Growing pains: Reacting to negative impacts of deep learning on machine learning for chemistry

23 November 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that deep learning has potential negative impacts on the scientific community and society as a whole. An ever-growing need for more computational resources may exacerbate the concentration of funding and the exclusiveness of research between countries, sectors, and institutions. Here, I introduce recent concerns and considerations of the machine learning research community and present potential solutions.


machine learning
artificial intelligence
language models
sociology of science


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