Okay, this sounds bad.
, a surprising number of scientists using these systems may be making grave methodological errors — and if that trend continues, the ripple effects in academia could be pretty severe., the duo became concerned when they came across a political science study that, using machine learning-produced data, claimed it could predict the next civil war with a staggering 90 percent accuracy.
After discovering the data leakage in the civil war paper, the Princeton researchers started searching for similar machine learning mistakes in other published studies — and the results, which they, were striking. They found data leakage in a grand total of 329 papers across a number of fields, including medicine and social sciences.
As they explain in the paper, the proliferation of machine learning is resulting in something they're calling a "reproducibility crisis," which basically means that the results of a study can't be reproduced by followup research.that's shaken the scientific establishment over the past decade, in which researchers misused statistics to arrive at sweeping conclusions that amounted to nothing more than statistical noise in large datasets.
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