In fact, both Covid Optimists and Pessimists are right
Filter loops are harder asymmetry how we view information and how to incorporate it into our behavior as individuals. Optimists can update their information optimistic update bias (on the way to taking more risks). Pessimists may be more at risk even if presented with a “positive” model. This is no different confirmation bias. It also depends on our behavior epistemic confidence: whether we decide to trust an expert prediction to change our opinion and behavior enough. This was created recently opposite back controversial article in Atlantic, written by an economist, on the risks of transmission of Covid-19 in children.
Science, and specifically epidemiology, is concerned with measurement and truth. Specific models are important. But at point A, if a group of people hears the worst case / pessimistic / precautionary principle model, the probability of the worst case may occur. shrink as a result of a change in team behavior to reduce risk. The opposite is also true: At the same point, if a group of people hears a “dynamic causal” / optimistic model and changes to more liberal behavior, the pattern changes. in the direction worst case.
“The pandemic forecast is similar to the weather forecast, as the 10-day outlook is good, but I can’t tell you what the weather will be like in the third week of July,” Lessler told me. In the case of infectious diseases, “we can’t say what will happen three months from now, because we have loops to give opinions on politics and behavior and uncertainty in the data behind it.”
Let’s go back to J: In situation 1 he may decide to take this pessimistic model as a push to stop smoking. The opposite can happen in situation 2. Ideally, his doctor would share both projections, and it would be up to J to measure both options.
Public health is more difficult because the decisions made by individuals are the consequences of influencing their community. Arguably, it is better to be poorly prepared and careful, as millions of lives are at risk, even if they are important to individual freedoms and externalities to the economy and affect the impact of our options and risk.
Here’s the good news: Over time, they could be optimistic and pessimistic predictive models Appear to converge. So the dynamic scenario and cause models are somehow correct: In general and gradually, we tend to make more accurate predictions along. This suggests that when the number of cases decreases, the patterns will be similar to each other, which indicates the end of the pandemic or simply a reflection of it. Lessler later shared in an email: “All models reach a very low case destination. It’s just a matter of telling them how long and what’s going on along the way.”
Thus, a more “pragmatic” approach, one that favors the constant use of masks, vaccines, and social distances, can best deliver the optimism of herds and a positive outcome to return to a more pleasant “normal” life this year.
When I did a Twitter survey earlier this month, more than two-thirds The more optimistic opinion of about 700 respondents seemed to be that the end of the pandemic in North America is near. I calmed down at first, but then I realized that this approach could lead to a more pessimistic outcome if the same optimism ordered more prudent behavior. Instead, it balances evidence-based prudence pessimism in the present, with the idea that this might lead to reason optimistic In the future, it may be best to promise behavior so you can get out of this together, like others you seem. Which is another way to summarize the writer Ezra Klein recently tweet: “Hope has been an insecure emotion lately. Personally and professionally, I don’t want to be optimistic about oppression as deaths go up. Pessimism is safer.”
Perhaps the healthier dose of pragmatism, tolerance of change and uncertainty, is even safer.
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