Avoiding misinformation at a time of uncertainty

Danil Mikhailov
9 min readMay 3, 2020

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I have written quite a bit on misinformation during the current Covid-19 pandemic, building on my expertise as a sociologist of science and technology. However, so far, I have always looked at the issue from the perspective of experts competing with misleading and often dangerous messages about the virus that are being shared by non-experts.

Lately, however, I have been thinking about a different category of misinformation altogether. Like many involved in Covid-19 work, I follow daily reports from multiple national governments on their specific responses, policies and plans. I also take in a broad range of respected media channels — BBC, CNN, the Times, the New York Times etc — observing how government messages are framed and presented, commented on, disputed or affirmed, mixed with opinion from numerous talking heads of varying degree of expertise. Finally, I see these messages hit social media channels like Twitter, where they are summarised, liked, forwarded, commented on, and so on.

A representation of a network of people connected online
Copyright: Wellcome

All, or most, of the participants in this “official” communication flow — the policy makers, journalists and politicians — are well-intentioned and try to stick to the facts, as we know them. And yet I am increasingly struck by the feeling that too much of the information being shared is likely to be misunderstood by the public and lead them to be misinformed.

To take one example, at the moment media channels of all types, from TV, to papers, to social media are saturated with debates about how different countries are going to come out of the lock-down. The focus is on testing, on contact tracing, on apps. Countries like South Korea are mentioned as models for how to do this successfully. And yet, as any scientist studying this epidemic will tell you, it is simply too early to tell if an exit from lock-down can be made successfully, without the infection rate ratcheting up again and becoming exponential. We simply do not have the data yet. Yes, South Korea has gotten on top of the initial outbreak — in February its infection rate was rising out of control, yesterday for the first time it had no new local cases — but it’s too early to judge. A few weeks ago Singapore was praised for getting on top of its infection rate too, but since then its rate has accelerated again.

The problem is that the facts may be right as they stand now — South Korea is indeed doing well at the moment, that much is not misinformation — but the conclusions about the future are premature. Because this virus is so new and so little is known about it still, despite remarkable progress by scientists, we are forced to operate in conditions of high uncertainty. And the virus itself is not the only source of uncertainty. Never in history has a third of the world’s population been locked down at the same time. We simply have no idea what effect this will have on the economy, on social order, on politics, or on our collective mental health.

Of course, governments cannot be paralysed by a lack of certainty. They have to make decisions on the best information available to them. But there is something different to this global crisis compared to previous global events of similar scale, whether previous pandemics like Spanish Flu, or events like WWII. Our communication system has radically altered the relationship between rulers and ruled. Governments now have to make decisions in the full glare of media attention and citizens are no longer passive recipients of one-way information. The communication is many-to-many, with ability for any citizen, at least in theory, to have their view heard, be picked up by others, go viral and thereby demand a response. During WWII, leaders like Churchill or Roosevelt could decide what information their citizens should know and what is best dealt with by those in charge. Even when the information was shared, it could be tightly controlled. If you had an unfavourable article appear in a newspaper, you could pick up the phone to the editor and try to argue your case. Who do you call when an awkwardly phrased answer in a live interview is broadcast across the world and then Twitter and Facebook explode, with a thousand memes going viral?

And this many-to-many communication has accelerated beyond all recognition in the last decade and a half. Technology, as the philosopher Paul Virilio rightly observed, has the ability to compress space and time: there is no corner of the world now where a message cannot reach and reach almost instantaneously. The internet and social media have created a beast hungry for constant information. In this world conclusions can’t help but be drawn, however premature. Our system of communication demands it. As nature abhors a vacuum, so a communication system must have news to report, opinions to share and predictions to make.

So, even though politicians, journalists and the broader chattering classes may know that we do not have the data to be sure lock-downs can be lifted successfully, or whether you become immune after you get the virus, or whether a vaccine will be effective, we cannot help speculating and raising expectations to fever pitch and then, if those expectations are dashed, trying to find someone to blame. Often that someone being the poor scientists and epidemiological modellers who have always caveated what they say, but whose nuance and caveats simply cannot cut through into public consciousness through the communication storm.

The whole premise of the scientific method is to come up with a hypothesis, which is then tested, a hypothesis that can later be falsified by more information, indeed, a hypothesis that must be falsifiable, as the philosopher Karl Popper argued. That testing and revision of what we know is core to scientific progress, but in the age of instant many-to-many communication, this is too often misunderstood — often wilfully so — as the original idea or model being “wrong” and therefore its authors being “to blame”. It’s been heart-breaking to watch scientists being attacked as they rightly adjusted their models, predictions and analyses, as they learned more about the virus and as they factored in public health reactions to it. Taking hypothesis and prediction as literal immutable truth, ignoring caveats, refusing to accept revisions is, in my opinion, also a category of misinformation.

