The Science Sleuth Holding Fraudulent Research Accountable
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Introduction by Mary Inman, Whistleblower Attorney
For most people, when they see the word "whistleblower," the image that leaps to mind is a lone individual bravely stepping forward to shine a light on misconduct she has witnessed first-hand. Meryl Streep as Karen Silkwood exposing safety violations observed while working the line at the Kerr-McGee plutonium plant. Matt Damon as Mark Whitacre in The Informant!, capturing on his pocket recorder clandestine meetings between his employer and its competitors to fix the price of lysine. However, a new breed of whistleblower is emerging who isn't at the scene of the crime but instead figures it out after the fact through laborious review of publicly available information and expert analysis. Elisabeth Bik belongs to this new class of whistleblower.
"There's this delicate balance where on one hand we want to spread results really fast as scientists, but on the other hand, we know it's incomplete, it's rushed and it's not great."
Using her expertise as a microbiologist and her trained eye, Bik studies publicly available scientific papers to sniff out potential irregularities in the images that suggest research fraud, later seeking retraction of the offending paper from the journal's publisher. There's no smoking gun, no first-hand account of any kind. Just countless hours spent reviewing scores of scientific papers and Bik's skills and dedication as a science fraud sleuth.
While Bik's story may not as readily lend itself to the big screen, her work is nonetheless equally heroic. By tirelessly combing scientific papers to expose research fraud, Bik is playing a vital role in holding the scientific publishing process accountable and ensuring that misleading information does not spread unchecked. This is important work in any age, but particularly so in the time of COVID, where we can ill afford the setbacks and delays of scientists building on false science. In the present climate, where science is politicized and scientific principles are under attack, strong voices like Bik's must rise above the din to ensure the scientific information we receive, and our governments act upon, is accurate. Our health and wellbeing depend on it.
Whistleblower outsiders like Bik are challenging the traditional concept of what it means to be a whistleblower. Fortunately for us, the whistleblower community is a broad church. As with most ecosystems, we all benefit from a diversity of voices —whistleblower insiders and outsiders alike. What follows is an illuminating conversation between Bik, and Ivan Oransky, the co-founder of Retraction Watch, an influential blog that reports on retractions of scientific papers and related topics. (Conversation facilitated by LeapsMag Editor-in-Chief Kira Peikoff)
Elisabeth Bik and Ivan Oransky.
(Photo credits Michel & Co Photography, San Jose, CA and Elizabeth Solaka)
Ivan
I'd like to hear your thoughts, Elisabeth, on an L.A. Times story, which was picking up a preprint about mutations and the novel coronavirus, alleging that the virus is mutating to become more infectious – even though this conclusion wasn't actually warranted.
Elisabeth
A lot of the news around it is picking up on one particular side of the story that is maybe not that much exaggerated by the scientists. I don't think this paper really showed that the mutations were causing the virus to be more virulent. Some of these viruses continuously mutate and mutate and mutate, and that doesn't necessarily make a strain more virulent. I think in many cases, a lot of people want to read something in a paper that is not actually there.
Ivan
The tone level, everything that's being published now, it's problematic. It's being rushed, here it wasn't even peer-reviewed. But even when they are peer-reviewed, they're being peer-reviewed by people who often aren't really an expert in that particular area.
Elisabeth
That's right.
Ivan
To me, it's all problematic. At the same time, it's all really good that it's all getting out there. I think that five or 10 years ago, or if we weren't in a pandemic, maybe that paper wouldn't have appeared at all. It would have maybe been submitted to a top-ranked journal and not have been accepted, or maybe it would have been improved during peer review and bounced down the ladder a bit to a lower-level journal.
Yet, now, because it's about coronavirus, it's in a major newspaper and, in fact, it's getting critiqued immediately.
Maybe it's too Pollyanna-ish, but I actually think that quick uploading is a good thing. The fear people have about preprint servers is based on this idea that the peer-reviewed literature is perfect. Once it is in a peer-reviewed journal, they think it must have gone through this incredible process. You're laughing because-
Elisabeth
I am laughing.
Ivan
You know it's not true.
