Big data and prediction: Four case studies

Northcott Robert

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Big data and prediction: Four case studies

机译：大数据和预测：四个案例研究

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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.

机译：数据密集型科学的兴起还是“大数据”，彻底改变了我们预测的能力？它是否暗示了对因果理解的预测的新优先事项，以及理论和人类专家的角色减少？我研究了一个需要预测的四个重要案例，所以可以：经济实验建议的政治选举，天气，GDP和干预措施的结果。这些案件建议谨慎。虽然有时大数据方法有时非常有用，但在本文的情况下，他们完全有限或根本完全改善预测，而且他们未来的前景也有限。

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《Studies in history and philosophy of science》 |2020年第6期|96-104|共9页
作者
Northcott Robert;
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作者单位

Univ London Birkbeck Coll Dept Philosophy Malet St London WC1E 7HX England;

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原文格式 PDF
正文语种 eng
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关键词
Big data; Prediction; Case studies; Explanation; Elections; Weather;

机译：大数据;预测;案例研究;解释;选举;天气;

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Big data and prediction: Four case studies

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