Money

February 2016

This is an attempt to clearly explain what money is, how it does what it does, why it has been so necessary and so useful in our past, and why it is becoming so dangerous to our future.
This is not a thorough examination of the many subtleties of money creation by declaration and by many types of credit, or an exploration of the many subtleties of the roles of finance. This simple acknowledgement of that complexity is all you will find here. And what you will find here makes most of the subtleties of finance redundant.

There will be many ideas introduced here.
Some of these ideas will be complex.
Do not expect to remember all of the ideas, and if you can get a sense of how they might work, then that is all this is about.
Becoming familiar with any idea requires repeated exposure in many contexts, and using that idea in new ways in new contexts. Reading this wont give you that, and it should allow anyone who can read to get the basics of the major concepts involved in money, and the major benefits and dangers it delivers to us all.

Money has evolved over time, as most things do.
It can be hard to see the relationship between a cave, and a modern sky scraper, yet both are dwellings, places that people shelter from the weather and other dangers, and when one looks at history, one can see gradual transitions from one to the other.

Money has been like that too.

The simplest and most important function of money is as a medium of exchange.
If you want something that Fred has, but Fred doesn’t want anything that you have, but George wants something that you have, but you don’t want what George has, then it is very useful to have something around that everyone agrees is valuable and useful, and can act as a medium of exchange.
If we call that thing money, then you can give your stuff to George for money, then give your money to Fred for what you want.
That is all simple in a sense.

In history many things have served this intermediary role.
It is useful if the thing serving the role is hard to counterfeit, is limited in supply, and has a long life.
In some societies rare bird feathers worked, in others rare sea shells.
In more modern times rare metals took on the role. Some used gold (a very stable and reasonably rare metal), some silver, some copper, some groups used all three.

In a very real sense, it doesn’t matter what is used.
All that matters is that it is hard to produce and thus the supply is limited in some manageable way.

When gold was in use, rich people found that it was dangerous to carry large quantities of gold or silver around, as it was easy for those with very little to steal it. If you were lucky they only took your gold, but often they also killed everyone, to reduce the risk of being identified.

Thus traders developed trust networks, of people in major centres, with well guarded vaults containing gold, silver, copper and other valuables, and they would send notes to each other, under seals in wax (to prevent forgery), that promised exchange of so much gold and silver etc at some future date.
This trading of promissory notes was the beginning of the banking industry.

It didn’t take long for the people in charge of these stores of value to figure out that they could create more promissory notes than they had gold or silver, provided that they always had enough gold or silver to actually pay out all the notes that came in.
This is one form of credit.
In this way, the amount of money in circulation could expand, and provided everyone didn’t show up on the same day demanding their gold, the banks got away with it.

Another thing the banks did was to accept title to property that had a reasonably consistent value in the market, and to issue money against such title.
Thus, you could take the title to your house to a bank, and the bank would then create money, and give you the money. Of course banks would never give you the full current market value of your house, because if something happened, and you couldn’t pay them back, and they needed to sell your house quickly to get back the money they had created from nothing, then they might have to sell your house below market value to sell it quickly.
Banks continue this practice today.

And it’s not just banks that issue credit.
Every time anyone issues you any good or service, and they have reason to trust you, that you will pay them some money at some future time, they are issuing credit, be it a builder, your local mechanic, your corner store, your uncle Bill, our aunt Gill, it doesn’t matter. The principle is the same in all cases.
What often differs is the charging of interest.

Because banks have a legal monopoly on being able to create money in this way, they charge you for that privilege, it is called interest. There is a genuine sense in which a small part of that interest can be thought of as insurance, and in most cases it is a very small part of what is actually charged.

So this is a basic understanding of what money is.
It is something that people agree has value, that is used as a medium of trade for something else.

But why do we trade?

How did this idea of trade get started, and why was it useful?

Not all things occur in uniform distributions. Some things are clumped in some spaces and times, and rare in other spaces and times.
If those things are valuable to other people for some reason (any reason at all) then there can be benefit in moving those things through space and time, from where they are common to where they are scarce.
This is the essence of trade.
Trade is the delivery of a good or service from a place of abundance to a place of scarcity.
There are infinitely many variations on various themes of why things can be more abundant in some places than others. Some themes are geological, processes that make minerals or types of soil more common some places than others. Other themes have to do with climate, variations on various scales of time, in temperature, wind and rain fall. Other themes have to do with the distribution of plants and animals and diseases. Other themes have to do with skills and knowledge about how to produce goods and services.

