, Zhi
Wang, Flora
Weissman, Samantha
Whitaker, Kristie
Wolters, Maria K.
Woon, Wei Lee
Wu, James
Wu, Catherine
Yang, Kengran
Yin, Jingwen
Zhao, Bingyu
Zhu, Chenyun
Brooks-Gunn, Jeanne
Engelhardt, Barbara E.
Hardt, Moritz
Knox, Dean
Levy, Karen
Narayanan, Arvind
Stewart, Brandon M.
Watts, Duncan J.
McLanahan, Sara
Metadata
Show full item recordAbstract
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.
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.