Pseudoscience Is Rampant: How Not to Fall for It
Whom to believe?
The relentless and often unpredictable coronavirus (SARS-CoV-2) has, among its many quirky terrors, dredged up once again the issue that will not die: science versus pseudoscience.
How does one learn to spot the con without getting a Ph.D. and spending years in a laboratory?
The scientists, experts who would be the first to admit they are not infallible, are now in danger of being drowned out by the growing chorus of pseudoscientists, conspiracy theorists, and just plain troublemakers that seem to be as symptomatic of the virus as fever and weakness.
How is the average citizen to filter this cacophony of information and misinformation posing as science alongside real science? While all that noise makes it difficult to separate the real stuff from the fakes, there is at least one positive aspect to it all.
A famous aphorism by one Charles Caleb Colton, a popular 19th-century English cleric and writer, says that "imitation is the sincerest form of flattery."
The frauds and the paranoid conspiracy mongers who would perpetrate false science on a susceptible public are at least recognizing the value of science—they imitate it. They imitate the ways in which science works and make claims as if they were scientists, because even they recognize the power of a scientific approach. They are inadvertently showing us how much we value science. Unfortunately they are just shabby counterfeits.
Separating real science from pseudoscience is not a new problem. Philosophers, politicians, scientists, and others have been worrying about this perhaps since science as we know it, a science based entirely on experiment and not opinion, arrived in the 1600s. The original charter of the British Royal Society, the first organized scientific society, stated that at their formal meetings there would be no discussion of politics, religion, or perpetual motion machines.
The first two of those for the obvious purpose of keeping the peace. But the third is interesting because at that time perpetual motion machines were one of the main offerings of the imitators, the bogus scientists who were sure that you could find ways around the universal laws of energy and make a buck on it. The motto adopted by the society was, and remains, Nullius in verba, Latin for "take nobody's word for it." Kind of an early version of Missouri's venerable state motto: "Show me."
You might think that telling phony science from the real thing wouldn't be so difficult, but events, historical and current, tell a very different story—often with tragic outcomes. Just one terrible example is the estimated 350,000 additional HIV deaths in South Africa directly caused by the now-infamous conspiracy theories of their own elected President no less (sound familiar?). It's surprisingly easy to dress up phony science as the real thing by simply adopting, or appearing to adopt, the trappings of science.
Thus, the anti-vaccine movement claims to be based on suspicion of authority, beginning with medical authority in this case, stemming from the fraudulent data published by the now-disgraced Andrew Wakefield, an English gastroenterologist. And it's true that much of science is based on suspicion of authority. Science got its start when the likes of Galileo and Copernicus claimed that the Church, the State, even Aristotle, could no longer be trusted as authoritative sources of knowledge.
But Galileo and those who followed him produced alternative explanations, and those alternatives were based on data that arose independently from many sources and generated a great deal of debate and, most importantly, could be tested by experiments that could prove them wrong. The anti-vaccine movement imitates science, still citing the discredited Wakefield report, but really offers nothing but suspicion—and that is paranoia, not science.
Similarly, there are those who try to cloak their nefarious motives in the trappings of science by claiming that they are taking the scientific posture of doubt. Science after all depends on doubt—every scientist doubts every finding they make. Every scientist knows that they can't possibly foresee all possible instances or situations in which they could be proven wrong, no matter how strong their data. Einstein was doubted for two decades, and cosmologists are still searching for experimental proofs of relativity. Science indeed progresses by doubt. In science revision is a victory.
But the imitators merely use doubt to suggest that science is not dependable and should not be used for informing policy or altering our behavior. They claim to be taking the legitimate scientific stance of doubt. Of course, they don't doubt everything, only what is problematic for their individual enterprises. They don't doubt the value of blood pressure medicine to control their hypertension. But they should, because every medicine has side effects and we don't completely understand how blood pressure is regulated and whether there may not be still better ways of controlling it.
But we use the pills we have because the science is sound even when it is not completely settled. Ask a hypertensive oil executive who would like you to believe that climate science should be ignored because there are too many uncertainties in the data, if he is willing to forgo his blood pressure medicine—because it, too, has its share of uncertainties and unwanted side effects.
The apparent success of pseudoscience is not due to gullibility on the part of the public. The problem is that science is recognized as valuable and that the imitators are unfortunately good at what they do. They take a scientific pose to gain your confidence and then distort the facts to their own purposes. How does one learn to spot the con without getting a Ph.D. and spending years in a laboratory?
"If someone claims to have the ultimate answer or that they know something for certain, the only thing for sure is that they are trying to fool you."
What can be done to make the distinction clearer? Several solutions have been tried—and seem to have failed. Radio and television shows about the latest scientific breakthroughs are a noble attempt to give the public a taste of good science, but they do nothing to help you distinguish between them and the pseudoscience being purveyed on the neighboring channel and its "scientific investigations" of haunted houses.
Similarly, attempts to inculcate what are called "scientific habits of mind" are of little practical help. These habits of mind are not so easy to adopt. They invariably require some amount of statistics and probability and much of that is counterintuitive—one of the great values of science is to help us to counter our normal biases and expectations by showing that the actual measurements may not bear them out.
Additionally, there is math—no matter how much you try to hide it, much of the language of science is math (Galileo said that). And half the audience is gone with each equation (Stephen Hawking said that). It's hard to imagine a successful program of making a non-scientifically trained public interested in adopting the rigors of scientific habits of mind. Indeed, I suspect there are some people, artists for example, who would be rightfully suspicious of changing their thinking to being habitually scientific. Many scientists are frustrated by the public's inability to think like a scientist, but in fact it is neither easy nor always desirable to do so. And it is certainly not practical.
There is a more intuitive and simpler way to tell the difference between the real thing and the cheap knock-off. In fact, it is not so much intuitive as it is counterintuitive, so it takes a little bit of mental work. But the good thing is it works almost all the time by following a simple, if as I say, counterintuitive, rule.
True science, you see, is mostly concerned with the unknown and the uncertain. If someone claims to have the ultimate answer or that they know something for certain, the only thing for sure is that they are trying to fool you. Mystery and uncertainty may not strike you right off as desirable or strong traits, but that is precisely where one finds the creative solutions that science has historically arrived at. Yes, science accumulates factual knowledge, but it is at its best when it generates new and better questions. Uncertainty is not a place of worry, but of opportunity. Progress lives at the border of the unknown.
How much would it take to alter the public perception of science to appreciate unknowns and uncertainties along with facts and conclusions? Less than you might think. In fact, we make decisions based on uncertainty every day—what to wear in case of 60 percent chance of rain—so it should not be so difficult to extend that to science, in spite of what you were taught in school about all the hard facts in those giant textbooks.
You can believe science that says there is clear evidence that takes us this far… and then we have to speculate a bit and it could go one of two or three ways—or maybe even some way we don't see yet. But like your blood pressure medicine, the stuff we know is reliable even if incomplete. It will lower your blood pressure, no matter that better treatments with fewer side effects may await us in the future.
Unsettled science is not unsound science. The honesty and humility of someone who is willing to tell you that they don't have all the answers, but they do have some thoughtful questions to pursue, are easy to distinguish from the charlatans who have ready answers or claim that nothing should be done until we are an impossible 100-percent sure.
Imitation may be the sincerest form of flattery.
The problem, as we all know, is that flattery will get you nowhere.
[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.]
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.