Who Qualifies as an “Expert” And How Can We Decide Who Is Trustworthy?
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Expertise is a slippery concept. Who has it, who claims it, and who attributes or yields it to whom is a culturally specific, sociological process. During the COVID-19 pandemic, we have witnessed a remarkable emergence of legitimate and not-so-legitimate scientists publicly claiming or being attributed to have academic expertise in precisely my field: infectious disease epidemiology. From any vantage point, it is clear that charlatans abound out there, garnering TV coverage and hundreds of thousands of Twitter followers based on loud opinions despite flimsy credentials. What is more interesting as an insider is the gradient of expertise beyond these obvious fakers.
A person's expertise is not a fixed attribute; it is a hierarchical trait defined relative to others. Despite my protestations, I am the go-to expert on every aspect of the pandemic to my family. To a reporter, I might do my best to answer a question about the immune response to SARS-CoV-2, noting that I'm not an immunologist. Among other academic scientists, my expertise is more well-defined as a subfield of epidemiology, and within that as a particular area within infectious disease epidemiology. There's a fractal quality to it; as you zoom in on a particular subject, a differentiation of expertise emerges among scientists who, from farther out, appear to be interchangeable.
We all have our scientific domain and are less knowledgeable outside it, of course, and we are often asked to comment on a broad range of topics. But many scientists without a track record in the field have become favorites among university administrators, senior faculty in unrelated fields, policymakers, and science journalists, using institutional prestige or social connections to promote themselves. This phenomenon leads to a distorted representation of science—and of academic scientists—in the public realm.
Trustworthy experts will direct you to others in their field who know more about particular topics, and will tend to be honest about what is and what isn't "in their lane."
Predictably, white male voices have been disproportionately amplified, and men are certainly over-represented in the category of those who use their connections to inappropriately claim expertise. Generally speaking, we are missing women, racial minorities, and global perspectives. This is not only important because it misrepresents who scientists are and reinforces outdated stereotypes that place white men in the Global North at the top of a credibility hierarchy. It also matters because it can promote bad science, and it passes over scientists who can lend nuance to the scientific discourse and give global perspectives on this quintessentially global crisis.
Also at work, in my opinion, are two biases within academia: the conflation of institutional prestige with individual expertise, and the bizarre hierarchy among scientists that attributes greater credibility to those in quantitative fields like physics. Regardless of mathematical expertise or institutional affiliation, lack of experience working with epidemiological data can lead to over-confidence in the deceptively simple mathematical models that we use to understand epidemics, as well as the inappropriate use of uncertain data to inform them. Prominent and vocal scientists from different quantitative fields have misapplied the methods of infectious disease epidemiology during the COVID-19 pandemic so far, creating enormous confusion among policymakers and the public. Early forecasts that predicted the epidemic would be over by now, for example, led to a sense that epidemiological models were all unreliable.
Meanwhile, legitimate scientific uncertainties and differences of opinion, as well as fundamentally different epidemic dynamics arising in diverse global contexts and in different demographic groups, appear in the press as an indistinguishable part of this general chaos. This leads many people to question whether the field has anything worthwhile to contribute, and muddies the facts about COVID-19 policies for reducing transmission that most experts agree on, like wearing masks and avoiding large indoor gatherings.
So how do we distinguish an expert from a charlatan? I believe a willingness to say "I don't know" and to openly describe uncertainties, nuances, and limitations of science are all good signs. Thoughtful engagement with questions and new ideas is also an indication of expertise, as opposed to arrogant bluster or a bullish insistence on a particular policy strategy regardless of context (which is almost always an attempt to hide a lack of depth of understanding). Trustworthy experts will direct you to others in their field who know more about particular topics, and will tend to be honest about what is and what isn't "in their lane." For example, some expertise is quite specific to a given subfield: epidemiologists who study non-infectious conditions or nutrition, for example, use different methods from those of infectious disease experts, because they generally don't need to account for the exponential growth that is inherent to a contagion process.
Academic scientists have a specific, technical contribution to make in containing the COVID-19 pandemic and in communicating research findings as they emerge. But the liminal space between scientists and the public is subject to the same undercurrents of sexism, racism, and opportunism that society and the academy have always suffered from. Although none of the proxies for expertise described above are fool-proof, they are at least indicative of integrity and humility—two traits the world is in dire need of at this moment in history.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
In different countries' national dietary guidelines, red meats (beef, pork, and lamb) are often confined to a very small corner. Swedish officials, for example, advise the population to "eat less red and processed meat". Experts in Greece recommend consuming no more than four servings of red meat — not per week, but per month.