Elisabeth
Yes, we both know that. I agree and I think in this particular situation, a pandemic that is unlike something our generation has seen before, there is a great, great need for fast dissemination of science.
If you have new findings, it is great that there is a thing called a preprint server where scientists can quickly share their results, with, of course, the caveat that it's not peer-reviewed yet.
It's unlike the traditional way of publishing papers, which can take months or years. Preprint publishing is a very fast way of spreading your results in a good way so that is what the world needs right now.
On the other hand, of course, there's the caveat that these are brand new results and a good scientist usually thinks about their results to really interpret it well. You have to look at it from all sides and I think with the rushed publication of preprint papers, there is no such thing as carefully thinking about what results might mean.
So there's this delicate balance where on one hand we want to spread results really fast as scientists, but on the other hand, we know it's incomplete, it's rushed and it's not great. This might be hard for the general audience to understand.
Ivan
I still think the benefits of that dissemination are more positive than negative.
Elisabeth
Right. But there's also so many papers that come out now on preprint servers and most of them are not that great, but there are some really good studies in there. It's hard to find those nuggets of really great papers. There's just a lot of papers that come out now.
Ivan
Well, you've made more than a habit of finding problems in papers. These are mostly, of course, until now published papers that you examined, but what is this time like for you? How is it different?
Elisabeth
It's different because in the beginning I looked at several COVID-19-related papers that came out and wrote some critiques about it. I did experience a lot of backlash because of that. So I felt I had to take a break from social media and from writing about COVID-19.
I focused a little bit more on other work because I just felt that a lot of these papers on COVID-19 became so politically divisive that if you tried to be a scientist and think critically about a paper, you were actually assigned to a particular political party or to be against other political parties. It's hard for me to be sucked into the political discussion and to the way that our society now is so completely divided into two camps that seem to be not listening to each other.
Ivan
I was curious about that because I've followed your work for a number of years, as you know, and certainly you have had critics before. I'm thinking of the case in China that you uncovered, the leading figure in the Chinese Academy who was really a powerful political figure in addition to being a scientist.
Elisabeth
So that was a case in which I found a couple of papers at first from a particular group in China, and I was just posting on a website called PubPeer, where you can post comments, concerns about papers. And in this case, these were image duplication issues, which is my specialty.
I did not realize that the group I was looking at at that moment was led by one of the highest ranked scientists in China. If I had known that, I would probably not have posted that under my full name, but under a pseudonym. Since I had already posted, some people were starting to send me direct messages on Twitter like, "OMG, the guy you're posting about now is the top scientist in China so you're going to have a lot of backlash."
Then I decided I'll just continue doing this. I found a total of around 50 papers from this group and posted all of them on PubPeer. That story quickly became a very popular story in China: number two on Sina Weibo, a social media site in China.
I was surprised it wasn't suppressed by the Chinese government, it was actually allowed by journalists that were writing about it, and I didn't experience a lot of backlash because of that.
Actually the Chinese doctor wrote me an email saying that he appreciated my feedback and that he would look into these cases. He sent a very polite email so I sent him back that I appreciated that he would look into these cases and left it there.
Ivan
There are certain subjects that I know when we write about them in Retraction Watch, they have tended in the past to really draw a lot of ire. I'm thinking anything about vaccines and autism, anything about climate change, stem cell research.
For a while that last subject has sort of died down. But now it's become a highly politically charged atmosphere. Do you feel that this pandemic has raised the profile of people such as yourself who we refer to as scientific sleuths, people who look critically and analytically at new research?
Elisabeth
Yeah, some people. But I'm also worried that some people who are great scientists and have shown a lot of critical thinking are being attacked because of that. If you just look at what happened to Dr. Fauci, I think that's a prime example. Where somebody who actually is very knowledgeable and very cautious of new science has not been widely accepted as a great leader, in our country at least. It's sad to see that. I'm just worried how long he will be at his position, to be honest.
Ivan
We noticed a big uptick in our traffic in the last few days to Retraction Watch and it turns out it was because someone we wrote about a number of years ago has really hopped on the bandwagon to try and discredit and even try to have Dr. Fauci fired.
