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Beyond Two Cultures: Cultural Infrastructure for Data-driven Decision Support

Authors
  • Freeman, Nikki L. B.
  • Sperger, John
  • El-Zaatari, Helal
  • Kahkoska, Anna R.
  • Lu, Minxin
  • Valancius, Michael
  • Virkud, Arti V.
  • Zikry, Tarek M.
  • Kosorok, Michael R.
Type
Published Article
Journal
Observational studies
Publication Date
Jul 01, 2021
Volume
7
Issue
1
Pages
77–94
Identifiers
DOI: 10.1353/obs.2021.0024
PMID: 35106520
PMCID: PMC8802367
Source
PubMed Central
Keywords
Disciplines
  • Article
License
Unknown

Abstract

In the twenty years since Dr. Leo Breiman’s incendiary paper Statistical Modeling: The Two Cultures was first published, algorithmic modeling techniques have gone from controversial to commonplace in the statistical community. While the widespread adoption of these methods as part of the contemporary statistician’s toolkit is a testament to Dr. Breiman’s vision, the number of high-profile failures of algorithmic models suggests that Dr. Breiman’s final remark that “the emphasis needs to be on the problem and the data” has been less widely heeded. In the spirit of Dr. Breiman, we detail an emerging research community in statistics — data-driven decision support. We assert that to realize the full potential of decision support, broadly and in the context of precision health, will require a culture of social awareness and accountability, in addition to ongoing attention towards complex technical challenges.

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