Machine learning is contributing to a “reproducibility crisis” within science

Washington DC (SPX) Feb 18, 2019 Rice University statistician Genevera Allen says scientists must keep questioning the accuracy and reproducibility of scientific discoveries made by machine-learning techniques until researchers develop new computational systems that can critique themselves. Allen, associate professor of statistics, computer science and electrical and computer engineering at Rice and of pediatrics-neurolog

AAAS: Machine learning 'causing science crisis'

Techniques used to analyse data are producing misleading and often wrong results, critics say.

Sat 16 Feb 19 from BBC News

Can we trust scientific discoveries made using machine learning?

Rice University statistician Genevera Allen says scientists must keep questioning the accuracy and reproducibility of scientific discoveries made by machine-learning techniques until researchers ...

Fri 15 Feb 19 from TechXplore

Can we trust scientific discoveries made using machine learning?, Tue 19 Feb 19 from SpaceDaily

Machine learning-based discoveries still need to be checked by humans

Researchers at Rice University want scientists to continue double-checking discoveries made using machine learning.

Mon 18 Feb 19 from UPI

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