It's one of these reminders that the way people think about scientists has, in many cases, far more to do with their own history or their own perspective going in than with any reality or anything about the science. It's pretty disturbing, but it's not a new thing. This has been happening for a while.
You can go back and read sociologists of science from 50-60 years ago and see the same thing, but I just don't think that it's in the same way that it is now, maybe in part because of social media.
Elisabeth
I've been personally very critical about several studies, but this is the first time I've experienced being attacked by trolls and having some nasty websites written about me. It is very disturbing to read.
"I don't think that something that's been peer-reviewed is perfect and something that hasn't been peer reviewed, you should never bother reading it."
Ivan
It is. Yet you have been a fearless and vocal critic of some very high-profile papers, like the infamous French study about hydroxychloroquine.
Elisabeth
Right, the paper that came out was immediately tweeted by the President of the United States. At first I thought it was great that our President tweeted about science! I thought that was a major breakthrough. I took a look at this paper.
It had just come out that day, I believe. The first thing I noticed is that it was accepted within 24 hours of being submitted to the journal. It was actually published in a journal where one of the authors is the editor-in-chief, which is a huge conflict of interest, but it happens.
But in this particular case, there were also a lot of flaws with the study and that, I think, should have been caught during peer review. The paper was first published on a preprint server and then within 24 hours or so it was published in that paper, supposedly after peer review.
There were very few changes between the preprint version and the peer review paper. There were just a couple of extra lines, extra sentences added here and there, but it wasn't really, I think, critically looked at. Because there were a lot of things that I thought were flaws.
Just to go over a couple of them. This paper showed supposedly that people who were treated with hydroxychloroquine and azithromycin were doing much better by clearing their virus much faster than people who were not treated with these drugs.
But if you look carefully at the paper there were a couple of people who were left out of the study. So they were treated with hydroxychloroquine, but they were not shown in the end results of the paper. All six people who were treated with the drug combination were clearing the virus within six days, but there were a couple of others who were left out of the study. They also started the drug combination, but they stopped taking the drugs for several reasons and three of them were admitted to the intensive care, one died, one had some side effects and one apparently walked out of the hospital.
They were left out of the study but they were actually not doing very well with the drug combination. It's not very good science if you leave out people who don't do very well with your drug combination in your study. That was one of my biggest critiques of the paper.
Ivan
What struck us about that case was, in addition to what you, of course, mentioned, the fact that Trump tweeted it and was talking about hydroxychloroquine, was that it seemed to be a perfect example of, "well, it was in a peer review journal." Yeah, it was a preprint first, but, well, it's a peer review journal. And yet, as you point out, when you look at the history of the paper, it was accepted in 24 hours.
If you talk to most scientists, the actual act of a peer review, once you sit down to do it and can concentrate, a good one takes, again, these are averages, but four hours, a half a day is not unreasonable. So you had to find three people who could suddenly review this paper. As you pointed out, it was in a journal where one of the authors was editor.
Then some strange things also happened, right? The society that actually publishes the journal, they came out with a statement saying this wasn't up to our standards, which is odd. Then Elsevier came in, they're the ones who are actually contracted to publish the journal for the society. They said, basically, "Oh, we're going to look into this now too."
It just makes you wonder what happened before the paper was actually published. All the people who were supposed to have been involved in doing the peer review or checking on it are clearly very distraught about what actually happened. It's that scene from Casablanca, "I'm shocked, shocked there's gambling going on here." And then, "Your winnings, sir."
Elisabeth
Yes.
Ivan
And I don't actually blame the public, I don't blame reporters for getting a bit confused about what it all means and what they should trust. I don't think trust is a binary any more than anything else is a binary. I don't think that something that's been peer-reviewed is perfect and something that hasn't been peer reviewed, you should never bother reading it. I think everything is much more gray.
Yet we've turned things into a binary. Even if you go back before coronavirus, coffee is good for you, coffee is bad for you, red wine, chocolate, all the rest of it. A lot of that is because of this sort of binary construct of the world for journalists, frankly, for scientists that need to get their next grants. And certainly for the general public, they want answers.
