Tag Archives: bias

American Exceptionalism?

When we hear the term “exceptional,” we tend to think in terms of merit–someone who is exceptionally good at something. But exceptional has another meaning: unusual. As in “not typical” or “abnormal.” Even before the disaster of the past four years, I’ve come to see American exceptionalism as more of an illustration of that less desirable definition than the former. Our current struggle with COVID-19 has certainly undercut the widespread belief that Americans are exceptionally competent.

My cardiologist cousin recently shared an article from the Journal of the American Medical Association (JAMA) that focused on the prevalence of biases that have inhibited our national response to the pandemic–biases that, when added to the utter lack of competent national leadership, certainly help to explain our inability to contain it.

The article began with a discussion of ventilators. One of the first decisions made by the Trump administration in response to the pandemic was to spend $3 billion dollars to build more ventilators. As the article noted, however,

These extra ventilators, even had they been needed, would likely have done little to improve population survival because of the high mortality among patients with COVID-19 who require mechanical ventilation, which acts to divert care-givers away from more health-promoting endeavors. Yet most US residents supported this response because they believed that enough ventilators would lead to better overall survival from this scourge.

So why are so many people supportive of ensuring a sufficient number of ventilators but not similarly supportive of efforts to implement earlier, more aggressive physical distancing, testing, and contact tracing– policies that would have saved far more lives? The article attributes that (illogical) response to the referenced biases, beginning with our human tendency to “prioritize the readily imaginable over the statistical, the present over the future, and the direct over the indirect.”

In other words, to prioritize emotion over science.

This causes humans to respond more aggressively to threats to identifiable lives, ie, those that an individual can easily imagine being their own (or representing of people they care about such as family members) than to the hidden, “statistical” deaths reported in accounts of the population-level tolls of the crisis. Similarly, psychologists have described efforts to rescue visible, endangered individual lives as a highest priority goal, even if more lives would be saved through alternative responses.

Anyone who has ever wrestled with the Trolley Problem has encountered that bias.

This very human trait is why descriptions of the millions of people killed by the Nazis and the Soviets, or reports of the Rwandan and Chinese genocides–or our own near eradication of Native Americans– are less moving, less likely to cause outrage, than the individual stories that emerge from those and other horrific episodes in human history.

The article also cites “Optimism Bias,” our human tendency to predict optimistic outcomes.

Although early pandemic prediction models considered both best and worst-case outcomes, sound policy would have attempted to minimize mortality by doing everything possible to prevent the worst case results, but human optimism bias led many to act as if the best case was in fact the most likely. President Trump provides one of many good examples of this bias.

There were others: A preference for benefits in the “here and now” to larger benefits in the future,  leading us to place greater value on saving a life today than a life tomorrow, and something called Omission Bias–a desire to avoid an imminent “harm” (like the pain of a vaccination) even when avoiding it is likely to lead to significantly worse results down the road.

It’s one thing to recognize the prevalence of these very human biases. It’s another thing, however, to indulge them–and it is unforgivable to cater to them through public policies rather than basing those policies on medical and scientific knowledge.

If we really want to achieve that first definition of American “exceptionalism,” we will stop denigrating and dismissing scientific and other expertise, stop scorning people who know what they’re doing as “elitists,” and stop electing people. who pander to our biases rather than those willing to base policy decisions on the best information available.


Producing A Shared Reality

A major element in the rightwing attack on “Fake News” is the assertion that platforms like Google and Facebook skew to the left, that they privilege liberal results.

Scholars and journalists, for their part, worry about the “filter bubble”–the use of sophisticated algorithms to target individuals with information that is consistent with their pre-existing biases.

A recent study focused on Google provides some reassurance on both counts.  

Google News does not deliver different news to users based on their position on the political spectrum, despite accusations from conservative commentators and even President Donald Trump. Rather than contributing to the sort of “echo chamber” problem that critics fear have plagued Facebook and other social media networks, our research has found that Google News algorithms recommended virtually identical news sources to both liberals and conservatives. That’s an important point to keep in mind when evaluating accusations that Google News is biased.

Our findings are part of an ample and growing body of research on this question. Online services – including Google’s regular search function – may provide intensely personalized information. But media scholars like us have found that when it comes to news, search engines and social media tend to lead people not to a more narrow set of sources, but rather to a broader range of information. In fact, we found, Google News is designed to avoid personalized search results, intentionally constructing a shared public conversation based on traditional criteria of journalistic values.

The construction of that public conversation is critically important. As the eminent media historian Paul Starr has observed, “journalism isn’t just about uncovering facts and framing stories; it is about assembling a public to read and react to those stories.” In other words, there is a crucial difference between an audience and a public.

Journalism in a democratic system is about more than dissemination of news; it’s about the creation of shared awareness. It’s about enabling citizens to occupy the same reality.  It’s about facilitating meaningful communication. As the information environment continues to fracture into smaller and more widely dispersed niches, many of us worry that we are in danger of losing the common ground upon which public communication and discourse depend.

When cities had one or two widely-read newspapers, residents were at least exposed to the same headlines, even if they didn’t read the articles. When large numbers of Americans tuned in to Walter Cronkite or to his competitors on one of the other two networks, they heard reports of the same events. If today’s citizens do not encounter even that minimal amount of shared information, if different constituencies access different media sources and occupy incommensurate realities, the concept of a public becomes meaningless.  Informed debate becomes impossible.  In that sort of fractured and fragmented environment, how do citizens engage in self-government?

If I say this is a table, and you insist it’s a chair, how do we come to an agreement about its use?

I hope this study, and the others it cites, are right–and that Americans retain enough of a common language and share enough of a common reality to qualify as a “public.”