Was Covid-19 NOT a black swan event?! (Part 2)
Trying to predict uncertainties is inherently futile and unhelpful; plus the experts didn't correctly predict much in the first place...
In Part I of this essay, I talked about how it’s in the natural tendency for the public discourse and political institutions to ignore existential threats to humanity. Therefore, the warnings made in TED talks by public intellectuals like Bill Gates do very little in actually getting us prepared for these risks in substantive ways.
But taking a step back, I want to make an even stronger argument in this Part II: First-order predictions about a black swan event are often not that helpful when its second-order, subsequent impacts could dramatically deviate from any initial forecasts. The world is in a horrible place right now not because we missed Bill Gates’s prediction about epidemics in 2019, but because we missed dozens of predictions and opportunities to fix the crisis bewteen March and today.
Predictions by a few brilliant experts aren’t that helpful…
Taleb and Tooze think Covid isn’t a black swan event partly because they think it was entirely predictable. My two initial objections are:
Sure you can say that some experts totally saw it coming, but a few visionaries cannot replace the failure of an entire “expert class” – those who are in positions of power in academia and policymaking. In fact, the best experts repeatedly got things wrong and are still giving out wrong and inconsistent predictions.
Even if you had predicted the initial fallout itself, the subsequent set of chain reactions often spiral way out of people’s imagination, making the initial prediction not so valuable.
For example, some brilliant investors in the tech world must have envisioned a dramtically different world with the rise of social media apps like Facebook and Twitter, but the impacts of these technologies have been much more profound and negative than anyone foresaw. That’s why we see some investors regreting nowadays that they had invested in companies like Facebook – their initial prediction that Facebook would connect people across the world was correct, but it’s also useless today as Facebook’s second-order impacts are much more consequential (e.g. influencing elections, profiting off of people’s echo chamber addictions, etc.).
It is already hard enough to predict the first-order trajectory of a virus, a technology, a movement, or a policy. But it is even harder and close to impossible to foresee the second-order impacts of these first-order developments. And arguably, the second-order chain of events are much more consequential than the initial black swan events themselves.
Those who can do well at first-order projections are successful VC investors, policymakers, and the like. Those who do well with second-order predictions are a few rare visionaries but mostly charlatans. The charlatans don’t have to be outright frauds; they are often well-intentioned policymakers blined by their own naive empiricism and ideological biases. (By the way, which category does Alex Jones fall under? And what about Alan Greenspan?)
The experts also didn’t correctly predict much…
Many seem to suggest we could’ve prevented Covid long before January. Sure, but we didn’t even need to do that. Had we gotten any prediction right in the subsequent months, things wouldn’t have been as bad.
I would prefer to focus not on the initial mistake, but on the prolonged series of failures by the expert class from March until today that will almost surely continue into the foreseeable future:
Trajectory of the virus
The political and media institutions across the spectrum (except a few) failed completely in predicting the swiftness and trajectory of the virus spread in the US. For timeline reference, In January, people in China knew Covid was going to evolve into at least a national epidemic. Even here at Policy Punchline, we interviewed epidemiologist Jessica Metcalf on Febuary 14th, in which she clearly stated that Covid would evolve into a global pandemic.
In other words, you didn’t have to know in 2019 that Covid were coming; you just needed to know that in Febuary; and most of the experts didn’t even do that. The institutions continued to give out wrong advice and predictions to the public until March and later.
Even today, there is still not an academic or scientific consensus regarding how deadly Covid-19 truly is. Therefore, the public discourse ends up devolving into being “narrative-driven,” where media outlets and even science experts cherrypick a set of facts to defend a certain political party’s decision, which continues to happen today even though our understanding our the virus has improved.
The suffering economy
In March, we suffered the fastest fall in global stock markets in financial history and the most devastating crash since the Wall Street Crash of 1929. People were prepared for a years-long recession, and Congress quickly passed the CARES Act.
The stock markets, however, magically recouped losses in a span of weeks and even reached historically high level of equity prices, and everyone got cocky and started talking about a V-shaped recovery: “this is a temporary shock to the economy, and there were no fundamental underlying issues blah blah blah.” The political will for more fiscal stimulus soon dissipated, and only on 12/21 did the Congress painfully pass a small $900 billion relief package.
The stimulus was late, long-overdue, and insufficient to solve the problem. Today, we’re still 10 million jobs away from the employment level in Febuary. We will likely head into an anti-competitive post-Covid recovery where large corportions eat up market shares of small Main Street businesses. Wealth inequality is pushed up to historically high levels.
The scary feeling and sense of urgency from March have long been forgotten and put into the history books. Today, we’re nowhere close to reaching a political consensus regarding what kind and size of stimulus is needed for post-Covid recovery in 2021 and beyond. The one consensus we do have, however, is that market participants are now more confident than ever that the markets will continue to go upwards next year.
