How Efficiency Shapes Human Language

Complexity Digest

We review recent research on the burgeoning topic of how language structure is shaped by principles of efficiency for communication and learning.
Work in this area has infused long-standing ideas in linguistics and psychology with new precision and methodological rigor by bringing together information theory, newly available datasets, controlled experimentation, and computational modeling.
We review a number of studies that focus on phenomena ranging from the lexicon through syntactic processes, and which deploy formal tools from information theory and probability theory to understand how and why language works the way that it does.
These studies show how a pervasive pressure for efficient usage guides the form of natural language and suggest a rich future for language research in connecting linguistics to cognitive psychology and mathematical theories of communication.


How Efficiency Shapes Human Language

Edward Gibson, et al.

Trends in Cognitive Science


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Power, Decision Making & Strategy in Extinction Rebellion – YouTube – Dr. Gail Bradbrook


Power, Decision Making & Strategy in Extinction Rebellion

Published on 20 Apr 2019

Dr. Gail Bradbrook – April 20th 2019 The 10 Working Principles of Extinction Rebellion https://Rebellion.Earth/who-we-are/#p… 1. We have a shared vision of change 2. We set our mission on what is necessary 3. We need a re-generative culture 4. We hopefully challenge ourselves, and this toxic system 5. We value reflection and learning 6. We welcome everyone, and every part of everyone into Extinction Rebellion 7. We actively mitigate for power 8. We avoid blaming and shaming 9. We are a non-violent movement 10. We are based on autonomy and de-centralization World Map of XR Chapters: DONATE? Join Us: https://Rebellion.Earth/contact/ Twitter: #ExtinctionRebellion Facebook:… Website: https://Rebellion.Earth Instagram:… Climate Factsheet for Rebels: https://Rebellion.Earth/the-climate-f… Rebellion Overview Document: International Signup: Southampton: Bristol: Sheffield:… Lancashire: Frome:… Glasgow: Scotland: Sweden: France: Germany: Netherlands: Denmark: Denmakr:… India: Australia: https://AusRebellion.Earth/ North Qld:… SE Qld:… NorthernRivers: NSW: VIC:… SA: WA: New Zealand:… Nelson NZ: USA:… SF Bay Area:… Sacramento:… Los Angeles:… New York:… Wash DC:… Boston: Chicago: Tampa: Central Kentucky: Savannah:… Austin: Yellow Springs:… Grand Rapids:… Minneapolis:… Colorado:… Denver:… Wyoming:… Montana:… NewMexico:… Seattle:… Eugene: Bellingham: Hawaii:… Canada:… Alberta, Canada:… Cowichan Bay, BC, Canada:… British Columbia, Canada:… Nova Scotia, Canada… Howe Sound, British Columbia, Canada:… Vancouver, BC, Canada: Ontario, Canada:… World Map of XR Chapters:

Claude Shannon: How a Real Genius Solves Problems – Medium – Zat Rana


Source: Claude Shannon: How a Real Genius Solves Problems – Personal Growth – Medium

Claude Shannon: How a Genius Solves Problems

It took Claude Shannon about a decade to fully formulate his seminal theory of information.

He first flirted with the idea of establishing a common foundation for the many information technologies of his day (like the telephone, the radio, and the television) in graduate school.

It wasn’t until 1948, however, that he published A Mathematical Theory of Communication.

This wasn’t his only big contribution, though. As a student at MIT, at the humble age of 21, he published a thesis that many consider possibly the most important master’s thesis of the century.

To the average person, this may not mean much. He’s not exactly a household name. But if it wasn’t for Shannon’s work, what we think of as the modern computer may not exist. His influence is enormous not just in computer science, but also in physics and engineering.

The word genius is thrown around casually, but there are very few people who actually deserve the moniker like Claude Shannon. He thought differently, and he thought playfully.

One of the subtle causes behind what manifested as such genius, however, was the way he attacked problems. He didn’t just formulate a question and then look for answers, but he was methodological in developing a process to help him see beyond what was in sight.

His problems were different from many of the problems we are likely to deal with, but the template and its reasoning can be generalized to some degree, and when it is, it may just help us think sharper, too.