On the one hand, if I had to choose what group of experts, or what field of human endeavor would I trust with finding the answer to a pandemic like this, or to any crisis, it would absolutely be scientists. Hands down. This is coming from someone who writes about scientific fraud.
But on the other hand, that means that if scientists aren't clear about what they don't know and about the nuances and about what the scientific method actually allows us to do and learn, that just sets them up for failure. It sets people like Dr. Fauci up for failure.
Elisabeth
Right.
Ivan
It sets up any public health official who has a discussion about models. There's a famous saying: "All models are wrong, but some are useful."
Just because the projections change, it's not proof of wrongness, it's not proof that the model is fatally flawed. In fact, I'd be really concerned if the projections didn't change based on new information. I would love it if this whole episode did lead to a better understanding of the scientific process and how scientific publishing fits into that — and doesn't fit into it.
Elisabeth
Yes, I'm with you. I'm very worried that the general audience's perspective is based on maybe watching too many movies where the scientist comes up with a conclusion one hour into the movie when everything is about to fail. Like that scene in Contagion where somebody injects, I think, eight monkeys, and one of the monkeys survives and boom we have the vaccine. That's not really how science works. Everything takes many, many years and many, many applications where usually your first ideas and your first hypothesis turn out to be completely wrong.
Then you go back to the drawing board, you develop another hypothesis and this is a very reiterative process that usually takes years. Most of the people who watch the movie might have a very wrong idea and wrong expectations about how science works. We're living in the movie Contagion and by September, we'll all be vaccinated and we can go on and live our lives. But that's not what is going to happen. It's going to take much, much longer and we're going to have to change the models every time and change our expectations. Just because we don't know all the numbers and all the facts yet.
Ivan
Generally it takes a fairly long time to change medical practice. A lot of times people see that as a bad thing. What I think that ignores, or at least doesn't take into as much account as I would, is that you don't want doctors and other health care professionals to turn on a dime and suddenly switch. Unless, of course, it turns out there was no evidence for what you were looking at.
It's a complicated situation.
Everybody wants scientists to be engineers, right?
Elisabeth
Right.
Ivan
I'm not saying engineering isn't scientific, nor am I saying that science is just completely whimsical, but there's a different process. It's a different way of looking at things and you can't just throw all the data into a big supercomputer, which is what I think a lot of people seem to want us to do, and then the obvious answer will come out on the other side.
Elisabeth
No. It's true and a lot of engineers suddenly feel their inherent need to solve this as a problem. They're not scientists and it's not building a bridge over a big river. But we're dealing with something that is very hard to solve because we don't understand the problem yet. I think scientists are usually first analyzing the problem and trying to understand what the problem actually is before you can even think about a solution.
Ivan
I think we're still at the understanding the problem phase.
Elisabeth
Exactly. And going back to the French group paper, that promised such a result and that was interpreted as such by a lot of people including presidents, but it's a very rare thing to find a medication that will have a 100% curation rate. That's something that I wish the people would understand better. We all want that to happen, but it's very unlikely and very unprecedented in the best of times.
Ivan
I would second that and also say that the world needs to better value the work that people like Elisabeth and others are doing. Because we're not going to get to a better answer if we're not rigorous about scrutinizing the literature and scrutinizing the methodology and scrutinizing the results.
"I quit my job to be able to do this work."
It's a relatively new phenomenon that you're able to do this at any scale at all, and even now it's at a very small scale. Elisabeth mentioned PubPeer and I'm a big fan — also full disclosure, I'm on their board of directors as a volunteer — it's a very powerful engine for readers and journal editors and other scientists to discuss issues.
And Elisabeth has used it really, really well. I think we need to start giving credit to people like that. And, also creating incentives for that kind of work in a way that science hasn't yet.
Elisabeth
Yeah. I quit my job to be able to do this work. It's really hard to combine it with a job either in academia or industry because we're looking for or criticizing papers and it's hard when you are still employed to do that.
