In Cal Newport’s book, So Good They Can’t Ignore You: Why Skills Trump Passion in the Quest for Work You Love, of which Haden’s article is about, Cal talks about the “adjacent possible”, which is:
A term taken from the science writer Steven Johnson, who took it from Stuart Kauffman, that helps explain the origins of innovation. Johnson notes that the next big ides in any field are typically found right beyond the current cutting edge, in the adjacent space that contains the possible new combinations of existing ideas. The key observation is that you have to get to the cutting edge of a field before its adjacent possible – and the innovations it contains – becomes visible.
I felt this book was a good example of that for me because I was just about to write something similar. It seems this is possible because Cal and I both have similar reading habits and a desire to find out how to do what we love. This book builds on principals from Seth Godin, Malcolm Gladwell, Derek Sivers, Daniel Pink, and Reid Hoffman. I will admit that I was a believer in the “passion mindset” and although I thought I was a hard worker, I tended to avoid the mental strain Cal talks about that’s so important to deliberately practice in order to build career capital (these are two terms Cal introduces). This book really does a good job of turning the passion mindset on it’s head while giving you solid, practical advice about how to get the things you want in a job: control/autonomy. The bad news is that it takes a long time, will hurt, and requires a lot of work.
Talk about CIV and UFO Defense
I’m on the cusp of formulating a new way to think about intelligence
I’m thinking about this in terms of a presentation, rather than a blog post, but the general idea is that one way to measure intelligence is a person or system’s ability to cross-reference ideas.
When you were a child, you may have been asked to fill out simple logic puzzles in math class. They were simple rows and columns and a couple of sentences, which you had to fill in using logic.
Imagine if all ideas in the world occupied both all of the columns and all of the rows in a giant logic puzzle and the more ideas are learned, the more columns and rows are added to this puzzle. It is from this idea that I present the following stories.
The Rosetta Stone
Despite being discovered in 1799 by Napoleon’s troops in Egypt, it wasn’t until 1822 that a man named Champollion was able to decode the Ancient Egyptian hieroglyphs, the middle portion Demotic script.
He was only able to do this by cross-referencing not just the Ancient Greek, but also Ancient Coptic and other hieroglyphs found at that time. It was this cross-language connections that ultimately helped decrypt the language.
The First Web App
In 1995 Paul Graham, founder of Y-Combinator, wanted to write an e-commerce application, but didn’t want to write it for Windows. After seeing an advertisement for Netscape, he had an idea to try running his Unix application in a browser.
In order for Graham to create Viaweb as the first web app, Netscape, the World Wide Web, the Internet, and Unix all had to be in place first. It was from these technologies that allowed The Adjacent Possible to occur.
The Adjacent Possible
Innovation in any field are typically found right beyond the current cutting edge, in the adjacent space that contains the possible new combinations of existing ideas. The cutting edge has to exist in a field before its adjacent possible – and the innovations it contains – becomes visible.
This explains why things like the discovery of oxygen or DNA occur at the same time around the world because the tools available to do so become available. However, the existence of technology is not enough, the person has to have the intelligence to connect the pieces together.
The Wright Brothers
By the time The Wright Brothers started working on powered flight, “flight” by gliders was already a thing. The problem was not ‘lift’ – the mechanics of that were known. The problem was in maintaining flight and controlling the aircraft.
Because The Wright Brothers were avid tinkers and ran a bicycle shop, they were able to apply ideas from how a bicycle maneuvers through space and recent developments from lightweight aluminum engines to overcome powered flight.
What is Intelligence?
The ability to cross-reference ideas requires both the knowledge of the ideas and the ability to recall and compare those ideas to each other. The ability to do this as a human generally requires expert domain knowledge or the cross-pollination of ideas across domains in a more holistic view, but some level of depth is required in at least one domain.
Compare this to a computer program that could be programmed to compare ideas at a massive scale. Every time a new paper is published or a new gadget is created, the ‘rows’ and ‘columns’ get bigger and every previous idea can now be compared. The results from a computer program doing this task in a holistic way may result in ideas and outcomes that a human would never come to on their own.
Uploaded on Apr 14, 2008
Lawrence Barsalou PhD Emory University. The human conceptual system contains categorical knowledge that supports online processing (perception, categorization, inference, action) and offline processing (memory, language, thought). Semantic memory, the dominant theory of the conceptual system, typically portrays it as modular, amodal, abstractive, and static. Alternatively, the conceptual system can be viewed as non-modular, modal, situated, and dynamic. According to this latter perspective, the conceptual system is non-modular and modal because it shares representational mechanisms with modality-specific systems in the brain, such as vision, action, and emotion. On a given occasion, modality-specific information about a category’s members is reenacted in relevant modality-specific systems to represent it conceptually. Furthermore, these simulations are situated, preparing the conceptualizer for situated action with the category. Not only do these situated simulations represent the target category, they also represent background settings, actions, and mental states, thereby placing the conceptualizer in the simulation, prepared for goal pursuit. Because the optimal conceptualization of a category varies across different courses of situated action, category representations vary dynamically and are not static. Furthermore, different situations engage different neural systems dynamically when representing a category. Under some circumstances, the linguistic system plays a more central role than simulation, whereas under other circumstances, simulation is more central. Thus, the concept for a category appears to be a widely distributed circuit in the brain that includes modality-specific and linguistic representations, integrated by association areas. Across situations, these circuits become realized dynamically in diverse forms to provide the knowledge needed for cognitive processing. Behavioral and neural evidence is presented to support this view. Learning Sciences Institute