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.
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.