All problems have a shape and a form. To solve them, we have to first understand them.

Build a Core Before Filling the Details

The importance of getting to an answer isn’t lost on any of us, but many of us do neglect how important it is to ask a question in such a way that an answer is actually available to us.

We are quick to jump around from one detail to another, hoping that they eventually connect, rather than focusing our energy on developing an intuition for what it is we are working with.

This is where Shannon did the opposite. In fact, as his biographers note in A Mind at Play, he did this to the point that some contemporary mathematicians thought that he wasn’t as rigorous as he could be in the steps he was taking to build a coherent picture. They, naturally, wanted the details.

Shannon’s reasoning, however, was that it isn’t until you eliminate the inessential from the problem you are working on that you can see the core that will guide you to an answer.

In fact, often, when you get to such a core, you may not even recognize the problem anymore, which illustrates how important it is to get the bigger picture right before you go chasing after the details. Otherwise, you start by pointing yourself in the wrong direction.

Details are important and useful. Many details are actually disproportionately important and useful relative to their representation. But there are equally as many details that are useless.

If you don’t find the core of a problem, you start off with all of the wrong details, which is then going to encourage you to add many more of the wrong kinds of details until you’re stuck.

Starting by pruning away at what is unimportant is how you discipline yourself to see behind the fog created by the inessential. That’s when you’ll find the foundation you are looking for.

Finding the true form of the problem is almost as important as the answer that comes after.

Harness Restructuring and Contrast

In a speech given at Bell Labs in 1952 to his contemporaries, Shannon dived into how he primes his mind to think creatively when addressing things that are keeping him occupied.

Beyond simplifying and looking for the core, he suggests something else — something that may not seem to make a difference on the surface but is crucial for thinking differently.

Frequently, when we have spent a lot of time thinking about a problem, we create a tunnel vision that rigidly directs us along a singular path. Logical thinking starts at one point, makes reasoned connections, and if done well, it always leads to the same place every time.

Creative thinking is a little different. It, too, makes connections, but these connections are less logical and more serendipitous, allowing for what we think of as new thinking patterns.

One of Shannon’s go-to tricks was to restructure and contrast the problem in as many different ways as possible. This could mean exaggerating it, minimizing it, changing the words of how it is stated, reframing the angle from where it is looked at, and inverting it.

The point of this exercise is simply to get a more holistic look at what is actually going on.

It’s easy for our brain to get stuck in mental loops, and the best way to break these mental loops is to change the reference point. We are not changing our intuitive understanding of the problem or the core we have identified, just how it is expressed.

We could, for example, ask: What is the best way to solve this? But we could also ask: What is the worst way to solve this? Each contains knowledge, and we should dissect both.

Just as a problem has forms, it also has many shapes. Different shapes hold different truths.

Multiply the Essence of Every Input

While it’s important to focus on the quality of ideas, it’s perhaps just as important to think about the quantity. Not just concerning total numbers but also how you get to those numbers.

To solve a problem, you have to have a good idea. In turn, to have a good idea, it’s often the case that you have to first go through many bad ones. Even so, however, throwing anything and everything at the wall isn’t the way to do that. There is more to it than that.

During the Second World War, Shannon met Alan Turing, another computer science pioneer. While Turing was in the US, they had tea almost every day. Over the years, they continued to keep in touch, and both men respected the other’s thinking and enjoyed his company.

When discussing what he thinks constitutes genius, Shannon used an analogy shared with him by Turing, from which he extrapolated a subtle observation. In his own words:

“There are some people if you shoot one idea into the brain, you will get a half an idea out. There are other people who are beyond this point at which they produce two ideas for each idea sent in.”

He humbly denied that he was in the latter category, instead putting people like Newton in there. But if we look beyond that, we can see what is at play. It’s not just about quantity.

Every input has a particular essence at its core that communicates a truth that lies behind the surface. This truth is the foundation for many different solutions to many different problems.

What Shannon is getting at, I suspect, is that generating good ideas is about getting good at multiplying the essence of every input. Bad ideas may be produced if you get the essence wrong, but the better you identify it, the more effectively you’ll be able to uncover insights.