"Humans 100% rely on the microbes to digest this food."
Yet somehow, the matter is far from settled. Quibbles over the scientific evidence emerge on a regular basis — as in a recent BMJ article titled, "No need to cut red meat, say new guidelines." News headlines lately have declared that limiting red meat may be "bad advice," while carnivore diet enthusiasts boast about the weight loss and good health they've achieved on an all-meat diet. The wildly successful plant-based burgers? To them, a gimmick. The burger wars are on.
Nutrition science would seem the best place to look for answers on the health effects of specific foods. And on one hand, the science is rather clear: in large populations, people who eat more red meat tend to have more health problems, including cardiovascular disease, colorectal cancer, and other conditions. But this sort of correlational evidence fails to settle the matter once and for all; many who look closely at these studies cite methodological shortcomings and a low certainty of evidence.
Some scientists, meanwhile, are trying to cut through the noise by increasing their focus on the mechanisms: exactly how red meat is digested and the step-by-step of how this affects human health. And curiously, as these lines of evidence emerge, several of them center around gut microbes as active participants in red meat's ultimate effects on human health.
Dr. Stanley Hazen, researcher and medical director of preventive cardiology at Cleveland Clinic, was one of the first to zero in on gut microorganisms as possible contributors to the health effects of red meat. In looking for chemical compounds in the blood that could predict the future development of cardiovascular disease, his lab identified a molecule called trimethylamine-N-oxide (TMAO). Little by little, he and his colleagues began to gather both human and animal evidence that TMAO played a role in causing heart disease.
Naturally, they tried to figure out where the TMAO came from. Hazen says, "We found that animal products, and especially red meat, were a dietary source that, [along with] gut microbes, would generate this product that leads to heart disease development." They observed that the gut microbes were essential for making TMAO out of dietary compounds (like red meat) that contained its precursor, trimethylamine (TMA).
So in linking red meat to cardiovascular disease through TMAO, the surprising conclusion, says Hazen, was that, "Without a doubt, [the microbes] are the most important aspect of the whole pathway."
"I think it's just a matter of time [before] we will have therapeutic interventions that actually target our gut microbes, just like the way we take drugs that lower cholesterol levels."
Other researchers have taken an interest in different red-meat-associated health problems, like colorectal cancer and the inflammation that accompanies it. This was the mechanistic link tackled by the lab of professor Karsten Zengler of the UC San Diego Departments of Pediatrics and Bioengineering—and it also led straight back to the gut microbes.
Zengler and colleagues recently published a paper in Nature Microbiology that focused on the effects of a red meat carbohydrate (or sugar) called Neu5Gc.
He explains, "If you eat animal proteins in your diet… the bound sugars in your diet are cleaved off in your gut and they get recycled. Your own cells will not recognize between the foreign sugars and your own sugars, because they look almost identical." The unsuspecting human cells then take up these foreign sugars — spurring antibody production and creating inflammation.
Zengler showed, however, that gut bacteria use enzymes to cleave off the sugar during digestion, stopping the inflammation and rendering the sugar harmless. "There's no enzyme in the human body that can cleave this [sugar] off. Humans 100% rely on the microbes to digest this food," he says.
Both researchers are quick to caution that the health effects of diet are complex. Other work indicates, for example, that while intake of red meat can affect TMAO levels, so can intake of fish and seafood. But these new lines of evidence could help explain why some people, ironically, seem to be in perfect health despite eating a lot of red meat: their ideal frequency of meat consumption may depend on their existing community of gut microbes.
"It helps explain what accounts for inter-person variability," Hazen says.
These emerging mechanisms reinforce overall why it's prudent to limit red meat, just as the nutritional guidelines advised in the first place. But both Hazen and Zengler predict that interventions to buffer the effects of too many ribeyes may be just around the corner.
Zengler says, "Our idea is that you basically can help your own digestive system detoxify these inflammatory compounds in meat, if you continue eating red meat or you want to eat a high amount of red meat." A possibly strategy, he says, is to use specific pre- or probiotics to cultivate an inflammation-reducing gut microbial community.
