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.
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.]
Dr. Robert Montgomery, the director of NYU Langone's Transplant Institute, is ironically the recipient of a heart transplant.
[Ed. Note: This is the fourth episode in our Moonshot series, which explores four cutting-edge scientific developments that stand to fundamentally transform our world.]
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 Single Blood Test May Soon Replace Your Annual Physical
The measurement of proteins in one blood test could provide a comprehensive snapshot of a person's health in the near future.
For all the excitement over "personalized medicine" in the last two decades, its promise has not fully come to pass. Consider your standard annual physical.
Scientists have measured thousands of proteins from a single blood test to assess many individualized health conditions at once.
Your doctor still does a blood test to check your cholesterol and gauge your risk for heart disease by considering traditional risk factors (like smoking, diabetes, blood pressure) — an evaluation that has not changed in decades.
But a high-risk number alone is not enough to tell accurately whether you will suffer from heart disease. It just reflects your risk compared to population-level averages. In other words, not every person with elevated "bad" cholesterol will have a heart attack, so how can doctors determine who truly needs to give up the cheeseburgers and who doesn't?
Now, an emerging area of research may unlock some real-time answers. For the first time, as reported in the journal Nature Medicine last week, scientists have measured thousands of proteins from a single blood test to assess many individualized health conditions at once, including liver and kidney function, diabetes risk, body fat, cardiopulmonary fitness, and even smoking and alcohol consumption. Proteins can give a clear snapshot of how your body is faring at any given moment, as well as a sneak preview at what diseases may be lurking under the surface.
"Years from now," says study co-author Peter Ganz of UCSF, "we will probably be looking back on this paper as a milestone in personalized medicine."
We spoke to Ganz about the significance of this milestone. Our interview has been edited and condensed.
Is this the first study of its kind?
Yes, it is. This is a study where we measured 5,000 proteins at once to look for patterns that could either predict the risk of future diseases or inform the current state of health. Previous to this, people have measured typically one protein at a time, and some of these individual proteins have made it into clinical practice.
An example would be a protein called C-reactive protein, which is a measure of inflammation and is used sometimes in cardiology to predict the risk of future heart attacks. But what's really new is this scale. We wanted to get away from just focusing on one problem that the patient may have at a time, whether it's heart disease or kidney disease, and by measuring a much greater number of proteins, the hope is that we could inform the health of ultimately just about every organ in the body or every tissue. It's a step forward for what I would call "a one-stop shop."
"I'm very excited about personalized medicine through proteins as opposed to genes because you get both the nature and nurture."
Three things get me excited about this. One is the convenience for the patient of a single test to determine many different diseases. The second thing is the healthcare cost savings. We estimated what the cost would be to get these 11 healthcare measures that we reported on using traditional testing and the cost was upwards of 3,000 British pounds. And even though I don't know for sure what the cost of the protein tests would ultimately be, [it could come down to about $50 to $100].
The last thing is that the measurement of proteins is part of what people have called personalized medicine or precision medicine. If you look at risk factors across the population, it may not apply to individuals. In contrast, proteins are downstream of risk factors. So proteins actually tell us whether the traditional risk factors have set in motion the necessary machinery to cause disease. Proteins are the worker bees that regulate what the human body does, and so if you can find some anomalies in the proteins, that may inform us if a disease is likely to be ongoing even in its earliest stages.
Does protein testing have advantages over genetic testing for predicting future health risks?
The problem with genomics is that genes usually don't take care of the environment. It's a blueprint, but your blueprint has no idea what you will be exposed to during your lifetime in terms of the environment and lifestyle that you may choose and medications that you may be on. These are things that proteins can account for. I'm very excited about personalized medicine through proteins as opposed to genes because you get both the nature and nurture as opposed to genomics, which only gives you nature but doesn't account for anything else.
Proteins can also be tracked over time and that's not something you can do with genes. So if your behavior improves, your genes won't change, but your proteins will.
Could this new test become a regular feature of your annual physical?
That's the idea. This would be basically almost a standalone test that you could have done every year. And hopefully you wouldn't need other tests to complement this. This could be your yearly physical.
How much more does it need to be validated before it can enter the clinic and patients can trust the results?
This was a proof-of concept study. To really make this useful, we need to expand from 11 measures of health to a hundred or more health insights, to cover the whole body. And we need to expand this to all racial groups. Three of the five centers in the study were European – all Caucasian – so it's one of our high priorities to find groups of patients with better representation of minorities.
When do you expect doctors to be routinely giving this test to patients?
Much closer to five years than 20 years. We're scaling up from 11 disease states to 100, and many of those studies are underway. Results should be done within three to five years.
Do you think insurance will cover it?
Good question. I have been approached by an insurance company that wanted to understand the product better – a major insurer, with the possibility that this could actually be cost saving.
I have to ask you a curveball -- do you think that the downfall of Theranos will make consumers hesitant to trust a new technology that relies on using a single blood sample to screen for multiple health risks?
[Laughs] You're not the first person to ask me that today. I actually got a call from Elizabeth Holmes [in 2008 when I was at Harvard]. I met with her for an afternoon and met her team two more times. I gave them advice that they completely disregarded.
In many ways, what we do is diametrically opposite to Theranos. They had a culture of secrecy, and what we do is about openness. We publish, like this paper in Nature Medicine, to show the scientific details. Our supplement is much longer than the typical academic paper. We reveal everything we know. A lot of the research we do is funded by [the National Institutes of Health], and they have strict expectations about data sharing. So we agree to make the data available on a public website. If there is something we haven't done with the data, others can do it.
So you're saying that this is not another Theranos.
No, God forbid. We hope to be the opposite.
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.