AI: Another Crisis!
April 25, 2019
Science, in today’s post modern world, seems to face crisis after crisis. Religious zealots, political fanboyz, and talking head news are often the triggers, but lack of funding and support are a modern cause. Machine learning is creating a new crisis in science says BBC article, “AAAS: Machine Learning ‘Causing Science Crisis.’”
According to Dr. Genevera Allen from Rice University that an increased reliance on machine learning in scientific studies has led to a crisis. She presented her research on this topic at the American Association for the Advancement of Science, where she warned scientists that if they did not improve their techniques they were wasting precious time and money. More scientific studies rely on machine learning to digest and gather results from data. The data sets are huge and are also expensive.
“But, according to Dr. Allen, the answers they come up with are likely to be inaccurate or wrong because the software is identifying patterns that exist only in that data set and not the real world. ‘Often these studies are not found out to be inaccurate until there’s another real big dataset that someone applies these techniques to and says ‘oh my goodness, the results of these two studies don’t overlap’ she said. ‘There is general recognition of a reproducibility crisis in science right now. I would venture to argue that a huge part of that does come from the use of machine learning techniques in science.’”
The reproducibility crisis means that when an experiment is repeated, scientists cannot replicate the results. Being able to reproduce results is a core practice in the scientific method, a tried and true method that annoys school children but ensures accuracy. When the results cannot be reproduced, it means the first set of results are wrong. It is possible that up to 85% of biomedical research done in the world is not accurate. Is machine learning making scientists lazy? If these results are applied in the real world, it could be worse than lack of funding and possibly religious zealots…possibly.
Whitney Grace, April 25, 2019
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