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.
Food Poisoning Sickens Millions a Year. Now, a Surprising Weapon Is Helping Protect Against Contamination.

Phages, which are harmless viruses that destroy specific bacteria, are becoming useful tools to protect our food supply.

Every year, one in seven people in America comes down with a foodborne illness, typically caused by a bacterial pathogen, including E.Coli, listeria, salmonella, or campylobacter. That adds up to 48 million people, of which 120,000 are hospitalized and 3000 die, according to the Centers for Disease Control. And the variety of foods that can be contaminated with bacterial pathogens is growing too. In the 20th century, E.Coli and listeria lurked primarily within meat. Now they find their way into lettuce, spinach, and other leafy greens, causing periodic consumer scares and product recalls. Onions are the most recent suspected culprit of a nationwide salmonella outbreak.

Some of these incidents are almost inevitable because of how Mother Nature works, explains Divya Jaroni, associate professor of animal and food sciences at Oklahoma State University. These common foodborne pathogens come from the cattle's intestines when the animals shed them in their manure—and then they get washed into rivers and lakes, especially in heavy rains. When this water is later used to irrigate produce farms, the bugs end up on salad greens. Plus, many small farms do both—herd cattle and grow produce.

"Unfortunately for us, these pathogens are part of the microflora of the cows' intestinal tract," Jaroni says. "Some farmers may have an acre or two of cattle pastures, and an acre of a produce farm nearby, so it's easy for this water to contaminate the crops."

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Lina Zeldovich

Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.

Your Future Smartphone May Detect Problems in Your Water

Biosensors on a touchscreen are showing promise for detecting arsenic and lead in water.

Photo by Johnny McClung on Unsplash

In 2014, the city of Flint, Michigan switched the residents' water supply to the Flint river, citing cheaper costs. However, due to improper filtering, lead contaminated this water, and according to the Associated Press, many of the city's residents soon reported health issues like hair loss and rashes. In 2015, a report found that children there had high levels of lead in their blood. The National Resource Defense Council recently discovered there could still be as many as twelve million lead pipes carrying water to homes across the U.S.

What if Flint residents and others in afflicted areas could simply flick water onto their phone screens and an app would tell them if they were about to drink contaminated water? This is what researchers at the University of Cambridge are working on to prevent catastrophes like what occurred in Flint, and to prepare for an uncertain future of scarcer resources.

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Hanna Webster
Hanna Webster is a freelance science writer based in San Diego, California. She received a Bachelor’s degree in neuroscience and creative writing in 2018 from Western Washington University, and is now a graduate student in the MA Science Writing program at Johns Hopkins University. She writes stories about neuroscience, biology, and public health. Her essays and articles have appeared in Jeopardy Magazine and Leafly. When Hanna is not writing, she enjoys consuming other art forms, such as photography, poetry, creative nonfiction, and live music