And it is this last theme, the theme of knowledge and skills that is most critical to understanding the current dangers of money, and it requires a little more elaboration first, before connecting a couple more themes.

Firstly we need to examine the theme of distributions a bit more closely.

Trade can form anywhere that there is an inequality in distribution.
When one looks at the distribution of metals in the ground, that is clearly, in the first instance, beyond anyone’s control.
They just are where they are, mostly the result of geological processes operating over millions or billions of years.

In order to get minerals, humans must first find them, then develop technologies to extract them.
Finding them has a component of access (land rights or prospecting rights, both of which have developed complex laws over time), and aspects of techniques and technologies (information and knowledge at various levels) to increase the likelihood and decrease the cost, of finding things.

Developing technologies for extraction allows us to make use of ever less concentrated forms of minerals. Originally people needed to find gold in chunks big enough to see, and in concentrations that it was worth their time with pick and shovel digging it out. Now we can use machines to dig out and crush thousands of tons of rock to extract minute quantities of gold (too small for the human eye to see).

This theme, of developing technologies that deliver more from less, with less human input, is very important.
It happens at many levels.
The rate at which it happens is increasing exponentially, and has been for a long time (hundreds of years).

And distributions can vary at many scales of time and space.

Markets can only exist where distributions are unequal.
Many things have distributions that are naturally unequal, and markets are a great tool in helping to ensure that those scarce things go to where they are most needed, and that there are incentives to develop new methods of producing more of the needed thing, or finding effective substitutes.

Distributions of things may be unequal over time and space.
This particularly applies to knowledge.

Being able to make use of knowledge of those inequalities is what drives many of the more abstract levels of markets and finance.

In the early days of money, people who traded in different areas would notice that things traded for more in some places than others (due to natural local variations in abundance) and so if the cost of transport was less than the profit available, they would trade between markets. In the early days such knowledge of difference in markets could take days or weeks or even years to travel from place to place.
These long distance traders took advantage of the fact that local traders concerned themselves with local conditions, and paid less attention to conditions the further away they were (in either time or space or complexity of understanding).

So unequal distributions in information and ways of thinking about information, have become every bit as important in markets as primary and secondary and derivative distributions of the goods and services and forms of money themselves.

In today’s world, a world in which knowledge travels around the world in a few hundredths of a second, and automated high speed trading computer systems try to take advantage of differences in timing of way less than a thousandth of a second (the time that light takes to travel between major cities, or between two blocks in a city, or between the component processors of a complex multiprocessor computer), so in today’s world of high speed trading, the type of computer you use, where you physically put your computer systems, having the shortest possible routes between trading information, trend information and the ability to lodge trades, can be the most critical factors in success (which is a sort of insanity when you think about it deeply, but we have not yet got all the pieces together to allow us to think about it deeply – and that is what this is all about).
This brings us to the theme of money as information.

Money has performed and still does perform some very valuable roles in society.

One role of money is in allowing the price and profit signals to coordinate complex activities without any of the participants needing to know all of the complexities.
The value of this function is huge.
What it means is, you don’t need to know what someone is going to use what you have for, you only need to know how much they are willing to pay for it, and what it costs you to produce it, to know if it is worth your while doing it.
From the other perspective, you don’t need to know how to produce the components you want, you only need to know that they exist in a market, and that the market will respond in reasonably predictable ways to changes in demand (what economists call supply curves, demand curves and elasticity functions).

You don’t even need to know exactly how you produce what you do, you need only be able to produce it.

[Sub-theme knowledge]
Most knowledge that people have is heuristic (an often unconscious but useful approximation to something), not conscious. We learn by doing, and most often we are not fully consciously aware of exactly how we do what we do, we know only that we can do it. The simple act of putting a fork full of food in your mouth is an amazingly complex piece of coordination of muscles, that few people ever think about, yet we all do it. Most of us learned how to stick our thumbs in our mouths while still in the womb, long before we had any idea of what a thumb or a mouth was. A fork is just like a long sort of thumb in a sense, so we don’t think about it, we just do it. If you try to think about actually coordinating all those muscles consciously, chances are you will make a mistake, and stab yourself with your fork. But when was the last time you missed your mouth with a fork?
Much of what we do in life is like that.
I have spent 40 years designing and writing computer systems. I have learned the hard way that listening to what people say they do is one thing, but actually observing in detail what they actually do is often something else entirely. The differences may be subtle, and they are usually very important to the process of effective automation.
Complex systems are like that.

