At the American Society for Microbiology annual meeting this past weekend, microbiologist Nick Loman of the University of Birmingham spoke about the promise and perils of artificial intelligence in biology. Although microbial geneticists such as Loman are beginning to harness the computational power of machine learning to analyze their data, Loman cautions that many scientists have plunged ahead with using AI before really understanding its benefits—and limitations.
The Scientist sat down with Loman in San Francisco to chat further.
The Scientist: Are there areas in biology where there have been large amounts of enthusiasm for these approaches? And what are some of the reasons for that?
Nick Loman: Definitely in this kind of -omics space people are getting excited about machine learning simply because these are data sets with millions, billions, even trillions of data points and there was no alternative way to analyze them. It’s also of particular interest ...
