WHY IS IT SO HARD TO KNOW WHAT TO DO FOR THANKSGIVING 🦃 THIS YEAR AND WHY DON'T WE ALL AGREE? A data analyst's perspective. Thread. 🧵
MANAGING CORONAVIRUS RISK IS HARD BECAUSE IT'S NOT JUST ABOUT THE SCIENCE. Don't get me wrong. It's not completely unrelated to the science either. It's in between. Why? Because it requires us to answer questions that are unanswerable by science alone. Questions like...🧵
1. WHAT'S AN ACCEPTABLE RISK? SCIENCE can't decide this for us. Logic can give us a guide for defining our risk preferences so that they're consistent. For instance, if I'm afraid of LESS risky stuff than coronavirus, it's illogical for me not to fear coronavirus as well.
Additionally, if I already have a more risky lifestyle than I want, I should rationally want to avoid the additional risk of coronavirus. Unfortunately, logic can only go so far. It can't tell me how much risk is worth the benefits of freely living my life. That's up to me.
2. WHAT ARE THE COSTS AND BENEFITS TO YOU? The costs and benefits of our decisions are specific to us and our situation. A mathematical modeler can't know what your life is like, but if they know your perception of the costs and benefits, modelers can put that into their models.
3. HOW MUCH DO YOU CARE ABOUT COSTS AND BENEFITS TO OTHERS? How much do you care about other people? Would you be willing to give up $100 of benefit if another person got $101 of benefit. What if it was only $99. What's the right level of trade-off? The answer is personal to you.
4. ARE YOU CONCERNED ABOUT COLLECTIVISM VS AUTONOMY? Would you prefer a plan that tries to get the best outcome for the group or just for you personally? Do you favor working with others to achieve common goals or does that sound like COMMUNISM to you? This is a personal choice.
5. WHOM DO YOU TRUST? This can determine what EVIDENCE you consider to be relevant evidence for making your decision. Most of us don't want to use data from untrustworthy sources. It's biased to exclude evidence AFTER you hear what the data says...
...but it's not necessarily biased to have prior criteria for what data you consider valid. Scientific knowledge can help with defining logical exclusion criteria but these criteria will always be a personal, subjective choice.
THESE DECISIONS HAVE TO BE MADE before we can objectively analyze available data and make the best decision. In order for experts to advise the public, they must make assumptions about the right answers to these questions. These assumptions affect their advice.
Sometimes the answers are based on their personal knowledge of the preferences of the end users of the advice. Sometimes the answers come from their personality or their politics. In my opinion, the general public isn't dumb at all to be skeptical of expertise.
The public is discerning enough to tell that there's a gap between their decision-making preferences and the preferences of the average expert. Unfortunately, as a society, we rarely do the work to translate the science into a form that respects individual-level preferences.
This might be because it's a vastly harder problem to re-engineer a system of simple top-level rules like "wash your hands" and "stand six feet apart" into a personalized rule set for each of the 7 billion humans globally.

I think we might need an app for that.

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More from @kareem_carr

4 Oct
Don't know what a P-VALUE is?

Don't know why P-VALUES work?

Don't know why sometimes P-VALUES don't work?

THIS IS THE THREAD FOR YOU. 🧵
DEFINITION OF A P-VALUE. Assume your theory is false. The P-VALUE is the probability of getting an outcome as extreme or even more extreme than what you got in your experiment.
THE LOGIC OF THE P-VALUE. Assume my theory is false. The probability of getting extreme results should be very small but I got an extreme result in my experiment. Therefore, I conclude that this is strong evidence that my theory is true. That's the logic of the p-value.
Read 11 tweets
3 Oct
Statisticians like me say CORRELATION ISN'T CAUSATION but that's not the whole story.

There are at least FOUR different scenarios!

A thread. 🧵
1. CORRELATED BY CHANCE. There's always a possibility that variables will correlate by chance. If you have a lot of data, you're almost certain to get a few high correlations. You will know you're in this situation if the same variables are much less correlated in new data.
2. CORRELATED DUE TO STRUCTURE. Clocks are correlated with each other but there's nothing about Clock A that can be changed in order to cause a change in Clock B or vice versa. There is no third thing you can change that will cause both clocks to change. There is no causation.
Read 8 tweets
30 Sep
The reason machine learning algorithms show bias is that the goal of these algorithms is to learn ALL the patterns in the data including the biases. The "bias" is actually the gap between what the data scientist THINKS is being learned and what's actually being learned. 🧵
An interesting feature of this bias is it's subjective. It depends on what the data scientist INTENDED to learn from the data. For all we know, the data scientist intended to learn all the patterns in the data, racism and all. In which case, there is no bias.
Generally, machine learning does not require us to be specific about what patterns we are trying to learn. It just vaguely picks up all of them. This means we often have no clue what was learned and if it is what we intended to learn.
Read 8 tweets
28 Sep
One of my most strongly held political beliefs is experts shouldn't rule over non-experts without their consent. I won't try to define for you who exactly the "experts" are because in my world it doesn't matter. Everybody can make that decision for themselves.
Depending on how we define "expert", the intelligent shouldn't rule over the unintelligent. Academics shouldn't rule over non-academics. Intellectuals shouldn't rule over non-intellectuals. The old and wise shouldn't rule over the young and foolish. I mean all of these things.
I believe in expertise without authority. For this reason, I don't really want to be associated with forcing people to wear masks. I'd prefer people do it because they trust health experts and if they don't, it's something between them and the governments which they elected.
Read 10 tweets
26 Sep
WHAT I SAID WAS "Scientific knowledge is socially constructed" BUT SOME PEOPLE HEARD "Scientific truth is a social construct". For me, there is a difference!
When you tweet things out to 45k people, you learn a lot about the difference between what you think you said and what people hear.
I now understand that some percentage of people are hearing me say "Scientific truth is a social construct" whenever I say "Scientific knowledge is socially constructed". I think both are true but that's not the whole story. Let me explain.
Read 15 tweets
26 Sep
Some folks think "Objective reality exists" is a good counterargument to "Science is socially constructed". It's not and here's why ...
The more I argue with folks about how "science is socially constructed", the more obvious it is to me that the people disagreeing with me are simply saying "Objective reality exists" (which I agree with but they seem to think I don't.)
Over and over again, they restate that reality is indeed real. Although this requires philosophical arguments to defend, they tend not to make any. Perhaps this is because messing with philosophy is how we get statements like "science is socially constructed" in the first place.
Read 10 tweets

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