Big data and prediction: Four case studies
In: Studies in History and Philosophy of Science Part A, Jg. 81 (2020-06-01), S. 96-104
unknown
Zugriff:
Has the rise of data-intensive science, or ‘big data’, revolutionized our ability to predict? Does it imply a new priority for prediction over causal understanding, and a diminished role for theory and human experts? I examine four important cases where prediction is desirable: political elections, the weather, GDP, and the results of interventions suggested by economic experiments. These cases suggest caution. Although big data methods are indeed very useful sometimes, in this paper's cases they improve predictions either limitedly or not at all, and their prospects of doing so in the future are limited too.
Titel: |
Big data and prediction: Four case studies
|
---|---|
Autor/in / Beteiligte Person: | Northcott, Robert |
Link: | |
Zeitschrift: | Studies in History and Philosophy of Science Part A, Jg. 81 (2020-06-01), S. 96-104 |
Veröffentlichung: | Elsevier BV, 2020 |
Medientyp: | unknown |
ISSN: | 0039-3681 (print) |
DOI: | 10.1016/j.shpsa.2019.09.002 |
Schlagwort: |
|
Sonstiges: |
|