We have so many numbers to describe how awful things are. Since February, the United States has conducted 170,315,721 Covid-19 tests, identified 11,603,800 cases, and tallied 250,300 deaths. In April, the unemployment rate hit a record 14.7 percent. Since the start of the pandemic, six million hungry Americans have enrolled in SNAP.
These numbers are supposed to guide our decision-making. They usually fail. While statistical shock and awe is abundant, we are often unable to grasp the true meaning of such figures—stymied by basic innumeracy, the incomprehensible scale of our present crises, and the profound mismatch between hard data and human feeling. But what’s the alternative? An ingrained technocratic bias toward quantification and the “expertise” it breeds has left many Americans, especially on the left, with the conviction that data is more valuable than any other form of knowledge. The pandemic has only magnified this reductive impulse: Isolated in our homes and largely unable to make sense of this year’s successive traumas together, we have clung to figures “like a raft in a sea of gobbledygook,” Kareem Carr, a doctoral candidate in biostatistics at Harvard, told me. But still, we are drowning in a sea of decontextualized data.
Statistics can tell us something about the world no other method can, but there is value in other forms of intelligence: in storytelling and wisdom traditions in intuition and moral reasoning. When “believers” in science position themselves on the side of the rational and promote mathematical reasoning above all else, they alienate themselves from important questions—and fresh answers—about the world around them and the people in it. The pandemic has shown that to face our many, interlocking catastrophes, we need other ways of thinking about the world and acting on it.
The human brain gravitates toward numbers but struggles to understand them. For example, a common mental shortcut called anchoring means we “tend to kind of seize on the first bit of information that we get, and then that becomes a reference point against which we judge all other information,” Bradley Adame, an associate professor of communication at Arizona State University, recently told The Verge. Numbers are especially powerful anchors—ironically because they perplex us, even as we’re certain we know what they mean.
Early in the pandemic, public health officials predicted Covid-19 would have a 1 percent mortality rate. That figure seems very small: There are better odds of getting into Harvard or dying in a car crash over 50 years of driving. But it was a dire prediction that one in 100 infected people would die. Even when people latched onto big, round numbers, like the possibility of a million American deaths, few understood that they could become a part of that statistic. Numbers are important, but they happen to other people.
At a governmental level, our inability to grasp the size of the Covid-19 crisis led to a mismanaged response that contributed to thousands of unnecessary deaths and an insufficient, onetime relief package. On a personal level, a failure to comprehend risk has led people to engage in potentially deadly activities, from grocery shopping maskless to going through with wedding plans. Online, where misinformation is rampant, numbers do little to combat the deluge of lies that often incorporate quantitative claims of their own. Now it’s increasingly apparent that data does little to help us grieve.
Honoring the dead has never been harder, and not just because the pandemic has closed hospitals to visitors and limited the size of funerals. For the last 20 years, the government has been quietly dismantling our capacity for collective mourning, argues Colin Dickey in Gen. Grief is politically volatile, so the GOP has made a mockery of it. “Death, to these ghouls, has ceased to mean anything beyond numbers, statistics, and polling results,” Dickey writes. Without an appreciation for the source of these numbers—the human pain and suffering, the crumbling institutions, the rapacious greed—they become emotionally inert and politically dangerous. Just look to Texas Lieutenant Governor Dan Patrick, who announced in April that he would die for the economy. “Let’s face reality of where we are: In Texas, we have 29 million people,” Patrick told Tucker Carlson. “We’ve lost 495, and every life is valuable, but 500 people out of 29 million, and we’re locked down.” Evidently, in the lieutenant governor’s Excel sheet, lost profits and lost lives are indistinguishable.
We see a similar pattern play out in other calamities, including the climate crisis. For decades, manufactured disputes over the “science” have delayed action. Even as we moved toward something like consensus on this issue, the scope of the problem, and the radical nature of the necessary response, can make the whole enterprise seem doomed. Perhaps the biggest impediment to change has been the misguided belief that it is a future problem—that one billion people may be displaced by climate change but not until 2050, or that New York City could disappear beneath the waves but not until the turn of the twenty-second century. Numbers are still important, but they happen to future people.
Death—from a virus, from climate change, from old age—is typically something people aim to “realize” in the most literal meaning of that word: to make real. The living cut their hair and tear their clothes in grief; they don’t typically turn to national vital statistics to see how many other people died the same way as their loved one. Unless, of course, they want to distance themselves from their pain. This year, that numbing by numbers has become a chronic condition. “Such is the perverse mathematics of tragedy: the staggering specificity of any one life lost; the overwhelming obscurity of lives lost,” Casey Cep wrote in The New Yorker in May.
The solution is not the end of statistics. Despite the Trump administration’s efforts to make an enemy of numbers themselves, public health officials, climate scientists, and policymakers should craft policies based on reliable data. But “statistics does a violence to human experience,” Carr said. “It crushes it down and throws out a lot of relevant information.” These limitations must be augmented with other kinds of insight, or at least acknowledged. We need to see the forest, but we must remember that we are the trees.
In the pandemic, obituary writers have taken on a new importance, Cep wrote in The New Yorker. When the coronavirus first made headlines, outlets began weaving death tolls into their reporting and spinning numbers into elaborate infographics. They also started publishing thousands of stories commemorating the people Covid-19 killed. Staring down the landmark of 100,000 coronavirus deaths, The New York Times published a front page full of mini-obituaries in May with the name, age, location, and a single fact about each of the deceased. Alternative proposals, like printing 100,000 dots, wouldn’t “really tell you very much about who these people were, the lives that they lived, [or] what it means for us as a country,” Simone Landon, assistant editor on the Times graphics desk, said at the time. These and numerous other memorialization efforts across the country reflect the earnest belief that an obituary, in Cep’s words, is “as close as we come in times like these to squaring the demands of statistic and story.”
Health communications experts increasingly agree. “There is growing evidence that traditional communication of vaccines—e.g., messages focusing on statistics—has not worked well,” Xiaoli Nan, director of the University of Maryland’s Center for Health and Risk Communication, told Undark. Rather than shaming people for their misunderstanding—or even their willful indifference to the facts—Nan and her team are looking for alternatives. “More successful strategies rely on trustworthy messengers, telling stories rather than using statistics, and appeals to moral values.”
Seeing outside of our single cell on this vast spreadsheet can feel impossible. I’m also just a number on the census, a Facebook algorithm, a product of our technocracy. But Carr told me something that helps to lay the foundation of the paradigm shift we need: Statistics are more like quantum physics than basic math. We want everything to add up as in middle-school algebra. But the real world is more complex, and more uncertain, than that. Embracing the chaos behind the cold, hard data could help us realize what we’ve lost—and what we can still save.