I think the failures of the pandemic have exposed some cognitive biases in the science community.
We overestimate how much people care about avoiding death
We overestimate how much people care about other people
We overestimate how much people trust scientists
The main reason I think it must be some kind of cognitive bias is we seem to be having trouble absorbing this information no matter how much evidence we see for it.
I think the public has cognitive biases about scientists as well:
They underestimate how much we care about truth and our reputations as truth tellers
They overestimate how much we care about money and political power
They underestimate how much we care about others
This is why I think science outreach is so important. It’s not just a way to teach people cool facts about the world. It’s a way to teach people about scientists and the science community and reduce misunderstanding.
If people don’t know who we are, they aren’t going to trust us.
It’s also important that people in the science community understand the needs and preferences of the communities who fund our quests for truth.
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If free speech means anything, then we ought to be able to use our voices to engage in rational debate, but also to be annoying or silly or frivolous, or to say the truth about how we really feel about others, even if it hurts feelings or damages reputations.
In this context, Joe Rogan should be able to say anything he wants even the n-word, but others should also be free to use their voices to impose a reputational cost on him and on Spotify for their odious speech.
Freedom of speech and freedom of association go hand in hand. People should be free to disassociate themselves from Rogan and from Spotify, not just because of what they say, but because of where they stand. We get to choose whom we stand with.
I get why the lab leak hypothesis is of geopolitical interest, but I don't get how it's important scientifically.
The question for me isn't "did covid come from a lab?" but rather, "is there anything about the severity of covid that's unique to a possible lab origin"?
If there isn't anything about a lab origin that could have contributed especially to covid's severity, then digging into a potential lab origin feels like a waste of time and goodwill, fighting over who to blame for the current crisis instead of working to avoid the next one.
And for what? I think there's a good chance that any evidence in that direction would be extremely messy and circumstantial, convincing to China's geopolitical rivals and unconvincing to its friends.
Very interesting take from @StatModeling :
“The social sciences are useless. So why do we study them?”
He argues that the main benefit of good social science research is to push back against the bad social science that people would otherwise do.
I’m sympathetic to this argument. Social science does provide a strong pushback to amateurish analyses of race and gender related data for instance which are very common on social media.
I think sometimes people are little too quick to claim that based on FACTS and LOGIC other people's risk preferences don't make sense.
For instance, I frequently see the claim that it's hypocritical or unreasonable to be willing to participate in a high-risk activity but then not be willing to participate in other lower risk activities.
The idea seems to be that a fully rational person would have some kind of fixed risk threshold. Below the risk threshold, the person would be willing to participate in the activity assuming it's something they find worth doing. Otherwise, they would decline.
Never confuse "sensitivity" and "specificity" again!
Here's how I keep them straight. 👇
First some background. There are four categories of test results:
[Skip this tweet if you already know this part!]
TP: Tested positive, Infected
FP: Tested positive, Uninfected
FN: Tested negative, Infected
TN: Tested negative, Uninfected.
Sensitivity is how "sensitive" the test is meaning "does it pick up all the cases?" What's another name for the cases detected by the test? The true positives! Therefore, another name for the sensitivity is the *true positive* rate. It's the percent of cases detected by the test.
Your rapid test is positive. Does that mean you have covid?
Here's the math you need to figure it out. A thread. 🧵
Let's define some terms that you might have heard of.
A "true positive" means the test result was positive and the person tested does indeed have covid.
A "false positive" means the test was positive but the person doesn't have covid.
A "true negative" means the test was negative and the person tested doesn't have covid.
A "false negative" means the test was negative but the person does have covid.
Got it? Good!