Who Qualifies as an “Expert” And How Can We Decide Who Is Trustworthy?

Who Qualifies as an “Expert” And How Can We Decide Who Is Trustworthy?

Discerning a real expert from a charlatan is crucial during the COVID-19 pandemic and beyond.

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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.]

Caroline Buckee
Dr. Caroline Buckee is an Associate Professor of Epidemiology and Associate Director of the Centre for Communicable Disease Dynamics at Harvard T.H. Chan School of Public Health. She is a co-founder of the COVID-19 Mobility Data Network, set up to support the use of population behavior data to guide policy makers in their response to the pandemic. Her other work is focused on understanding the mechanisms driving the spread of infectious diseases that impact the most vulnerable populations worldwide, particularly malaria. Before coming to Harvard, Dr. Buckee completed a D.Phil. at the University of Oxford, and Omidyar and Wellcome Trust fellowships at the Santa Fe Institute and the Kenya Medical Research Institute, respectively, where she analyzed malaria parasite evolution and epidemiology. Dr. Buckee’s group uses a range of mathematical models, experimental and genomic data, and “Big Data” from mobile phones and satellites to understand how human pathogens spread and may be controlled.
Can Biotechnology Take the Allergies Out of Cats?

From a special food to a vaccine and gene editing, new technologies may offer solutions for cat lovers with allergies.

Photo by Pacto Visual on Unsplash

Amy Bitterman, who teaches at Rutgers Law School in Newark, gets enormous pleasure from her three mixed-breed rescue cats, Spike, Dee, and Lucy. To manage her chronically stuffy nose, three times a week she takes Allegra D, which combines the antihistamine fexofenadine with the decongestant pseudoephedrine. Amy's dog allergy is rougher--so severe that when her sister launched a business, Pet Care By Susan, from their home in Edison, New Jersey, they knew Susan would have to move elsewhere before she could board dogs. Amy has tried to visit their brother, who owns a Labrador Retriever, taking Allegra D beforehand. But she began sneezing, and then developed watery eyes and phlegm in her chest.

"It gets harder and harder to breathe," she says.

Animal lovers have long dreamed of "hypo-allergenic" cats and dogs. Although to date, there is no such thing, biotechnology is beginning to provide solutions for cat-lovers. Cats are a simpler challenge than dogs. Dog allergies involve as many as seven proteins. But up to 95 percent of people who have cat allergies--estimated at 10 to 30 percent of the population in North America and Europe--react to one protein, Fel d1. Interestingly, cats don't seem to need Fel d1. There are cats who don't produce much Fel d1 and have no known health problems.

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Temma Ehrenfeld
Temma Ehrenfeld writes about health and psychology. In a previous life, she was a reporter and editor at Newsweek and Fortune. You can see more of her work at her writing portfolio (https://temmaehrenfeld.contently.com) and contact her through her Psychology Today blog.
Genetic Testing Companies Are Facing a Racial Bias Problem in Disease Risk Tests

The large genetic studies underlying certain disease risk tests have primarily been done in populations of European ancestry, limiting their accuracy.

Earlier this year, California-based Ambry Genetics announced that it was discontinuing a test meant to estimate a person's risk of developing prostate or breast cancer. The test looks for variations in a person's DNA that are known to be associated with these cancers.

Known as a polygenic risk score, this type of test adds up the effects of variants in many genes — often in the dozens or hundreds — and calculates a person's risk of developing a particular health condition compared to other people. In this way, polygenic risk scores are different from traditional genetic tests that look for mutations in single genes, such as BRCA1 and BRCA2, which raise the risk of breast cancer.

Traditional genetic tests look for mutations that are relatively rare in the general population but have a large impact on a person's disease risk, like BRCA1 and BRCA2. By contrast, polygenic risk scores scan for more common genetic variants that, on their own, have a small effect on risk. Added together, however, they can raise a person's risk for developing disease.

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Emily Mullin
Emily Mullin is a science and biotech journalist whose work has appeared in The Washington Post, New York Times, Wall Street Journal, Scientific American, National Geographic and Smithsonian Magazine.