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.
New Podcast: "Making Sense of Science"
Making Sense of Science features interviews with leading medical and scientific experts about the latest developments and the big ethical and societal questions they raise. This monthly podcast is hosted by journalist Kira Peikoff, founding editor of the award-winning science outlet Leaps.org.
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Kira Peikoff

Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.

A Doctor Who Treated His Own Rare Disease Is Tracking COVID-19 Treatments Hiding In Plain Sight

Dr. David Fajgenbaum looking through a microscope at his lab.

Courtesy of Fajgenbaum

In late March, just as the COVID-19 pandemic was ramping up in the United States, David Fajgenbaum, a physician-scientist at the University of Pennsylvania, devised a 10-day challenge for his lab: they would sift through 1,000 recently published scientific papers documenting cases of the deadly virus from around the world, pluck out the names of any drugs used in an attempt to cure patients, and track the treatments and their outcomes in a database.

Before late 2019, no one had ever had to treat this exact disease before, which meant all treatments would be trial and error. Fajgenbaum, a pioneering researcher in the field of drug repurposing—which prioritizes finding novel uses for existing drugs, rather than arduously and expensively developing new ones for each new disease—knew that physicians around the world would be embarking on an experimental journey, the scale of which would be unprecedented. His intention was to briefly document the early days of this potentially illuminating free-for-all, as a sidebar to his primary field of research on a group of lymph node disorders called Castleman disease. But now, 11 months and 29,000 scientific papers later, he and his team of 22 are still going strong.

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Julia Sklar
Julia Sklar is a Boston-based independent journalist who covers science, health, and technology. You can follow her on Twitter at @jfsklar.