[Sub-theme Complexity]
Complexity theory is a topic that takes years of study to become familiar with, but a guy called David Snowden has developed a quite simple framework called the Cynefin Framework, that is a really useful and practical introduction to what is in reality an infinitely complex and dimensional set of interacting systems; but by simplifying that infinity down to just four general classes, he gives a very good feel for the basics of what is going on.
He categorised complexity into four categories:
simple
complicated
complex and
chaotic.

Each type of complexity is best approached and dealt with in different ways.

Simple systems are those where the constraints on the system are very well defined, the categories and processes are all well known.
A manufacturing environment can be an example. The input materials come in definite forms, with well defined and reliable properties, and they need to be assembled in well defined ways to produce a product. One can develop hard rules in such environments that produce very reliable outcomes. Rule based systems work well in this sort of environment. This is the environment of “best practice”.
One can sense what is happening, determine what category it belongs in, and make the appropriate response for that specific category.
Such systems respond very well to standard engineering techniques.   They are easy to automate.

Complicated systems are a little less reliable, the categories less well formed. Individuals in such systems develop heuristic knowledge that they are often not consciously aware of, and use that knowledge to perform their tasks with skill. This applies in most real domains of the skilled worker, be they carpenter, plumber, electrician, metalworker, potter, programmer, doctor, lawyer, politician or financial analyst. The individuals involved use skills they have acquired through practical experience that they often have little or no conscious awareness of. They often cannot tell you how they operate, and they do operate, very well. People in such environments need the freedom to be able to apply these skills in practice, to get effective results. In this environment of complicated systems, people must sense, analyse and then respond appropriately. And most often the analysis is subconscious. Most people will have a story about what they do, and most often, when you look very closely, the story and the reality don’t quite match up. Most often people are doing what works, but their story about what they are doing and why they are doing it, don’t quite fit (close, but not close enough to make a working computer system). This is the domain of good practice, of things that work most often, but not always.   Automating such systems involves very much more complex systems than a simple set of “if” “then” statements.  Modern developments in deep neural networks and Bayesian inference systems are delivering useful tools for such automation.

Complex systems have many different components that are only loosely constrained. Hard rules don’t work in such systems. One has to think about them in terms of probabilities, tendencies, dispositions to action. In such systems one can develop a feel for what might likely happen, and what actually happens can often be different.
Long term prediction in such systems is often impossible, one can only push them a little, and see how they actually respond. Then one reinforces things going the way you want, and dampens down those things going in other directions.
In the jargon of complexity, one probes the system, senses how the system responds, then responds accordingly (based upon the best information available at the time, and in the full knowledge that there is only a probability of an outcome).
The behaviour of systems and people (as a special subclass of systems) is emergent, it develops over time and space and context.   Automation at this level is in its infancy, and should have useful tools within a decade.

Chaotic systems come in two general classes. There are systems that follow rules, but very tiny variations in inputs (below the level of measurement error) rapidly result in very large variations in outputs. Aspects of weather systems follow this theme, and it has become known as the butterfly effect, where the story goes that the flapping of the wings of a butterfly go on to become a cyclone. That is something of an exaggeration. Most flapping of wings cancel out into nothingness, and a very tiny number get amplified to something significant. That is one of the characteristics of such complex systems, one cannot say ahead of time exactly what will get cancelled out and what will get amplified.
The other class of chaotic systems is more purely random, and follows rules only in terms of general probabilities. So one cannot say anything about any particular event, and can make reasonable predictions only when very large groups of events are involved. This actually seems to apply to most of reality, but fortunately for people, the smallest things people can see, and the smallest times people can appreciate, consist of very large collections of the very tiny fundamental stuff that seems to make up this reality, over very large periods of time from the perspective of that very tiny stuff, so the reality of our normal human perception has a very predictable and causal quality to it most of the time.
In chaotic systems there is no use trying to predict, prediction does not work reliably, and anything that looks like it is working is actually just illusion, a temporary aberration. So in chaotic systems one can only act, then sense (look around and see what is going on now) then respond. The behaviour of the system is going to be novel.   Because of prediction biases in human brains, machines are already better than humans at detecting chaos.
All of reality involves all types of systems.
Judging how much of what is going on in any system is the result of any particular class of systems is one of the arts of life.

