Dr. Bik is a microbiologist who has worked at Stanford University and for the Dutch National Institute for Health who is “blessed” with “what I’m told is a better-than-average ability to spot repeating patterns,” according to their new Op-Ed in the New York Times.
In 2014 they’d spotted the same photo “being used in two different papers to represent results from three entirely different experiments….” Although this was eight years ago, I distinctly recall how angry it made me. This was cheating, pure and simple. By editing an image to produce a desired result, a scientist can manufacture proof for a favored hypothesis, or create a signal out of noise. Scientists must rely on and build on one another’s work. Cheating is a transgression against everything that science should be. If scientific papers contain errors or — much worse — fraudulent data and fabricated imagery, other researchers are likely to waste time and grant money chasing theories based on made-up results…..
But were those duplicated images just an isolated case? With little clue about how big this would get, I began searching for suspicious figures in biomedical journals…. By day I went to my job in a lab at Stanford University, but I was soon spending every evening and most weekends looking for suspicious images. In 2016, I published an analysis of 20,621 peer-reviewed papers, discovering problematic images in no fewer than one in 25. Half of these appeared to have been manipulated deliberately — rotated, flipped, stretched or otherwise photoshopped. With a sense of unease about how much bad science might be in journals, I quit my full-time job in 2019 so that I could devote myself to finding and reporting more cases of scientific fraud.
Using my pattern-matching eyes and lots of caffeine, I have analyzed more than 100,000 papers since 2014 and found apparent image duplication in 4,800 and similar evidence of error, cheating or other ethical problems in an additional 1,700. I’ve reported 2,500 of these to their journals’ editors and — after learning the hard way that journals often do not respond to these cases — posted many of those papers along with 3,500 more to PubPeer, a website where scientific literature is discussed in public….
Unfortunately, many scientific journals and academic institutions are slow to respond to evidence of image manipulation — if they take action at all. So far, my work has resulted in 956 corrections and 923 retractions, but a majority of the papers I have reported to the journals remain unaddressed.
Manipulated images “raise questions about an entire line of research, which means potentially millions of dollars of wasted grant money and years of false hope for patients.” Part of the problem is that despite “peer review” at scientific journals, “peer review is unpaid and undervalued, and the system is based on a trusting, non-adversarial relationship. Peer review is not set up to detect fraud.”
But there’s other problems. Most of my fellow detectives remain anonymous, operating under pseudonyms such as Smut Clyde or Cheshire. Criticizing other scientists’ work is often not well received, and concerns about negative career consequences can prevent scientists from speaking out. Image problems I have reported under my full name have resulted in hateful messages, angry videos on social media sites and two lawsuit threats….
Things could be about to get even worse. Artificial intelligence might help detect duplicated data in research, but it can also be used to generate fake data. It is easy nowadays to produce fabricated photos or videos of events that never happened, and A.I.-generated images might have already started to poison the scientific literature. As A.I. technology develops, it will become significantly harder to distinguish fake from real.
Science needs to get serious about research fraud.
Among their proposed solutions? “Journals should pay the data detectives who find fatal errors or misconduct in published papers, similar to how tech companies pay bounties to computer security experts who find bugs in software.”