So, what can we do with this very different type of misinformation? It is not caused by lack of education or a hidden agenda in the way the more traditional type I have considered so far often is. It is comprised of facts that are not actually wrong, just premature or incomplete. The issue is inherent in human nature: when we are scared, we want answers and we want them now. This inclination is augmented by technology that so conveniently seems to serve up answers at a click of a button. You cannot educate or explain the problem away, because the purveyors of this type of misinformation are acting under pressure caused by the affordances of technology and the communication system we now have (see my previous posts about how communication platforms exert time pressure and how we are subject to technological somnambulism).

The answers lie in understanding that the communication storm that is raging all around us shares some features with real storms: when you are in the midst of it, your senses are overwhelmed. Like a ship caught out in a storm at sea, you don’t know where the reefs are. You need a point of orientation: the light of a lighthouse if you will. So, the key question with a communications storm is what can serve as our lighthouse: what are the indubitable facts about this virus that will not change among the many that might?

I think there are three important ones that we need to hold on to, to get us through the storm safely.

One, science is the only exit strategy, as my colleagues in Wellcome rightly affirm. The world has no immunity to this virus. We need to invest in and support science to find a vaccine and/or drugs that are effective against Covid-19. Yes, we do not know if any given vaccine or drug will work or how long it will take to find one that does, but we can be certain that a vaccine is how we get out of it. The oft debated alternative strategy of herd immunity is not in fact a strategy at all, it is the default position we land in if our one viable exit strategy fails, as this excellent article explains.

Two, we know that until we have a working vaccine and/or drugs we need to flatten the curve of infection so our health systems don’t collapse and we minimise the number of people who die. That means changes to our pattern of lives that prevent us from passing on the virus, if we have it. But we need to do it in such a way that our economies and societies do not completely break down, as that might harm as many or even more people than the virus itself. For this reason, at the same time as supporting the scientific experts, we also need to broaden the circle of what we see as an expert. A complex system problem like this pandemic needs not only epidemiologists, but everyone from computer scientists, engineers, manufacturers and logistics experts to operationalise results of research (how do you get from 1 viable vaccine to 7 billion doses of one?), to social scientists, psychologists, economists, experts in arts and humanities to understand the effects on the population of lock-down policies. Each has a part to play, but each will also need to show flexibility of approach, stepping out of their own box in a way that may feel uncomfortable, to create a truly interdisciplinary effort.

Three, patience, diplomacy and international cooperation are crucial at all levels to maximise the chance of success. Under immense pressure, the temptation is always to point the finger of blame, but we know the one thing that will guarantee we fail is if, when confronting a powerful enemy, we fight among ourselves. The virus cares not for political parties, ideologies, religions or national borders. Scientists finding a viable drug or a vaccine would not solve the problem, if said vaccine or drug is nationalised for the use of our country only, or even our country first. In an interconnected world a virus that becomes endemic in India or Congo or Russia, makes obsolete all the money that might be spent by Europe or USA to protect their own citizens, as new waves of infection are imported, possibly with mutations that make the original vaccine ineffective. Research done by any country that is not shared with the international scientific community openly, just slows us all down, as the speed of getting out of the pandemic for all of us, will be set by the slowest, not the fastest runner.

These three things are sufficiently well established and so should form the core of all communication messages. Much of the rest, that is reported as fact, is uncertain and subject to change, or should be assumed to be.

It’s worth observing, also, that we know the whats but do not know the hows. Classically, in scenarios where the what is known but the how is not, you need to experiment, be flexible and be ready to change course as more evidence emerges. To give ourselves the ability to change course, we need to maintain public buy-in and trust. This requires a different type of communication style from our leaders.

Above all else, we need transparency about the difficult choices facing us, acknowledgement of uncertainty, and openness about any mistakes being made. In the current world of over-exposure and many-to-many communication leaders must assume that any mistakes will come out and if they are caught hiding them, leaders should expect to lose the trust of the populace. Being authoritative, competent but unflinching in telling hard truths from the beginning is the only way to cut through this new type of misinformation caused by the over-abundance of communication at the same time as our knowledge is at its most limited.

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Danil Mikhailov

Anthropologist & tech. ED of data.org. Trustee at 360Giving. Formerly Head of Wellcome Data Labs. Championing ethical tech & data science for social impact.