Hazen foresees the emergence of drugs that act not on the human, but on the human's gut microorganisms. "I think it's just a matter of time [before] we will have therapeutic interventions that actually target our gut microbes, just like the way we take drugs that lower cholesterol levels."
He adds, "It's a matter of 'stay tuned', I think."
New Device Can Detect Peanut Allergens on a Plate in 30 Seconds
People with life-threatening allergies live in constant fear of coming into contact with deadly allergens. Researchers estimate that about 32 million Americans have food allergies, with the most severe being milk, egg, peanut, tree nuts, wheat, soy, fish, and shellfish.
"It is important to understand that just several years ago, this would not have been possible."
Every three minutes, a food allergy reaction sends someone to the emergency room, and 200,000 people in the U.S. require emergency medical care each year for allergic reactions, according to Food Allergy Research and Education.
But what if there was a way you could easily detect if something you were about to eat contains any harmful allergens? Thanks to Israeli scientists, this will soon be the case — at least for peanuts. The team has been working to develop a handheld device called Allerguard, which analyzes the vapors in your meal and can detect allergens in 30 seconds.
Leapsmag spoke with the founder and CTO of Allerguard, Guy Ayal, about the groundbreaking technology, how it works, and when it will be available to purchase.
What prompted you to create this device? Do you have a personal connection with severe food allergies?
Guy Ayal: My eldest daughter's best friend suffers from a severe food allergy, and I experienced first-hand the effect it has on the person and their immediate surroundings. Most notable for me was the effect on the quality of life – the experience of living in constant fear. Everything we do at Allerguard is basically to alleviate some of that fear.
How exactly does the device work?
The device is built on two main pillars. The first is the nano-chemical stage, in which we developed specially attuned nanoparticles that selectively adhere only to the specific molecules that we are looking for. Those molecules, once bound to the nanoparticles, induce a change in their electrical behavior, which is measured and analyzed by the second main pillar -- highly advanced machine learning algorithms, which can surmise which molecules were collected, and thus whether or not peanuts (or in the future, other allergens) were detected.
It is important to understand that just several years ago, this would not have been possible, because both the nano-chemistry, and especially the entire world of machine learning, big data, and what is commonly known as AI only started to exist in the '90s, and reached applicability for handheld devices only in the past few years.
Where are you at in the development process and when will the device be available to consumers?
We have concluded the proof of concept and proof of capability phase, when we demonstrated successful detection of the minimal known clinical amount that may cause the slightest effect in the most severely allergic person – less than 1 mg of peanut (actually it is 0.7 mg). Over the next 18 months will be productization, qualification, and validation of our device, which should be ready to market in the latter half of 2021. The sensor will be available in the U.S., and after a year in Europe and Canada.
The Allerguard was made possible through recent advances in machine learning, big data, and AI.
(Courtesy)
How much will it cost?
Our target price is about $200 for the device, with a disposable SenseCard that will run for at least a full day and cost about $1. That card is for a specific allergen and will work for multiple scans in a day, not just one time.
[At a later stage, the company will have sensors for other allergens like tree nuts, eggs, and milk, and they'll develop a multi-SenseCard that works for a few allergens at once.]
Are there any other devices on the market that do something similar to Allerguard?
No other devices are even close to supplying the level of service that we promise. All known methods for allergen detection rely on sampling of the food, which is a viable solution for homogenous foodstuffs, such as a factory testing their raw ingredients, but not for something as heterogenous as an actual dish – especially not for solid allergens such as peanuts, treenuts, or sesame.
If there is a single peanut in your plate, and you sample from anywhere on that plate which is not where that peanut is located, you will find that your sample is perfectly clean – because it is. But the dish is not. That dish is a death trap for an allergic person. Allerguard is the only suggested solution that could indeed detect that peanut, no matter where in that plate it is hiding.
Anything else readers should know?
Our first-generation product will be for peanuts only. You have to understand, we are still a start-up company, and if we don't concentrate our limited resources to one specific goal, we will not be able to achieve anything at all. Once we are ready to market our first device, the peanut detector, we will be able to start the R&D for the 2nd product, which will be for another allergen – most likely tree nuts and/or sesame, but that will probably be in debate until we actually start it.