8 habits of highly effective fraudsters

Scientists aren't always right. In fact, individual research papers turn out to be wrong pretty often and scientists are the first people to tell you that they don't know everything there is to know. They're just working on it with more rigor than most of us.

But scientists are also people. And sometimes, they lie. At Ars Technica, John Timmer looks at some of the most famous cases of scientific fraud and comes away with 8 key lessons that show us how science's biggest scam artists got away with faking their data—sometimes for years.

1) Fake data nobody ever expects to see. If you're going to make things up, you won't have any original data to produce when someone asks to see it. The simplest way to avoid this awkward situation is to make sure that nobody ever asks. You can do this in several ways, but the easiest is to work only with humans. Most institutions require a long and painful approval process before anyone gets to work directly with human subjects. To protect patient privacy, any records are usually completely anonymized, so no one can ever trace them back to individual patients. Adding to the potential for confusion, many medical studies are done double-blind and use patient populations spread across multiple research centers. All of these factors make it quite difficult for anyone to keep track of the original data, and they mean that most people will be satisfied with using a heavily processed version of your results.

3) Tell people what they already know. Since you don't want anyone excited about your work, due to the likelihood they will ask annoying questions, you need to avoid this reaction at all costs. Under no circumstances should your work cause anyone to raise an intrigued eyebrow. The easiest way to do this is to play to people's expectations, feeding them data that they respond to with phrases like "That's about what I was expecting." Take an uncontroversial model and support it. Find data that's consistent with what we knew decades ago. Whatever you do, don't rock the boat.

Read the rest of the list at Ars Technica


  1. I suspect the most common and most successful form of scientific fraud is very simple: Throw out the results that don’t support your story.

    1.  That supposes you are actually performing research as opposed to cooking up results out of thin air.

      For actual research you have to distinguish between “cherry picking”  data (e.g. throw out all patients that didn’t respond positively to a drug) v.s. not including say some measurement that doesn’t seem to support the theory or go against it  that you have no understanding of or explanation for.

    2. Traditionally*, scientists aren’t expected to reach a particular conclusion, they’re just expected to gather some data and reach a conclusion, whatever it may be.  So the data that disproves your story is actually still somewhat valuable…possibly even publishable.  Throwing out your data just means that you spent a bunch of time and money and have nothing to show for it.

      * excluding, of course, the whole corrupt world of corporate scientific findings-for-hire, in which you can pretty much reverse everything I’ve said in this comment.

      1. You’re right, but… unfortunately throwing out your data doesn’t just mean that you spent a bunch of time and money and have nothing to show for it. It also means that future funding is more difficult to come by, and your job is at risk if you don’t publish anything – even though your results are useless.

        The whole “publish or perish” thing is what drives most scientific fraud. Realistically, most science gives negative results or otherwise fails. But despite the failures being just as useful as successes, nobody is interested in the failures. So everything has to be framed as a success. Often this is possible, but not always. 

        If you’re months or years into a research project and find that you’re stuck with essentially nothing even remotely publishable, through no fault of your own, you’re screwed if you’re not a tenured university professor (and these days most people doing the most risky/speculative research aren’t). It can ruin your career entirely. So a lot of BS gets published. 

        I have personal experience with this and let me tell you, it is heartbreaking to realize that the research you’ve spent months/years working on is useless. I decided not to BS it and did not try to publish my master’s research. I’ve been unemployed ever since and my chances of going back to school are not the greatest.

  2. Most of the advice applies only if the fraudster’s goal is to have a long, secure, but not especially distinguished scientific career. Many of the frauds that I can recall have been detected because the researchers involved *wanted* to make a splash, so point 3) in particular was not a piece of advice they could have followed.

  3. Gregg Braden, in my opinion, is a master of pushing fake pseudoscience (do they offer that degree?) –  Why do so many people believe this guy, or pay him anything for seminars, or buy his books/dvds/any other bullspit he offers?

  4. If applied with Dilbertism,  Research is always a finagle. 

    Or as they say, “Inconclusive. More funding required.” When the funding dries up, the published content may be refutable, with an argument that, hence the lack of funding to back up the premise makes it refutable. Such is the swindle.

Comments are closed.