I try to make it about the papers and do it in a polite way, but still it's a very hard job to do if you have a daytime job and a position and a career to worry about. Because if you're critical of other academics, that could actually mean the end of your career and that's sad. They should be more open to polite criticism.
Ivan
And for the general public, if you're reading a newspaper story or something online about a single study and it doesn't mention any other studies that have said the same thing or similar, or frankly, if it doesn't say anything about any studies that contradicted it, that's probably also telling you something.
Say you're looking at a huge painting of a shoreline, a beach, and a forest. Any single study is just a one-centimeter-by-one-centimeter square of any part of that canvas. If you just look at that, you would either think it was a painting of the sea, of a beach, or of the forest. It's actually all three of those things.
We just need to be patient, and that's very challenging to us as human beings, but we need to take the time to look at the whole picture.
DISCLAIMER: Neither Elisabeth Bik nor Ivan Oransky was compensated for participation in The Pandemic Issue. While the magazine's editors suggested broad topics for discussion, consistent with Bik's and Oransky's work, neither they nor the magazine's underwriters had any influence on their conversation.
[Editor's Note: This article was originally published on June 8th, 2020 as part of a standalone magazine called GOOD10: The Pandemic Issue. Produced as a partnership among LeapsMag, The Aspen Institute, and GOOD, the magazine is available for free online.]
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Clever Firm Predicts Patients Most at Risk, Then Tries to Intervene Before They Get Sicker
The diabetic patient hit the danger zone.
Ideally, blood sugar, measured by an A1C test, rests at 5.9 or less. A 7 is elevated, according to the Diabetes Council. Over 10, and you're into the extreme danger zone, at risk of every diabetic crisis from kidney failure to blindness.
In three months of working with a case manager, Jen's blood sugar had dropped to 7.2, a much safer range.
This patient's A1C was 10. Let's call her Jen for the sake of this story. (Although the facts of her case are real, the patient's actual name wasn't released due to privacy laws.).
Jen happens to live in Pennsylvania's Lehigh Valley, home of the nonprofit Lehigh Valley Health Network, which has eight hospital campuses and various clinics and other services. This network has invested more than $1 billion in IT infrastructure and founded Populytics, a spin-off firm that tracks and analyzes patient data, and makes care suggestions based on that data.
When Jen left the doctor's office, the Populytics data machine started churning, analyzing her data compared to a wealth of information about future likely hospital visits if she did not comply with recommendations, as well as the potential positive impacts of outreach and early intervention.
About a month after Jen received the dangerous blood test results, a community outreach specialist with psychological training called her. She was on a list generated by Populytics of follow-up patients to contact.
"It's a very gentle conversation," says Cathryn Kelly, who manages a care coordination team at Populytics. "The case manager provides them understanding and support and coaching." The goal, in this case, was small behavioral changes that would actually stick, like dietary ones.
In three months of working with a case manager, Jen's blood sugar had dropped to 7.2, a much safer range. The odds of her cycling back to the hospital ER or veering into kidney failure, or worse, had dropped significantly.
While the health network is extremely localized to one area of one state, using data to inform precise medical decision-making appears to be the wave of the future, says Ann Mongovern, the associate director of Health Care Ethics at the Markkula Center for Applied Ethics at Santa Clara University in California.
"Many hospitals and hospital systems don't yet try to do this at all, which is striking given where we're at in terms of our general technical ability in this society," Mongovern says.
How It Happened
While many hospitals make money by filling beds, the Lehigh Valley Health Network, as a nonprofit, accepts many patients on Medicaid and other government insurances that don't cover some of the costs of a hospitalization. The area's population is both poorer and older than national averages, according to the U.S. Census data, meaning more people with higher medical needs that may not have the support to care for themselves. They end up in the ER, or worse, again and again.
In the early 2000s, LVHN CEO Dr. Brian Nester started wondering if his health network could develop a way to predict who is most likely to land themselves a pricey ICU stay -- and offer support before those people end up needing serious care.
Embracing data use in such specific ways also brings up issues of data security and patient safety.
"There was an early understanding, even if you go back to the (federal) balanced budget act of 1997, that we were just kicking the can down the road to having a functional financial model to deliver healthcare to everyone with a reasonable price," Nester says. "We've got a lot of people living longer without more of an investment in the healthcare trust."
