Tag: Chaos

12 Rules

Here’s a set of “12 Rules for Life” that highlight potential contradictions or loopholes in Jordan Peterson’s philosophy, offering an alternative set of guiding principles:

  1. Don’t Pretend Order is Always the Answer: While Peterson emphasizes order, life’s complexity often demands flexibility. Embrace uncertainty and don’t force rigid structures onto situations that require fluidity.
  2. Stand Up for Yourself, Even if It Means Disrupting the Peace: Peterson advises standing up straight with confidence, but real courage sometimes requires challenging the status quo, even if it causes discomfort.
  3. Treat Yourself Like Someone You Can Afford to Disappoint: Peterson encourages treating yourself with care, but sometimes it’s okay to fall short of your own expectations. Self-compassion includes accepting your flaws.
  4. Make Friends Who Challenge You, Not Just Those Who Support You: Instead of only associating with people who want the best for you, also engage with those who question you, as they often provide the most growth.
  5. Compare Yourself to Who You Want to Be, Not Who You Were Yesterday: While self-comparison can be useful, aim for aspirational goals rather than dwelling on small, incremental changes.
  6. Pursue What’s Intrinsically Valuable, Not Just What’s Meaningful: Meaning can sometimes be subjective or imposed by society. Focus on what feels genuinely valuable to you, even if it seems trivial to others.
  7. Tell the Truth, but Acknowledge the Power of Strategic Silence: Honesty is important, but there are times when silence or withholding information can protect others or yourself.
  8. Assume Responsibility for Your Choices, but Recognize When to Delegate: While taking responsibility is vital, understand your limits and the importance of sharing burdens with others.
  9. Speak Your Truth, Even if It’s Unpopular: Instead of just listening, assert your perspective, especially when it goes against the grain. Your voice matters, even in dissent.
  10. Be Precise in Your Actions, Even When Words Fail You: Precision in speech is valuable, but actions often speak louder. Focus on how you behave rather than getting lost in the minutiae of language.
  11. Encourage Risk-Taking in Safe Spaces: Instead of just leaving kids to skateboard, create environments where risks can be taken with safety nets in place. Growth comes from pushing boundaries, but there’s wisdom in knowing when to protect.
  12. Find Beauty in the Mundane, Not Just in Moments of Crisis: Instead of seeking solace in life’s darkest moments (like petting a cat on the street), cultivate appreciation for everyday beauty and simplicity, without waiting for things to go wrong.

These rules aim to address the nuance that Peterson’s principles sometimes overlook, acknowledging the complexity of life where contradictions and exceptions are often the rule.

Complicated, Complexity, Chaos

Leave a comment

WHAT DOES COMPLEXITY MEAN?

Science has progressed, at least beginning with the physical sciences, by always being reductionistic: that is, reducing things to their primary elements, whether they’re electrons, atoms, molecules, or genes and so forth. That has been enormously successful, but one of the things that we’ve begun to appreciate more and more is that kind of paradigm has extraordinary limitations.

When you try to build up from these fundamental elements to the collective whole, you discover that the whole is much greater than, behaves differently than, and is structured differently from the sum of its parts. What you recognize in parallel with that is almost all of the major issues that we face on the planet — everything from climate change and the question of stability in markets to potential questions about risk and how we deal with things like cancer, and the encroaching threat of global urbanization — are what we call complex. They’re not easily, or even potentially, reduced to the sum of their parts.

For example, organisms like you and I are much more than the sums of our cells or genes. A city is much more than the sum of all its people or roads and businesses. Furthermore, all of these are not just conglomerations of all of these things: They’re all highly dependent upon one another. There’s what we call express emergent properties: New things emerge as you build these systems up, whether they are economies, climates, cities, or our bodies.

The Critical Difference Between Complex and Complicated

(…) A typical complex system is composed of myriad individual constituents or agents that once aggregated take on collective characteristics that are usually not manifested in, nor could easily be predicted from, the properties of the individual components themselves. For example, you are much more than the totality of your cells and, similarly, your cells are much more than the totality of all of the molecules from which they are composed. What you think of as you — your consciousness, your personality, and your character — is a collective manifestation of the multiple interactions among the neurons and synapses in your brain.

