Elisabeth Bik writes about image manipulation, paper mills and other research integrity problems in published scientific papers.
HN commenters point to it as the blog of Elisabeth Bik and suggest it as a place to take concerns about suspect research.
I feel like this study is missing the forest for the trees. Which section of society has the highest trust in scientists? Probably it's other scientists, closely followed by science journalists. Yet this article is set in the paradigm in which people are divided into "the public" and "scientists", with the latter being universally correct and the former in need of education by the latter.
Over the past few years I've read a lot of scientific papers outside my normal field of reading (computer science/cryptography). My guess is over 100 in the past two years alone, or more if you count scan reading or checking only particular sections to follow up on a citation. The overwhelming impression this left is that many research fields are actually overrun with pseudo-science and that the institutions cannot detect this (or can but prefer not to).
This new study is especially ironic because social psychology is one of the biggest offenders when it comes to spreading misinformation. The entire field is rightly seen as junk due to the prevalence of non-replicable studies on 35 undergrads being generalized to the entire world, which are often then used to demand major political change. This particular study probably will replicate, because the claim it's making is so obvious as to be near tautological, but that is hardly better.
A good example of academic pseudo-science is claims about bots that subtly manipulate people's politics via Twitter. There are around 10,000 published papers…
> People can share data in whatever format they have and it wouldn’t be hard for me or others to import it one way or another.
It's one thing for a highly-skilled user with a decade of experience to be able to import it eventually, another for an unskilled user to just have off-the-shelf tooling do it the same way for everyone automatically. This is more about meta-studies and unlocking new use cases. It sucks that the state-of-the-art for sharing academic microscopy data right now is basically looking at raster images embedded in PDFs, or email the authors, and then write a custom Scikit-Image script. Imagine if you had to read a PDF catalog and then email someone to order something off Amazon, or if your favorite CRUD app consisted instead of having an expert read a PDF and email a screenshots to you. What if sending those very emails to different recipients required implementing each users custom IMAP-like mail client. That sounds absurd, but it's kind of the way academic data sharing works now, lots of people are re-inventing the wheel and creating custom file formats.
Consider, for example, the work of Dr. Bik (example at [1]) who identifies cloned sections from microscopy data. Or what if, instead of each researcher having to generate their own images, or get lucky and remember a particular image there was a Getty Images/AP Newsroom platform where you could just filter for your particular subject and imaging parameters and share your data. A collection of…
I saw a story recently about a school in Kentucky that published student agendas with AI and apparently no human supervision, and it had hallucinated states and elements on the periodic table and the like[0]. This shouldn't happen, even with the most optimistic estimates of AI's capabilities being true, yet there is a cultlike mentality around it that leads people to lose their minds and throw even basic common sense out the window. It's being used to publish garbage scientific papers [1] and rewrite the historical narrative [2]. AI is being used everywhere, with abandon, and seemingly little to no oversight or plan to manage the inevitable consequences of the flood of slop and bullshit that it creates. And then on top of that there is the environmental and economic impact of data centers, the social alienation, deskilling and intellectual rot its use creates, and the fact that the big AI companies all seem to be run by a cult of technofascist psychopaths. And the cherry on the dystopian sundae being that we're told we have no choice, that it's inevitable regardless of the consequences and we just have to adapt to whatever future these psychopaths create for us and whatever role they decide we have in it.
I don't think it's overcorrection so much as a proportional backlash against society losing its mind over this thing.
[0] https://www.fox5vegas.com/2026/08/14/middle-school-student-agendas-contain-misspelled-states-science-errors-raising-ai-questions/
[1]…
Her site is:
https://scienceintegritydigest.com/about/
https://scienceintegritydigest.com/
She wrote an op-ed in the NYT last year: https://www.nytimes.com/interactive/2022/10/29/opinion/science-fraud-image-manipulation-photoshop.html
She says her work has led to 938 papers being retracted.
One of the interesting parts to me is that most of her work seems to be completely manual. She seems to have an eye for seeing photoshop on microscopy images or images of gels. The biggest method of fraud that she seems to find is researchers cutting and pasting from one image to another, for example, the scientist runs a gel but the results don't work out the way they hoped, so they paste in a line from another gel to make the experiment look like it worked.
The uncomfortable part is that this is just one of many ways that you could fabricate or alter research results, and Dr. Bik is only one person finding it in her spare time. Probably a whole lot of fraud goes undetected.
Elisabeth Bik is a real hero. the amount of unpaid hours she has put into detecting fraud in published scientific papers is unbelievable and a true service to the scientific community.
Her work is pure positive externality: nobody has incentive to pay for it. Journals barely care about fraud (as long as it's not caught by someone else), reviewers don't have much incentive to check carefully for it (and might even be in on the fraud), and the authors engaging in fraud obviously prefer that journals not look too closely.
That's why I am a patron: https://www.patreon.com/elisabethbik
She maintains a blog if you want to read more about what she does, e.g.: https://scienceintegritydigest.com/2020/12/31/2020-a-year-in-review/
> and all ads should be blocked
I can feel with your sentiment, but don’t see a practical way to do that.
Define “ad”. Is “read more in my blog” an ad? Is “see Foo’s blog at …” an ad? “Read Foo’s excellent blog”? “Read more here” in a blog entry?
If you say “when it is paid for it’s an ad”, how do you detect that? And what is “paid”? In a webring (https://en.wikipedia.org/wiki/Webring) people reciprocally ‘pay’ each other by providing incoming links, thus all gaining reputation. The difference with a citation ring (https://scienceintegritydigest.com/2022/03/23/citation-statistics-and-citation-rings/) is subtle.
And for true ads, would you want to block a starting blog author from promoting their work online?