So – coming back to money, and the information aspect of money, in the complex systems that are human beings on this planet, with all the geological, atmospheric, cosmological, biological and human processes all interacting with each other, money provides one input amongst many to the outcomes of complex systems.

In as far as money allows information to flow between complex systems, it has provided a important function.
The role of profit and price signals in coordinating human activity has been important.
It retains a level of importance, but that importance is lowering as other aspects of information increase exponentially.

Information systems are growing on a double exponential trend- that is the rate of increase is increasing.

[Sub-theme Exponential trends]

So what are exponentials?
An arithmetic progression is when something is added to something else.
An exponential trend is when something is multiplied by something else.
Over short terms the difference is often not obvious, but over longer terms the difference is profound.

If one adds one to the one before, the sequence goes 1, 2, 3, 4, ….
If one doubles the one before, the sequence is the same initially, then it diverges 1, 2, 4, 8, ….
By the 30th term, the arithmetic sequence is at 30, the geometric one is at a billion. Every 10 doublings is an increase by a factor of 1024 (2,4,8,16,32,64,128,256,512,1024).

The price performance of computing power is now doubling every 10 months.
People are used to thinking in terms of exponential increase in money or populations of around 2% per year, involving an increase of a factor of 10 in 100 years.
Very few people are used to thinking in terms of increases of a factor of ten every 3 years.
If you are looking at a “noisy” graph of something, with noise at around the 5% level, and you wait to see a trend emerge from the noise, then if that trend is an exponential trend, it is only 5 doublings from when it first emerges from the noise, to when it totally fills the graph (4 years at current rates).

Up until recently the power of computation had been restricted mostly to information, and it is starting to move more and more into the realm of real goods and services.

Computers can now beat the best people in the world at games like Chess and Jeopardy and Go – and Go is a very complex game, far more complex than chess.
So why is all of this important to thinking about money?

In a very real sense, money works only because we believe it will work.

It is our shared trust that people will actually exchange the token of money for some good or service at some future time that gives money its value.

In reality, there exists only the goods and services that exist, at any moment in time.
Goods tend to degrade with time.
Services do not exist if not actually employed (there existed a potential, which potential was not actualised).

The exponential increase in computational ability has led to an exponential increase in the automation of many goods and services.
Automation is great for the owners of capital, but not so great for the people displaced in the process.

[Sub-them Scarcity]

One of the key things about money and markets as a measure of value is that there must be scarcity for markets to work.
If everyone has all they need, then there is no market value.
This is entirely sensible in a one sense, but it hides something very important.

Oxygen in the air is arguably the most important thing for any human being.
If anyone is denied it for just a few minutes, then under normal conditions of temperature etc, their cellular chemical systems are disrupted to the degree that they cannot be restarted, and the person is dead.
Yet air is abundant.
We all have all we need of this most important thing, and it has no value in markets.

Why is this important?
What is hiding?

[Theme Value]

What is hiding is the common illusion that money measures human value.
All market values have this inbuilt aspect of scarcity.

Anything universally abundant has no market value.

Why is that important?

It is important, because of the exponential increase in computation and automation.

Automation allows us to produce an abundance of a large and growing set of goods and services.
That ought to be great news, but it isn’t for most people, because of a series of historical events.

We now have the ability through automation, to deliver universal abundance of all of the necessities of life.
It is actually a reasonably trivial exercise to create enough secure housing, enough wholesome food, enough energy, clean water, communication and transportation, using fully automated systems.
But, to do so would drive the market value of all of those goods and services to zero.
Automation is driving the market value of labour, and the value of knowledge, rapidly towards zero.

This could be a cause to rejoice!
Abundance for all!
Universal emancipation!
Wealth and riches for everyone.
Every person with all the goods and service and freedom and security they could reasonably expect.

But that is not what we see happening.

