Our long, pandemic-inspired videoconference moment comes with several benefits, including the comfort of having to live and dress the part from the waist-up only (in my case, wearing basketball shorts and house shoes below the reach of the webcam), to how it has encouraged us to get creative in our approaches to sharing our work.
In March 2021, I was able to deliver a research seminar at the University of Chicago—to an audience full of frighteningly smart people with large reputations—without the risk of being screamed at or having a tomato thrown at me.
The freedom of the videoconference emboldened me to try different things. For this seminar, I dedicated precious time to telling the audience about predictions and ideas that I was wrong about. Not about my broken NCAA bracket, but about the many ways that my early assumptions and predictions about the Covid-19 pandemic were incorrect. By doing this, I was hoping to give myself an intellectual challenge (to say something smart about being wrong), as well as mask my insecurity, impostor syndrome, and fear of talking to an audience of extremely smart people. This strategy is more than a little bit pretentious: By dissecting a wrong idea in front of everyone, I would signal how awesome I truly was.
The self-serving aspects of the approach were not, however, the only motivations for admitting I was wrong. Over the last year I’ve been frustrated with the scientific community’s general reluctance to openly discuss when and why we’re wrong, and specifically, in our study and prognostications of the pandemic. Our unwillingness to highlight what we were wrong about was a missed opportunity to teach the public about the scientific process, to put its necessary ups and downs on fuller display.
Our aversion to discussing our wrongness has had dire consequences: We (perhaps unintentionally) oversold our confidence in concepts that were still underdeveloped, alienated many who had legitimate questions, and (ironically) fanned the flames of misinformation and disinformation. For example, quacks have generated mashup-edits of prominent scientists saying one thing about Covid-19 in June 2020, a different thing in August, and something else in November. In response, we mostly offered the same flabbergasted response: “C’mon. That is wrong, and that isn’t how science works.” But our responses are missing something: We might be part of the problem.
What underlies scientists’ inability to cop to mistakes, flubs, or poor predictions?
It would be easy to pin it on the notoriously large egos of scientists. And while egos fuel many problems in science, I suspect that the real reasons for our Covid-19 stubbornness are more complicated.
From the beginning of the pandemic, misinformation and disinformation were not mere nuisances, but defining forces in the global response. And their most influential authors were not only renegade “doctors” with YouTube channels, but government officials directly responsible for the pandemic policy.
At the very least, bad information stymied or derailed public conversation about the science of Covid. The truth is more grim: The doubt that was inspired by bad faith actors drove formal public health policies (or non-policies). Skepticism and science denial had stakes far greater than the winner of a Twitter spat. Simple unknowns were weaponized, and many Covid lies were actively orchestrated and propagated in order to sow doubt about the way that science works, sometimes for political gain.
In the face of this, the scientific community’s reluctance to come clean about uncertainties and missteps are not only understandable, but even appropriate: There is a time and place to have abstract debates about the true meaning of “efficacy,” and a time to act on the information that we have in service of the public good. The pandemic, and the millions of lives (globally) that we lost in its wake, qualify as a large enough emergency that one can forgive a little chest-thumping bravado: We’re scientists, we’ve spent decades studying this stuff, and your bullshit is harming people. We, experts and the informed citizen-science public, might know that science is a process that cannot exist without accumulating new data and discarding old ideas. But much of the public is unaware of how this process actually works. Our “trust me, I’m a scientist” appeals can be misguided.