Popultyics, founded in 2013, was the result of years of planning and agonizing over those population numbers and cost concerns.
"We looked at our own health plan," Nester says. Out of all the employees and dependants on the LVHN's own insurance network, "roughly 1.5 percent of our 25,000 people — under 400 people — drove $30 million of our $130 million on insurance costs -- about 25 percent."
"You don't have to boil the ocean to take cost out of the system," he says. "You just have to focus on that 1.5%."
Take Jen, the diabetic patient. High blood sugar can lead to kidney failure, which can mean weekly expensive dialysis for 20 years. Investing in the data and staff to reach patients, he says, is "pennies compared to $100 bills."
For most doctors, "there's no awareness for providers to know who they should be seeing vs. who they are seeing. There's no incentive, because the incentive is to see as many patients as you can," he says.
To change that, first the LVHN invested in the popular medical management system, Epic. Then, they negotiated with the top 18 insurance companies that cover patients in the region to allow access to their patient care data, which means they have reams of patient history to feed the analytics machine in order to make predictions about outcomes. Nester admits not every hospital could do that -- with 52 percent of the market share, LVHN had a very strong negotiating position.
Third party services take that data and churn out analytics that feeds models and care management plans. All identifying information is stripped from the data.
"We can do predictive modeling in patients," says Populytics President and CEO Gregory Kile. "We can identify care gaps. Those care gaps are noted as alerts when the patient presents at the office."
Kile uses himself as a hypothetical patient.
"I pull up Gregory Kile, and boom, I see a flag or an alert. I see he hasn't been in for his last blood test. There is a care gap there we need to complete."
"There's just so much more you can do with that information," he says, envisioning a future where follow-up for, say, knee replacement surgery and outcomes could be tracked, and either validated or changed.
Ethical Issues at the Forefront
Of course, embracing data use in such specific ways also brings up issues of security and patient safety. For example, says medical ethicist Mongovern, there are many touchpoints where breaches could occur. The public has a growing awareness of how data used to personalize their experiences, such as social media analytics, can also be monetized and sold in ways that benefit a company, but not the user. That's not to say data supporting medical decisions is a bad thing, she says, just one with potential for public distrust if not handled thoughtfully.
"You're going to need to do this to stay competitive," she says. "But there's obviously big challenges, not the least of which is patient trust."
So far, a majority of the patients targeted – 62 percent -- appear to embrace the effort.
Among the ways the LVHN uses the data is monthly reports they call registries, which include patients who have just come in contact with the health network, either through the hospital or a doctor that works with them. The community outreach team members at Populytics take the names from the list, pull their records, and start calling. So far, a majority of the patients targeted – 62 percent -- appear to embrace the effort.
Says Nester: "Most of these are vulnerable people who are thrilled to have someone care about them. So they engage, and when a person engages in their care, they take their insulin shots. It's not rocket science. The rocket science is in identifying who the people are — the delivery of care is easy."
In The Fake News Era, Are We Too Gullible? No, Says Cognitive Scientist
One of the oddest political hoaxes of recent times was Pizzagate, in which conspiracy theorists claimed that Hillary Clinton and her 2016 campaign chief ran a child sex ring from the basement of a Washington, DC, pizzeria.
To fight disinformation more effectively, he suggests, humans need to stop believing in one thing above all: our own gullibility.
Millions of believers spread the rumor on social media, abetted by Russian bots; one outraged netizen stormed the restaurant with an assault rifle and shot open what he took to be the dungeon door. (It actually led to a computer closet.) Pundits cited the imbroglio as evidence that Americans had lost the ability to tell fake news from the real thing, putting our democracy in peril.
Such fears, however, are nothing new. "For most of history, the concept of widespread credulity has been fundamental to our understanding of society," observes Hugo Mercier in Not Born Yesterday: The Science of Who We Trust and What We Believe (Princeton University Press, 2020). In the fourth century BCE, he points out, the historian Thucydides blamed Athens' defeat by Sparta on a demagogue who hoodwinked the public into supporting idiotic military strategies; Plato extended that argument to condemn democracy itself. Today, atheists and fundamentalists decry one another's gullibility, as do climate-change accepters and deniers. Leftists bemoan the masses' blind acceptance of the "dominant ideology," while conservatives accuse those who do revolt of being duped by cunning agitators.
