2021-03-04, 05:51 PM
AI is wrestling with a replication crisis
Will Douglas Heaven
Will Douglas Heaven
Quote:Last month Nature published a damning response written by 31 scientists to a study from Google Health that had appeared in the journal earlier this year. Google was describing successful trials of an AI that looked for signs of breast cancer in medical images. But according to its critics, the Google team provided so little information about its code and how it was tested that the study amounted to nothing more than a promotion of proprietary tech.
“We couldn’t take it anymore,” says Benjamin Haibe-Kains, the lead author of the response, who studies computational genomics at the University of Toronto. “It's not about this study in particular—it’s a trend we've been witnessing for multiple years now that has started to really bother us.”
Haibe-Kains and his colleagues are among a growing number of scientists pushing back against a perceived lack of transparency in AI research. “When we saw that paper from Google, we realized that it was yet another example of a very high-profile journal publishing a very exciting study that has nothing to do with science,” he says. “It's more an advertisement for cool technology. We can’t really do anything with it.”