Coronavirus has been all over the news the past few weeks, and you'd be forgiven for feeling like the world is suddenly falling apart around us. At this point, it's clear that public officials' response to the crisis so far in the United States and Europe has been woefully inadequate and far too late in light of the virus's exponential growth rate and potential to overwhelm hospitals. If you haven't already made plans to close your office and prepare for extended periods with your kids home from school, do it now! I can't emphasize this enough: unless you are in the business of providing essential services, you are killing people in expectation the longer you wait to shut things down.
That might seem like a ridiculous statement if there are only a handful or even zero confirmed cases in your area. But that can change fast. I write to you today from Westchester County, New York, where there were zero reported cases on March 1. By the end of the week, we had close to 100, one of the worst outbreaks in the United States. So this crisis has extra personal resonance for me, and I'm grateful that my risk modeling background has come in handy for helping my family and me anticipate and cope with the present situation. Below is a selection of things I've learned or am thinking this week about with respect to COVID-19, most of which I don't see getting talked about that much in other places:
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While it may seem inevitable now that many, many people will contract the virus at some point, there are lots of reasons why you should still try not to be one of them. First and foremost of these is the need to flatten the curve, or avoid a situation where hospitals become so overwhelmed with serious cases that they can't function. But another reason is because we don't know that recovery is always complete and permanent. One study, for example, found that about a quarter of SARS survivors suffered from chronic fatigue syndrome for years after infection. (SARS is the closest genetic cousin to the novel coronavirus among past diseases.)
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This situation is instructive for understanding the difference between personal risk and collective risk. On the one hand, it is still the case that in the vast majority of the world, going out for an errand today to shop for groceries or go to the gym is extremely unlikely to result in your infection -- well less than a 1 in 1000 chance according to my estimates. And yet we are seeing that failing to take early and drastic action to curb community spread has enormous impacts on the ultimate harm caused by the outbreak. How can this be? It's because even though the chances of you, personally, becoming infected may be tiny, if thousands upon thousands of other people in your local community make the same choice, the chances of someone getting infected are almost certain -- and then that someone will infect more people, and on and on. So the many, many cancellations and disruptions to the economy we're seeing are absolutely the right move even taking into account how inconvenient they are.
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Probabilistic thinking is extraordinarily relevant to this crisis. The risks we can choose take on in this environment are measured in small increments. We don't face a binary choice between hiding out in a bunker for months or acting as if nothing is out of the ordinary. You can still take a walk outside. You can still go to see the doctor for an unrelated issue or take a meal to a friend who needs one. If your have no choice but to be in regular close contact with other people, you can still avoid getting sick if you're lucky and careful. The more careful you are, the less lucky you need to be. Be careful out there, folks.
For more, the rationalist and effective altruist communities have been all over this topic for weeks before most people were paying attention. And the EA-affiliated forecasting platform Metaculus has a whole set of prediction tournaments in progress. If you're interested in taking a deeper dive and exploring more speculative questions related to the pandemic, those links are great places to start.
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Smart Decisions Don't Happen By Accident
Because we in the social sector have been trained to believe that smart decisions thrive on evidence, it’s easy to assume that the act of gathering evidence will make the difference between a poor decision and a wise one. Yet one of the most striking and consistent findings from research with foundations, policymakers, and nonprofits is that even when evidence is available, it is rarely used. Why is it so hard to apply evaluation and research findings to philanthropic decisions? Why does evidence so often seem to generate more questions than answers? How can social sector leaders better bridge the disconnect between knowledge and action?
Past literature on the use of evidence in philanthropy has noted several barriers to its greater adoption, including a lack of time, technical training, and political motivation among the target users. But the gap is also the result of factors relating to organizational design, misconceptions about the role and value of data, and a failure to prioritize decision-relevant questions. In this feature article from Stanford Social Innovation Review's spring 2020 issue, Julia Coffman, Tanya Beer, and I outline these less frequently acknowledged reasons why evidence so often falls short of its potential, and detail five ideas to help social sector leaders use evidence more effectively.
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Stuff You Should Know About
- In possibly the most significant policy victory of the effective altruism movement to date, a ballot initiative proposed in Zurich, Switzerland, by the Effective Altruism Foundation passed by a large majority late last year, more than doubling the city's international aid budget and introducing cost-effectiveness language for the first time into the statue. Beyond the details of the policy itself, it is also interesting to read about Switzerland's multi-stakeholder negotiating process for ballot initiatives as well as the advocates' estimate of the cost-effectiveness of their own efforts.
- The forecasting research team behind the Good Judgment Project (chronicled in the book Superforecasting and detailed in the last edition of To Be Decided) has joined up with the federal government once again for what sounds like a fascinating study on empirical interventions to improve counterfactual reasoning, "forecasting on questions that ask how history would have unfolded if some key factor or event had been different." The goal is "to develop evidence-based guidelines that any organization can use to improve its "lessons-learned" processes." You can learn more and sign up to participate as a forecaster here.
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What I've Been Reading
Brainstorming Better Options Is Key to Better Decisions
I first heard of the Heath brothers (Chip and Dan) years ago when I saw Chip speak about their first two books, Made to Stick and Switch. So I was pleased to discover they’ve written a book specifically about decision-making called Decisive. As a guide to decision-making, Decisive is most notable for its material on widening the range of choices we consider as part of that process. Research shows that most decisions we make take the form of “whether or not," with one study finding that fewer than 30% of business teams considered more than one alternative. Yet a University of Kiel study found multi-option decision processes resulted in six times as many “very good” decisions compared to single-option processes, as rated retrospectively by the decision-makers themselves. So, how do you generate more options?
(Blog post | Twitter thread)
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Deciding Well in Complex and Risky Times
Last year, I was commissioned by Democracy Fund (part of Pierre Omidyar's network of philanthropies) to develop a framework for how foundations and other social sector institutions can manage risk effectively in complex and uncertain environments. The result was "What We Should Talk About When We Talk About Risk," a white paper developed in collaboration with the foundation's Strategy, Impact, and Learning team (you can read my colleague Liz Ruedy's entertaining introduction here). The centerpiece is a set of seven principles for good decision-making that has since served as an evaluation rubric for analyzing Democracy Fund's own grantmaking process and making recommendations for improvement. We invite you to apply it to your own organization's decision-making process, especially as many of you face consequential decisions in the days ahead.
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That's all for now!
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