What's changed, all sides agree, is the speed at which bamboozlement can propagate. In the digital age, it seems, a sucker is born every nanosecond.
The Case Against Credulity
Yet Mercier, a cognitive scientist at the Jean Nicod Institute in Paris, thinks we've got the problem backward. To fight disinformation more effectively, he suggests, humans need to stop believing in one thing above all: our own gullibility. "We don't credulously accept whatever we're told—even when those views are supported by the majority of the population, or by prestigious, charismatic individuals," he writes. "On the contrary, we are skilled at figuring out who to trust and what to believe, and, if anything, we're too hard rather than too easy to influence."
He bases those contentions on a growing body of research in neuropsychiatry, evolutionary psychology, and other fields. Humans, Mercier argues, are hardwired to balance openness with vigilance when assessing communicated information. To gauge a statement's accuracy, we instinctively test it from many angles, including: Does it jibe with what I already believe? Does the speaker share my interests? Has she demonstrated competence in this area? What's her reputation for trustworthiness? And, with more complex assertions: Does the argument make sense?
This process, Mercier says, enables us to learn much more from one another than do other animals, and to communicate in a far more complex way—key to our unparalleled adaptability. But it doesn't always save us from trusting liars or embracing demonstrably false beliefs. To better understand why, leapsmag spoke with the author.
How did you come to write Not Born Yesterday?
In 2010, I collaborated with the cognitive scientist Dan Sperber and some other colleagues on a paper called "Epistemic Vigilance," which laid out the argument that evolutionarily, it would make no sense for humans to be gullible. If you can be easily manipulated and influenced, you're going to be in major trouble. But as I talked to people, I kept encountering resistance. They'd tell me, "No, no, people are influenced by advertising, by political campaigns, by religious leaders." I started doing more research to see if I was wrong, and eventually I had enough to write a book.
With all the talk about "fake news" these days, the topic has gotten a lot more timely.
Yes. But on the whole, I'm skeptical that fake news matters very much. And all the energy we spend fighting it is energy not spent on other pursuits that may be better ways of improving our informational environment. The real challenge, I think, is not how to shut up people who say stupid things on the internet, but how to make it easier for people who say correct things to convince people.
"History shows that the audience's state of mind and material conditions matter more than the leader's powers of persuasion."
You start the book with an anecdote about your encounter with a con artist several years ago, who scammed you out of 20 euros. Why did you choose that anecdote?
Although I'm arguing that people aren't generally gullible, I'm not saying we're completely impervious to attempts at tricking us. It's just that we're much better than we think at resisting manipulation. And while there's a risk of trusting someone who doesn't deserve to be trusted, there's also a risk of not trusting someone who could have been trusted. You miss out on someone who could help you, or from whom you might have learned something—including figuring out who to trust.
You argue that in humans, vigilance and open-mindedness evolved hand-in-hand, leading to a set of cognitive mechanisms you call "open vigilance."
There's a common view that people start from a state of being gullible and easy to influence, and get better at rejecting information as they become smarter and more sophisticated. But that's not what really happens. It's much harder to get apes than humans to do anything they don't want to do, for example. And research suggests that over evolutionary time, the better our species became at telling what we should and shouldn't listen to, the more open to influence we became. Even small children have ways to evaluate what people tell them.
The most basic is what I call "plausibility checking": if you tell them you're 200 years old, they're going to find that highly suspicious. Kids pay attention to competence; if someone is an expert in the relevant field, they'll trust her more. They're likelier to trust someone who's nice to them. My colleagues and I have found that by age 2 ½, children can distinguish between very strong and very weak arguments. Obviously, these skills keep developing throughout your life.
But you've found that even the most forceful leaders—and their propaganda machines—have a hard time changing people's minds.
