by Dr. Elisabeth Bik is a microbiologist who has worked at Stanford University and the Netherlands National Institute of Health, and her strength is above-average repetitive pattern recognition. In 2014 she discovered that the same photo was used in two different papers to represent three completely different experimental results. She is very angry at this type of falsification, because a scientist has to rely on and build on the work of another scientist, and falsification is a betrayal of what science is supposed to do, allowing other researchers to waste time and money on wrong results superior. She didn’t think it was an isolated case, so she started devoting her free time to identifying suspicious images. In 2016 she reported that after analyzing 20,621 peer-reviewed papers, she found that at least one out of every 25 had image problems. In 2019, she quit her full-time job to focus on fighting fakes. After analyzing more than 100,000 papers since 2014, she found 4,800 with significant image duplication and 1,700 with other issues. She reported 2,500 of them to journal editors, posting the results on the PubPeer website after discovering that journals often did not respond. The academic publishing industry has been slow to respond to paper issues, and her work to date has resulted in only 956 revisions and 923 retractions, with most of the reported papers unprocessed. She believes that science needs to take the issue of fake data seriously, and that AI can be used to identify duplicate data as well as generate fake data.