Doubling the output of your ideas is the first step, but capturing the essence is the difference.

All You Need to Know

Much of life — whether it’s in your work, or in your relationships, or as it relates to your well-being — comes down to identifying and attacking a problem so that you can move past it.

Claude Shannon may have been a singular genius with a unique mind, but the process he used isn’t out of reach for any of us. His strength was in this process and its application.

Good problem-solving is a product of both critical and creative thinking. The best way to combine them is to have some process in place that allows each to shine through.

Thinking patterns shape our minds. The goal is to have the right thinking patterns doing so.

Comments and discussion in source: Claude Shannon: How a Real Genius Solves Problems – Personal Growth – Medium

Action Learning – Introduction by Reg Revans – YouTube

Action Learning – Introduction by Reg Revans

Published on 22 Nov 2012

Professor Reg Revans explains the philosophy, origins and applications of Action Learning in archive footage from 1984. Over the years, the theory and practice of Action Learning has developed – this film provides a clear statement of where it all began. (DVD running time: 18 mins 50 secs. PAL and NTSC formats available). Excerpt from a film by Joanna Kozubska, available as a DVD from IFAL (International Foundation for Action Learning). Visit “Resources’ to download an order form.

On the spatiotemporal extensiveness of sense-making – Laura Mojica and Tom Froese, April 2019

Dr. Tom Froese

The battle over the spatial extensiveness of mind has pretty much been won in recent debates in cognitive science. Here we argue that the next step is to defend the temporal extensiveness of mind!

On the spatiotemporal extensiveness of sense-making: Ultrafast cognition and the historicity of normativity

Laura Mojica and Tom Froese

The enactive approach conceives of cognition as acts of sense-making. A requirement of
sense-making is adaptivity, i.e., the agent’s capacity to actively monitor and regulate its own trajectories with respect to its viability constraints. However, there are examples of sense-making, known as ultrafast cognition, that occur faster than the time physiologically required for the organism to centrally monitor and regulate movements, for example via long-range neural feedback mechanisms. These examples open a clarificatory challenge for the enactive approach with respect to how to operationalize monitoring and regulation, and with respect to the temporal scale of sense-making, which has…

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Adaptive social learning for systemic leadership – Catherine Hobbs

Integration and Implementation Insights

Community member post by Catherine Hobbs

Catherine Hobbs (biography)

What’s involved in developing human capacity to address complexity, taking a mid- to longer-term viewpoint than is usual? How can we create the conditions in which people can cope with the daily challenges of living in a complex world and flourish? What form of leadership is required to inspire and catalyse this transformation?

Framework for adaptive social learning

The need for systems thinking is often referred to, but rarely considered, as a rich and comprehensive resource which could be developed further and applied. A critical systems thinking approach suggests that a variety of approaches should be drawn upon, in a manner of methodological pluralism, being aware of the strengths and weaknesses of different approaches and applying them adaptively using synthesis as well as analysis.

In the spirit of such an approach, I’ve developed a learning pathway for systemic…

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Mind, Body, Quantum Mechanics – Stuart Kauffman, April 2019

I’d be interested in opinions on this! V good or has he gone ‘late career’ and mystical?! 😀


Source: Mind, Body, Quantum Mechanics | SpringerLink

Activitas Nervosa Superior

pp 1–4Cite as

Mind, Body, Quantum Mechanics

  • Stuart KauffmanEmail author


I discuss the following: The causal closure of classical physics implies that consciousness in a classical physics brain can at best be epiphenomenal. Quantum mechanics can break the causal closure of classical physics in two ways: measurement and a newly discovered Poised Realm. Conscious experience may be associated with quantum measurement. Here quantum mind has acausal consequences for the classical brain. I propose genetic experiments to test this. Entanglement may solve the “binding problem.” I believe these proposals unite mind and body in a new way and answer Descartes after 350 years of the Stalemate introduced by his dualism of Res cogitans and Res extensa.


Causal closure Quantum mechanics Poised realm Mind body