Throughout history, there's been this fear of demagogues leading whole countries into terrible decisions. In reality, these leaders are mostly good at feeling the crowd and figuring out what people want to hear. They're not really influencing [the masses]; they're surfing on pre-existing public opinion. We know from a recent study, for instance, that if you match cities in which Hitler gave campaign speeches in the late '20s through early '30s with similar cities in which he didn't give campaign speeches, there was no difference in vote share for the Nazis. Nazi propaganda managed to make Germans who were already anti-Semitic more likely to express their anti-Semitism or act on it. But Germans who were not already anti-Semitic were completely inured to the propaganda.
So why, in totalitarian regimes, do people seem so devoted to the ruler?
It's not a very complex psychology. In these regimes, the slightest show of discontent can be punished by death, or by you and your whole family being sent to a labor camp. That doesn't mean propaganda has no effect, but you can explain people's obedience without it.
What about cult leaders and religious extremists? Their followers seem willing to believe anything.
Prophets and preachers can inspire the kind of fervor that leads people to suicidal acts or doomed crusades. But history shows that the audience's state of mind and material conditions matter more than the leader's powers of persuasion. Only when people are ready for extreme actions can a charismatic figure provide the spark that lights the fire.
Once a religion becomes ubiquitous, the limits of its persuasive powers become clear. Every anthropologist knows that in societies that are nominally dominated by orthodox belief systems—whether Christian or Muslim or anything else—most people share a view of God, or the spirit, that's closer to what you find in societies that lack such religions. In the Middle Ages, for instance, you have records of priests complaining of how unruly the people are—how they spend the whole Mass chatting or gossiping, or go on pilgrimages mostly because of all the prostitutes and wine-drinking. They continue pagan practices. They resist attempts to make them pay tithes. It's very far from our image of how much people really bought the dominant religion.
"The mainstream media is extremely reliable. The scientific consensus is extremely reliable."
And what about all those wild rumors and conspiracy theories on social media? Don't those demonstrate widespread gullibility?
I think not, for two reasons. One is that most of these false beliefs tend to be held in a way that's not very deep. People may say Pizzagate is true, yet that belief doesn't really interact with the rest of their cognition or their behavior. If you really believe that children are being abused, then trying to free them is the moral and rational thing to do. But the only person who did that was the guy who took his assault weapon to the pizzeria. Most people just left one-star reviews of the restaurant.
The other reason is that most of these beliefs actually play some useful role for people. Before any ethnic massacre, for example, rumors circulate about atrocities having been committed by the targeted minority. But those beliefs aren't what's really driving the phenomenon. In the horrendous pogrom of Kishinev, Moldova, 100 years ago, you had these stories of blood libel—a child disappeared, typical stuff. And then what did the Christian inhabitants do? They raped the [Jewish] women, they pillaged the wine stores, they stole everything they could. They clearly wanted to get that stuff, and they made up something to justify it.
Where do skeptics like climate-change deniers and anti-vaxxers fit into the picture?
Most people in most countries accept that vaccination is good and that climate change is real and man-made. These ideas are deeply counter-intuitive, so the fact that scientists were able to get them across is quite fascinating. But the environment in which we live is vastly different from the one in which we evolved. There's a lot more information, which makes it harder to figure out who we can trust. The main effect is that we don't trust enough; we don't accept enough information. We also rely on shortcuts and heuristics—coarse cues of trustworthiness. There are people who abuse these cues. They may have a PhD or an MD, and they use those credentials to help them spread messages that are not true and not good. Mostly, they're affirming what people want to believe, but they may also be changing minds at the margins.
How can we improve people's ability to resist that kind of exploitation?
I wish I could tell you! That's literally my next project. Generally speaking, though, my advice is very vanilla. The mainstream media is extremely reliable. The scientific consensus is extremely reliable. If you trust those sources, you'll go wrong in a very few cases, but on the whole, they'll probably give you good results. Yet a lot of the problems that we attribute to people being stupid and irrational are not entirely their fault. If governments were less corrupt, if the pharmaceutical companies were irreproachable, these problems might not go away—but they would certainly be minimized.