Chapter 2 - How the Wicked World Was Made
What is the purpose of the Blueprint?
Many services provide summaries of books to make them more digestible. But digestible doesn't mean useful. For this reason, this Blueprint outlines critical themes and topics for you to apply in your life.
We are not limited to only text. We can cite sources beyond the book, pulling videos and other forms to explore ideas shared here. In short, you can take any idea, double-click on it, and explore as you see fit.
This won't diminish the need for the book. The book serves as a foundation for our exploration, and what I take away may not be what you will. Get reading!
The First Book: Range by David Epstein
David Epstein examined the world’s most successful athletes, artists, musicians, inventors, forecasters, and scientists. He discovered that generalists, not specialists, are primed to excel in most fields—especially those that are complex and unpredictable. Generalists often find their path late, and they juggle many interests rather than focusing on one. They’re also more creative, more agile, and able to make connections their more specialized peers can’t see.
Who should read this?
All books have a thesis they attempt to answer, and Range's subtitle gives away the thesis right on the cover!
Why generalists succeed in a specialized world?
If the quote," jack of all trades, master of none." resonates with you, this book will fascinate you. Or if you are curious, you might berate yourself for having too many interests. The book is about being broadly curious to solve problems more effectively.
You can get an offline PDF version of the blueprint to support our work here!
If you missed Range Ch. 1 - The Cult of the Headstart you can start there here!
Chapter 2 - How the Wicked World Was Made
I want to start this section by defining a key term from this chapter:
The Flynn Effect is the increase in correct IQ test answers with each new generation in the twentieth century.
Differences between premodern and modern thinking
The differences between premodern and modern thinking. Premodern is defined as people that live in remote villages or as farmers and are characterized by little contact with the outside world.
'The greater the does of modernity, the more likely an individual grasped the abstract concept of "shapes"...' Further elaboration on the conceptual groupings: "No amount of cajoling, explanation or examples could get remote villagers to use reasoning based on any concept that was a concrete part of their daily lives."
To complete a picture here, "premodern people miss the forest for the trees: modern people miss the trees for the forest." As people move closer to modernity, their abstract thinking becomes more powerful. They don't have to rely on direct experiences as much.
We now see the world with "scientific spectacles". We can see the world in a wide variety of categories. We can group and regroup objects or thoughts rapidly with flexible frameworks. The problem lies in our modern education system that pushes specialization rather than transferable knowledge. From Flynn: "The traits that earn good grades at [at the university] do not include the critical ability of any broad significance." and "There is no sign that any department attempts to develop [anything] other than narrow critical competence."
Develop a scientific-reasoning Swiss Army Knife
Jeannette Wing is a computer science professor at Colombia University and former corporate vice president of Microsoft Research. She has pushed broad "computational thinking." Computational thinking is a set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. It involves the mental skills and practices for designing computations that get computers to do jobs for people. Computational thinking helps to explain and interpret the world as complex information processes.
The most important takeaway here is that one useful tool is rarely enough to fit all situations we may encounter. The world is complex, interconnected, and always changing so should our tools.
Fermi Problems
Fermi problems can also be called order estimation. This thinking is used for estimation problems designed to teach dimensional analysis or approximation of extreme scientific calculations. Such a question is usually a back-of-the-envelope calculation.
This skill seems like magic on the surface. But at its core, it’s about making guesses without real data in front of you. The thing about these guesses is that they are grounded within the reality of the question being asked. This skill is one major advantage for those with broad experience as they will be able to make these inferences with less time to work to a ballpark answer.
Here is a framework to apply Fermi Estimations:
1. Break down the problem
2. Throw out some numbers
3. Bound the problem
4. Sanity Check
Examples of Fermi Questions can be found from the University of Michigan!
Trivia: These problems are named after Enrico Fermi, physicist and the creator of the world's first nuclear reactor.
Now the question moves if we can apply and learn broad knowledge, are there examples of a skilled group that has done this?