What we see is that our systems have been tuned towards money as an abstract measure of value.
When most things were in fact genuinely scarce, that was a sensible thing.

However, now that we have the technical ability to deliver abundance to everyone of a large and growing set of goods and services, the quest for money and profit is delivering some very predictable and very perverse outcomes for the majority of humanity.

Because markets require scarcity to deliver value, what we are seeing is the very predictable rise of artificial barriers to abundance.

The idea of “intellectual property” has been the topic of many hidden agreements between governments and large corporations. The real effect of these agreements is to deny the benefit of things that could reasonably be freely available to all, to a large section of humanity. The sole purpose of such agreements is the maintenance of the current systems of monetary value, and the power and control encapsulated within them.

What most people have not yet seen is that we now have available information systems that are so much more powerful than the price/profit signals of the market.

What very few people are aware of is why capital tends to accumulate.
We all know the old saying, the rich get richer, and the poor get children.
But few people understand the mathematical and logical underpinnings of such statements, and the assumptions that are generally believed that continue to make them a reasonable approximation to reality.

We are at something of a crossroads.

We have the ability to create a world where individual life and individual liberty are held as the highest values, and everyone is empowered to do whatever they reasonably and responsibly choose (not an unrestrained freedom to follow any whim, but a reasonable freedom where we take reasonable care to prevent risk to the life and liberty of anyone else).

If we fail to do that, and continue to treat money as our prime social measure of freedom and value, then we face a future that is bleak for the vast majority of humanity, and insecure for all.

We have the ability to create a future of security, diversity and freedom, yet doing so will require a shift away from market values as guiding principles.
Certainly it is true that markets have in the past, in times characterised by genuine scarcity, been associated with the greatest degrees of liberty and security, and as demonstrated above, that relationship is neither linear nor entirely causal (a matter for separate exploration elsewhere).

We now have an opportunity to transition away from domination by scarcity based values, and towards values based in abundance, and go far beyond the information signals of the market place.

And some things will always be scarce, and it is likely that there will always be a place for markets, and that place is unlikely to be a dominant one.  [An analogy I have used elsewhere is that markets will likely become like anaerobic bacteria, no longer the dominant life form on the planet that they once were, but still remaining in special niches where the abundant oxygen of our atmosphere cannot reach.]

The big issue of our time is:
How do we manage the transition?

We need to keep our current systems working while the replacement systems are developed.

That will require everyone having a confidence that they will in fact share in the freedom and abundance that is coming.

Exactly how we do that, and avoid the many dangers of poisoning our environment with the unintended consequences of various sorts of processes is not a simple question.

And just as markets have worked by distributing cognition, by accepting that there will exist people who are developing specialist knowledge to do what is needed to deliver better and cheaper more profitable products to market, so we must accept that different communities will develop different ways of working through these issues.

Human beings are fundamentally social cooperative entities.

Sure, we can compete for scarce resources, and when things are abundant, we can be very cooperative. We have both natures, and which one gets expressed depends very much on context.

I suspect that some form of universal basic income, paid to every person on the planet, would be the single most stable way to transition away from monetary based systems, and into full automation.
If people were not concerned that the loss of a particular form of employment meant a risk of major threat to well being, then automation could progress far more rapidly than it is at present.

We might need to rethink the rules around taxation so that money invested in productive tools has a very low rate of taxation, while that put into speculative investments had a much higher rate of tax. Also a low rate of tax on all financial transactions at source would serve to significantly alter the existing highly skewed incentive structure in the financial industries. There are many such simple changes which would be strongly opposed by those groups currently making vast amounts of money out of them, but would produce hugely beneficial outcomes to society more generally.

It seems clear that life extension will very soon become available.
Those who wish to live a very long time, in near perfect health, will very soon have that option.
That reality will strongly alter the incentive structures for everyone.

It will no longer be enough to know that you are highly unlikely to run into someone you have cheated.
With modern information systems, and extremely long lives, it will become almost impossible to cheat, at any level, and get away with it for very long.
That is likely to have a profound effect on human behaviour, and human awareness, over time.

With universal abundance of almost everything imaginable (or a substitute that is almost indistinguishable), there is no need to cheat – at any level.

The hardest thing to get is that automation has that power, and it could be a very few years (under a decade) from delivery.

