One of the most talked about sessions at the AWC Annual Conference was the final plenary with Dr. Jevin West of UW and its Center for an Informed Public (CIP)—and author of a book titled Calling Bullshit. Here, we highlight his talk about misinformation—and its sneaky counterpart, disinformation, along with suggested steps people working in local government can take to recognize and address these insidious information trends.
Brandolini’s law states that “the amount of energy needed to refute BS is an order of magnitude bigger than what is needed to produce it.” In other words, it’s a lot easier to make a mess of information than it is to clean it up or prove it wrong.
Accordingly, Dr. West began his session by sharing that he “never has a shortage of material,” but that there are lots of ways we can all learn to be better consumers of information. He shared an image of a fake bombing that, when posted, went viral globally. Although it was quickly proved to be a “deep-fake” generated by artificial intelligence, it had already been pushed by both Russia and India’s propaganda machine—the end result being a half-trillion dollar drop in the market. As Dr. West pointed out, “there’s a lot of money to be made in a half-trillion dollar drop.”
Motivations not-withstanding, his point is vital. The tech is out there to be used. And with this kind of impact, imagine what could be possible during elections or crisis events? Across the country there’s a slow decline of trust in our information environment—problematic for a wide variety of reasons, not least of which is that when we become over-saturated with false emergencies, we may not be willing—or able—to act fast when there’s a true crisis.
While public trust in government is abysmally low in the United States, Dr. West reminded attendees that trust levels are much higher for local government—nearly twice as high, in fact. That puts a burden of responsibility on local officials to consider carefully, and respond thoughtfully, to online information.
Dr. West touched on several categories of information, including rumor. Rumors are unofficial and unverified stories about events that may or may not turn out to be true. Some may be tropes (sharks in the street during a flood) but may also…sometimes, be true.
Defining what is and isn’t mis- and disinformation can sometimes be tricky, since they’re often built around some kernel of truth. The main difference is that misinformation is shared unintentionally and disinformation is shared intentionally and is designed to misinform, confuse, or distract.
MISinformation is false or misleading info that has been misunderstood or misconstrued, and it can be very harmful because it often comes with sincere and generally good intentions, sometimes even from trusted sources.
DISinformation on the other hand is info that is false and is intended to be misleading.
So how do we identify false or misleading information—especially when its trajectory is ever-more sophisticated? Dr. West has advice. He stressed that scammers work hard to leverage peoples’ good intentions, and to capitalize on our emotions. One of the favored methods is with a “bait and switch” tactic. The example Dr. West used was a local Facebook post about a sad/lost/medically needy dog, a post that plays on our emotions. We want to help, and so the post gets moved up, or reposted, shared, or messaged, and before we know it the link is switched out and instead of helping a sick dog, we’re all looped into some “amazing” real estate deal.
Dr. West focused most of his session on misinformation and noted that it often comes wrapped in data and graphics. Synthetic media and memes are big too, but when information is wrapped in data, it looks official and can lead to impactful decisions.
One place information can easily go astray is in assuming causation. Arranging data on the wrong scale can lead to some alarming suggestions and spurious correlations, such as a chart Dr. West shared showing that the number of letters in the winning word of the national spelling bee can be correlated to the number of people killed by venomous spiders! His point was that if you look at millions of data sets, you can always find things that will coincidentally align. You might think there’s a correlation, but really…there’s not. Furthermore, correlation is not necessarily causation. In fact, lots of people—including professional researchers and journalists—misattribute causality and correlative evidence.
One real-life example was the assertion that bald men were at higher risk of severe Covid. This idea went internationally viral in part because it began with publication in a legit journal. There was an association between baldness and Covid—a common cause—namely age, but that commonality was not correlative. Many bald people were over a certain age, and many people who got Covid were over a certain age. Baldness, however, does not cause Covid, nor does it increase the disease’s severity.
Another really common area for misinformation/misunderstanding is in selection bias. This is when the researchers choose a cross-section of people to study that (unintentionally) impacts the outcome. An illustrative example Dr. West used was data that apparently showed a high degree of correlation between being a rap artist and being murdered—giving these musicians a higher occupational hazard rate than soldiers of war! In fact, however, because rap is a relatively new format, the sample pool was bad (because most rap musicians aren’t old enough to have died normal, non-violent deaths). Rap has only been around a short while, so anyone who has died so far, has probably died young. Most rappers haven’t had the chance to die of old age (selection bias).
With the amount of distrust and division in our world, Dr. West stressed the importance of recognizing the difference between a lie and a mistake. At one point during the Covid crisis, there was a claim circulating that dentists believed masks cause cavities. In fact, this was just an error, because at the start of the crisis so many people without issues avoided going to the doctor or dentist. Therefore, the group they sampled was only made up of patients already suffering with severe dental issues.
Bottom line? If it sounds too good (or too bad) to be true, then it probably is.
When it comes to looking at data—Dr. West says, you can start with information that’s true, and still wind up with misinformation (intentional or not). Here are a few tips he advised everyone to use when reviewing data in charts and graphs:
- Question big drops/rises.
- Check that bar graphs start at “0.”
- Check for cherry-picking. Do graphing units remain consistent across the graph? You shouldn’t have 1-year intervals for 10 years, followed by a 10-year jump, nor should you have missing years, or datasets.
- Remember that cumulative graphs (like iPhone sales) ALWAYS go up. If you showed quarterly sales, that data would show a different story.
- Be alert to scaling mistakes, as these can lead to major misinterpretations.
- Read laterally! What are other sources saying about the information or how it’s presented?
Lastly, and in defense of civil discourse, Dr. West ascribes to the rule of thumb called Hanlon’s razor:
“Never ascribe to malice what can be adequately explained by incompetence.” He takes this adage one step further: “Never ascribe to incompetence what could be an understandable mistake.”
Relevant to virtually every discussion around distrust and division, Dr. West reminded attendees that while we all want to get better at these distinctions, ideally—and to position ourselves for the very best outcomes, we can learn to do it tactfully, and in a way that makes all of us look smarter, rather than at someone else’s expense.
Here are a few of Dr. West’s suggested skill-building resources for local officials to begin shifting their approach to information:
Traversing the information ocean can feel intimidating, and at times overwhelming, but Dr. West made clear his belief that—regardless of the size or nature of the divide—we can co-design for trust, building bridges by taking small steps thoughtfully and consistently, together.