Dan Ariely has a long history of controversies and studies with falsified data. He wrote 3 popular books and gained a lot of fame before others started uncovering the problems in his studies

https://en.wikipedia.org/wiki/Dan_Ariely

It’s amazing that problems with his studies are still being uncovered. Equally amazing that Duke still maintains a relationship with him after so many problems have been identified with his research.

Science is self-correcting, but sometimes, the correction mechanism it is very slow and inconsequential enough that people are incentivized to just publish anything. Peer review is merely a quality check—and not a very good one. Just the other day, I ran into a paper in my field that claims to have solved a central problem that scientists have been working on for 50 years, single-authored, using some fancy mathematics. I was excited to read it, but it didn't take long for me to find out that it's complete BS-derivations that don't follow, made-up equation terms, and conflation of basic terms in the field. I was really surprised that this passed the editor and at least two peer reviewers. I dug deeper and found that the same author has published 11 research articles in top journals in 2026 alone — mostly physics and chemistry, and adjacent fields— and I'm talking about really top journals like Scientific Reports and Physics Letters B. Most of these have serious mathematical flaws that are unfixable. I wrote to a couple of editors, but only one took it seriously enough to initiate an investigation. I made a promise to myself that if no real action is taken, I will seriously consider changing careers.

It does seem like its way too easy to do this kind of fraud.

The study seems extremely easy to replicate (no fancy equipment needed, just ask some people to proofread), and yet nobody did until now. Is there some way to change incentives to get people to try and replicate? Assign undergrads to replicate random research papers?

No paper should ever be referenced until it has been replicated by an independent group. The replication crisis in science is real, and it won't take long for no one to believe anything anymore.

I came here for a procrastination joke comment and didn't find it, but I suppose someone will get around to it eventually.

Dan Ariely is well past the point that he needs to not be a faculty member at Duke University. Data Coda do a fantastic job ferreting out academic fraud. With these fraudulent behavioral science experiments like this relying on printed papers/markups, and coauthors not present and who did not even see the raw data, I wonder if the experiment was ever actually conducted. I would love to see that question answered where fraud is suspected, something I'd hope IRBs would step up to do.

I'm glad the authors seem to have acknowledged the problem and not doing much about it :-)

One thing I didn't know before reading this: an unusually large effect size can itself be a red flag. You don't have to understand all the statistics to at least notice when a result looks almost too good to be true.

Having skimmed this article and the replication study itself (which references some studies that complicate our common understanding of the positive effects of deadlines) I’m left wondering what the constructive alternative is to deadlines and/or how deadlines should be maintained or determined.

I hope that with LLMs we'll see a lot faster identification of these anomalies. Imagine that this guy taught at MIT and has his own lab at Duke, basically more than 20 years of taking up some of the most prestigious positions in his field, all based on fraud.

The butterfly effect this has on science as a practice is huge. Some marginal researcher who actually deserved it was bumped out of those places, and somewhere down the line someone was bumped all the way out of academia because of this guy's lies. And this is hardly the only person in this situation.

What's scary is that the next fraudster will read this take down and see what they have to do to avoid detection. It wouldn't be that hard to form data that looks a lot more plausible. Replication may be the only solution, unfortunately it's so expensive and time consuming, without any of the actual benefits of doing the original study. Maybe it should be government funded, the US replication lab, its only mission to replicate the top X papers from some named fields each year.

It's shocking to me how badly the data was falsified. You'd think a researcher who is A. well versed in statistics and B. has seen a lot of actual research data would be able to produce more believable data. Does this mean we're only seeing the tip of the iceberg? how many papers are based on hard to detect falsifications?

There is such a smell around this whole literature.

I wonder what it's like to be a grad student in social psychology right now. When the norm is surprising results, any responsible, competent researcher is going to realize that they can't do it honestly. So this leaves behind people who are willing to bend the rules, or people who don't see the problem with, for example, the garden of forking paths.

People for a long time have had far too much faith in peer review as and had a dim view of anything other then experimental results and work, despite how much fraud and just bad experiments their are. Not to mention how many variables their might actually be to account for in something like psychology or any of the social science's.

Deriving things from axioms and postulates alone is problematic but some one who can do both begins to actually do useful work in my opinion and some one who can accept the difficult their actually is in knowing anything about human psychology simply from studying it and underneath all experiments is assumptions and the people in the experiment who have so many variables. This is not like medicine human psychology is very flexible and for me though not a social scientist I feel of all theories of human psychology they are only applicable to people now and not even 300 years ago, though of course one must concede that the micro psychological principles might be applicable to humans more generally.

Short of blindly outsourcing the work to an LLM and checking to see if its hallucinated problems are actually problems[0], how can more laymen (without the ability to run replication studies, and without degrees in statistics) learn to more easily identify questionable/potentially fraudulent research like this?

This is a question that has been really bothering me for a while. I have a short list of things I’ve learnt to check, but it’s all stuff I’ve picked up in a very ad hoc way (reading and listening to these kinds of critical analyses, mostly). For example, until now, I wouldn’t think about implausibly large Cohen’s d, despite this seeming like an easily generalisable rule that anyone could eyeball. But without being told, and without the reference points given in the article, I wouldn’t have a clue. And I would like to have more of a clue. And I would like other people to have more of a clue. How?

[0] https://smackernews.com/item/49484925 HN

Sure. The guy put it off until the last minute, and then had to fake his way through it. It writes itself.

The reason why people(or ai agents) have not been able to systematically destroy bad research in fields where fraud is so rampant is because they data are not published or easily accessible without emailing the author and asking them.

I sincerely hope that any self respectful journal that publishes papers should have a minimum bar: submit the data on a public link with no paywall or blockers and feature the link prominently on your paper.

Dan Ariely remaining at Duke, after it has become clear that much if not most of his work is fraudulent, is at least as big a black mark for Duke as Jason Arday was for Cambridge.

Not to mention the Epstein ties.

The last point in the OA about rounding the estimate of the time spent on the assigned tasks. Just wondering if the response would depend on the wording of the instructions to participants and the nature of the incentivisation.

Me being a bit of a boy scout / Belbin 'company worker', I would tend to use a timer (I'm a pomodoro method person for things like marking or checking references &c).

The rest, oh yes. I stopped paying much attention to studies based on dozens of undergraduates doing weird concocted tasks years ago.

They probably procrastinated all their deadlines and then fibbed things.

So this paper appears to be fabricated, but was the conclusion actually wrong? I do appear to perform better on tasks with an external deadline than on self-set ones.

Figures, even the studies about procrastination are fraught with issues. Guess I'll put off reading the details until tomorrow.

this image https://datacolada.org/wp-content/uploads/scatter_like_vs_in... itself visually shows fake data. Too perfectly clustered.

At the risk of bringing up a controversial topic, in the midst of the Jason Arday furore last month when everyone was like "this wouldn't happen to a white professor", the person who kept coming to mind for me was Ariely. I became a data scientist in no small part due to his early work, and seeing academia totally incapable of punishing him is deeply disappointing.

What should I do now with the 4+ books authored by Ariely that I have sitting on my shelf?

There's a bit of irony that probably 50% of us are procrastinating while reading this

I'll get around to reading this at some point.

Procrastination: They couldn't be bothered.-

"Trust the science" is one of the most anti-science phrases ever invented. The whole point of science is to challenge everything.

The name of the place should be enough of a giveaway for any thinking person Center for Advanced Hindsight.

SMH.

And yet it will live forever, just like Dunning-Kruger despite its statistical issues. I fully expect to see it cited during some workshop or other pointless training exercise.

Oh the irony...