Only three chapters into @CharlesCMann's *The Wizard and the Prophet* and why didn't anyone insist that I read this book before? Super-relevant to progress studies.
Just finished the Borlaug chapter, which is jaw-dropping, even though I already knew the Borlaug story in outline.
The sheer amount of hardship Borlaug endured, the setbacks, the lack of support from almost everyone around him, the tedium of crossing thousands of varieties and planting them by hand… all to save the world's hungry. Someone needs to make a movie out of this.
Seriously, there are so many great scenes. Usually science is hard to make dramatic on the big screen, but this would be fairly easy.
Like this scene where he has no equipment and no one will lend him any, so he literally pulls the plow through the field himself, like a mule:
Or this scene, where he thinks he has lost all the seeds from one variety, and then he finds a forgotten envelope with seeds in it.
This is better writing than you find in many major films
Borlaug is a good litmus test for whether you actually care about humanity. He grew up poor, labored in the fields, never took a big salary, saved maybe ~1B people from starvation in Mexico, India, Pakistan, etc, and won a Nobel Peace Prize for it.
This image gets posted a lot lately, and not everyone knows what it means.
It's a reference to “survivor bias”: a statistical problem in which a sample is non-representative because some elements have been eliminated before the sample was taken. Here's a brief explainer.
The story: You're Britain. It's WW2. Your planes are getting shot down. You want to reinforce them with armor. But you can't armor the whole plane (for weight among other reasons).
What parts of the plane do you prioritize for armor?
Your researchers collect data on where your planes are getting shot. Whenever a plane returns from a mission, they note where they found bullet holes. This diagram shows all the holes that were found across many missions.
If you want a single, vivid, and frankly disgusting example to hold in mind to remember how much our lives have improved over the last ~150 years…
Consider *shit*.
Literally, excrement. How much previous generations had to think about it, be around it, even handle it:
Before the automobile, horses flooded the streets, and cities were mired in their muck. According to Richard Rhodes, in NYC, horses dropped 4 million pounds of manure and 100 thousand gallons of urine on the streets every *day*. (!)
And Robert Gordon quotes this passage from *The Horse in the City*. “On New York’s Liberty Street there was a manure heap seven feet high.”
Shoveling shit was literally a full-time job. And one of the key uses of horses was to pull the wagons that carried away horse droppings.
A similar thing happened during the smallpox eradication program: a new applicator device, the “bifurcated needle”, used 1/4 the vaccine, and thus 4x'ed the supplies.
Close-up of a bifurcated needle, holding a drop of smallpox vaccine.
D. A. Henderson, who led the eradication program, made an award for his team called the “Order of the Bifurcated Needle.” His daughter made a patch showing the points of the needle bent into a zero.
Today Google @DeepMind announced that their deep learning system AlphaFold has achieved unprecedented levels of accuracy on the “protein folding problem”, a grand challenge problem in computational biochemistry.
I spent a couple years on this problem in a junior role in the early days of @DEShawResearch, so it's close to my heart. DESRES (as we called it internally) took an approach of building a specialized supercomputing architecture, called Anton:
Proteins are long chains of amino acids. Your DNA encodes these sequences, and RNA helps manufacture proteins according to this genetic blueprint.
Proteins are synthesized as linear chains, but they don't stay that way. They fold up in to complex, globular shapes.
Many people don't know that in scientific jargon, “predict” and “explain” are *also* not causation. They are forms of correlation.
These terms can cause extreme miscommunication.
(Technically, “association” might be a better term than “correlation”, which can have a narrower technical meaning in statistics. But since I'm writing this for non-experts, I'm going to use the term “correlation” in the colloquial, wider sense.)
In lay usage, “X predicts Y” implies that X comes *before* Y. Predictions are about the future.
In statistics, there is no time implication at all. It is just a type of correlation.