Efficacy of lockdowns and preparedness for ICU rush
In April, lockdowns were instituted in hope to stop the spread of the virus. We said we were going to do them for a few weeks to stop the spread before gradually reopening up. The lockdowns turned out to be much less effective than we predicted because of a variety of factors from people’s unwillingness to cooperate to the chaos in federal-state coordination. Then, Europe had to go back into lockdowns in November, and likewise with many part of the U.S. because the extremely high level of case counts are overwhelming hosptial capacities again like they did in March.
Say it was understandable that the local governments weren’t prepared for the ICU rush in March, but then they had 8 months to prepare for the second wave – which politicians have been talking about for months – and they still didn’t get it right.
8 months after the initial Covid hit, most politicians are still unable to express a consistent view on the trade-off between public health and economics. Which do you prioritize and at what cost? Because it’s difficult to take a stance, most have chosen the easy way out to resort to reactionary and flip-flop policies, such as telling businesses to reopen and close under a short notice, while not investing nearly enough resources for school reopening or hospital capacity expansion.
The severe consequence is the loss of public trust. California governor Gavin Newsom and NY governor Andrew Cuomo were initially praised as brilliant technocrats who took swift actions against Covid, but are now seen as enforcers of unreasonable, inconsistent lockdown policies even by initial supporters. On the other hand, Florida governor Ron DeSantis, who initially ignored expert advice and simply decided to fully reopen the state, is seen as a rising star by Republican voters for not instituting any lockdown. These are all sub-optimal policy choices, and it shouldn’t have to be this way.
Non-existent social solidarity and more dramatic polarization
When our podcast began our Covid-19 special coverage in March, and likewise with all podcasts and articles published then, the central narrative was all about “social solidarity.” What happened later was QAnon swept through the heartland; BLM forced a major social awakening upon this country; dramatic polarization dominated the socio-political discourse; and half the country now thinks the election was stolen… Nobody saw any of this coming.
So, from the trajectory of the virus to the duration of the lockdown, from V-shaped recovery to the great social progress and “Blue Wave” – most of the dominant narratives and predictions have been proven to be wrong and wrong and wrong…
You can see Covid-19 as this big, overarching, singular event that could’ve been prevented long before it happened. Or, you can see it as a series of small “black swan” events all connected together, and we managed to mishandle and mispredict almost every single one of them in the past few months.
Stop trying to predict; embrace the uncertainty to make good policies
What I hope to show here is even if we didn’t get the initial outbreak right, we still had a few dozen of opportunities to compensate for that initial mistake. The fact that we still mismanaged all the following opportunities thus points not to our inability to prevent Covid early on, but our more fundamental inability to make good decisions in face of radical uncertainty.
Taleb tried very hard to convey this point in his works and in that New Yorker interview:
His profession, he says, is “probability.” But his vocation is showing how the unpredictable is increasingly probable. If he was right about the spread of this pandemic it’s because he has been so alert to the dangers of connectivity and nonlinearity more generally, to pandemics and other chance calamities for which covid-19 is a storm signal. “I keep getting asked for a list of the next four black swans,” Taleb told me, and that misses his point entirely. In a way, focussing on his January warning distracts us from his main aim, which is building political structures so that societies will be better able to cope with mounting, random events.
Taleb wants us not to focus on the initial mistakes, but to care about the series of mistakes we continued to make and the lessons we shall learn from them.
We should stop fooling ourselves that it would be possible to keep foreseeing and preventing all “black swan” events because they’re by nature unpredictable. Trying to pin down uncertainties defeats the whole point of studying uncertainties. What is needed, therefore, is to build up resilient institutions that can be “antifragile” to most uncertainties.
Collective blindness in hindsight
Taleb warned us about the “collective blindness” before the black swan event took place, but what I see as more dangerous is the collective blindness and memory loss in hindsight.
Because we’ve read so much about Covid, because there’s so much media reporting on how the government failed to respond to it, and because we think we know the matter so well today, we’re now convincing ourselves that we could’ve totally seen it coming.
Or, at least, we think that had we had the kind of information that Trump or the government had, we could’ve totally predicted what would then unfold.
But we didn’t back then, and we probably can’t going forward. So, it’s probably best to get out of our own cognitive dissonance and hindsight bias and stop thinking that we’ve got it all down.
As I’ve explained in my post about election forecasting, we should constantly adjust our beliefs in face of uncertainties that constantly emerge in today’s world. One helpful to put this into practice could be to write down a few short-term predictions you have for 2021, and see if they match with what acutally happens. If they don’t, that means that you should probably readjust your way of thinking.
The last thing we need today, however, is to linger on the initial mistakes we made in January and convince ourselves that the world would’ve been a beautiful place had we just fixed this one thing… The reality is there were in fact so many more things that we failed to fix, and we won’t get it right next time either.
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Re: Soros and reflexivity: Human behavior is fundamentally labile. That's why it cannot be modeled with polynomial equations with fixed (let alone know) coefficients. The assumption that these coefficients exist has led to a lot of meaningless mathematics (the use of calculus especially) among modern academic economists. The baleful effect of Paul Samuelson.