In general, then, a universal characteristic of a complex system is that the whole is greater than, and often significantly different from, the simple linear sum of its parts. In many instances, the whole seems to take on a life of its own, almost dissociated from the specific characteristics of its individual building blocks (…)

West, Geoffrey. Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies (p. 23). Penguin Publishing Group. Kindle Edition.

A car is complicated, traffic is complex. You can build a car or repair it, but you have to manage traffic. You can achieve full visibility of a complicated system but not of a complex one. That’s why rules can be used with the former but not with the latter.

“Things are complicated”

It isn’t that things are complicated, because complicated is to be distinguished from complex. Let us have a couple of examples.

One of the great successes in the development of science was understanding the motion of the planets. Newton’s laws of gravity and motion and so on set the template of everything we do. Newton’s laws explained all of that, which was fantastic. This reductionistic and simplistic — that is to say it’s not complex — explanation was very profound. Your cellphone wouldn’t work if we didn’t understand all of that with great accuracy, since we use satellites to send our messages.

To do that in detail, to understand it in the detail that it is needed to make technology like this work, we need to put in all of the various little corrections that occur to Newton’s laws due to things like the atmosphere and things like satellites that may have deviated slightly because of an asteroid and so forth, and all of that gets complicated. That’s complicated.”New things emerge as you build these systems up, whether they are economies, climates, cities, or our bodies.”TWEET THIS QUOTE

The other example would be the building of an airplane. We understand in detail and in great depth the physics and material sciences of flight — the engineering and math involved. In that sense, an airplane is a simple system: We can describe it with a relatively small set of equations or algorithms. It’s extremely complicated, potentially, if you try to build a Boeing 787. It is very complicated, but nothing in principle will stop you from doing it. I think there are two great big manuals at Boeing that tells you how to build the 787, the Dreamliner. It’s how they carry it out. You cannot imagine manuals for knowing how your body, or New York City, or the stock market works.

Complicated systems require expertise in their management, but as long as the proper expertise is available and used, the attractiveness of complicated systems is that they generally can be successfully managed. Complicated thinking leads Peoples to think that they are doing something purposeful when in reality they are not, and in fact they are likely doing more harm than good. Complex systems are nuanced and require a nuanced approach. The one thing that will not work is a rigid, rules-based, complicated approach.

While it is not necessary to be a genius to manage complexity, it is helpful to consider for a minute the difference between a genius and someone who is really smart. The reality is that Einstein thought differently. A little-known fact is that most of his mathematical problems were solved by others, including an assistant, Walther Mayer, who solved many of the mathematical equations and did most of the calculations that Einstein’s musings required. Einstein was a complexity thinker, while Mayer was a very good and very intelligent complicated thinker.

When we go to these complex systems — when you think along the lines I’ve elaborated on — you conclude that to get a quantitative, predictive understanding of them is, in principle, impossible if you insist on getting into great detail. This is where I come in.

SCALING LAWS

There is, potentially, an in-between place where we may not have a theory for the way the system works in infinite detail, but Geoffrey west, has shown that you generally can get what physics calls a “coarse grain description”: an understanding of the idealized, average behavior of these systems, and maybe even more than that — how they deviate from various things and so forth. That’s what the scaling laws represent. They show that if you tell me the size of a mammal — its mass, how much it weighs. I can tell you to 80 or 90 percent accuracy how much food it needs to eat a day, how fast its heart beats, how long it is going to live, the length and radius of the fifth branch of its circulatory system, the flow rate of blood of a typical capillary, the structure of its respiratory system, how long it needs to sleep and so on.

You can answer all of these kinds of systems for the average idealized mammal of a given size, and it will be correct to an 85 or 90 percent level. I can predict the metabolism of an elephant, for example, but give me a specific element and I won’t be able to tell you exactly what the metabolic rate is. By metabolic rate, I mean that in colloquial terms: How much it is going to need to eat each day. To bring it closer to home, one can roughly predict the lifespan of a mammal of a given size, and in particular where this life span of a hundred years come from. I can tell you what the parameters are that control that, but I won’t be able to tell you detail how long you’re going to live.

ze the whole, we must accept the sub-optimality of the parts”