And one thing you can be certain of, it will never happen as the natural expression of a free market system.
Markets must always value universal abundance, of anything, at zero, which at the meta-level, of optimising systems for a flow of money, gives universal abundance of anything a strong negative value.

Markets can be powerful tools to help us if we see them for what they are.

If we adopt them as any sort of end in themselves then they are likely to become the most destructive thing in history.

——————————————–

[Pre 2016 ideas]

This is one of my posts from well into a thread on KurzweilAI Universal Basic Income in Nov 2014 that encapsulates a lot of my thinking clearly.

This post on what is wealth covers the issue from another perspective.

[From an older context, and still relevant:]

Within a market mode of thought, McDonalds will never meet all demand. They will never meet the demand that exists at the zero price point.
Markets can deliver abundance to a subset of humanity, even a significant majority, but there is never any incentive to meet all demand – even the demand of those who have no money, or insufficient from the perspective of the supplier.
Thus universal abundance is outside of the incentive sets available to a market based system.

Universal basic income can go some way towards mitigating aspects of this issue, and can never entirely mitigate the meta incentives inherent in the system as a whole, to reduce the level of income of a majority to survival only.

Your assertion that “people are never satiated” is false. Psychology has falsified that assertion. You must know the old saying of “too much of a good thing”. I find it hard to believe that you haven’t at some time in your life eaten so much of something you loved that you simply couldn’t eat any more – neither the desire nor the physical capacity.

McDonalds produce burgers to a particular price point. Any demand below that price point is not met.
The only way to ensure that all demand is met (universal abundance) is to have the price point at zero.

I know this is difficult to get one’s head around when one is totally immersed in a market mode of thought, when one is under the illusion that all things have costs.
That is demonstrably not true.
Air doesn’t have a cost.
Air is vital.
There is a massive demand for air.
That demand is met in full, with a huge reservoir.
Air has zero market value.

Imagine when most imaginable goods and services are similarly freely and instantly available.
There need be no cost, if all the work in production and delivery of those goods and services is done by automated systems that are automated to the point of self maintenance.

[This could be achieved today with respect to all information, except that doing so would destroy many jobs and most industrial profits, and cause massive disruption to existing systems, because those systems are fundamentally organised on the basis of scarcity. Most of human knowledge is already in digital format, and could be made available to every individual on the planet, but is available only to those who are able to pay ($30 to read an individual research paper, even for those who need to read thousands to find the few that are actually important to them – very few have that sort of money – I certainly do not).]

I am confident that we could in fact produce such a set of machines, if we chose to do so.
I am confident that it could be done in today’s economic reality for a cost that is less than the lifecycle cost of a single Nimitz class aircraft carrier.

Believe me, I value oxygen.
I was a free diver and a scuba diver. In practising for deep free diving I explored all sorts of deep meditative techniques and control of heart rate, respiration rate, and levels of consciousness.
The range of experiences that resulted has left me with a profound appreciation of the value of oxygen.

Nietzsche did well with the tools he had. I really enjoyed reading him, and he had nothing in his experience with which to really model (in the meta sense) the sorts of models that we have today. Today we have virtual reality of digitally created worlds.
Today, if you are a systems developer, with deep experience of all levels of systems development (I have written a language, an assembler, many levels of systems software, and many user applications in the 40 years I have been programming), then it is easy to understand where Nietzsche made his error of logic. If all we have to experience is the model of reality created by our brain, then it is hard to see that all our experience is of the model, and none of it of reality itself (as the model is our experiential reality, it is hard to see that it is just a model, and not actually reality). It seems clear to me that the model of reality that we experience as reality is software, and the software system that is our conscious awareness gets its experiential qualia of existence from the model, not from reality directly.
And evolution has dictated that the model is reasonably accurate in most individuals in the sorts of realms that evolution has had to deal with, but not necessarily so good in some of the more novel situations (like trying to understand quantum mechanics) that we encounter in modern society.

I think philosophers who claim that science has nothing to say about choice or ends are displaying hubris.
Science is simply asking questions, and dealing with whatever evidence shows up, with all the tools at hand.
Science in this sense can have a lot to say about the role of mirror neurons in empathy, or the role of attendant strategies that prevent cheating in stabilising cooperation in highly cooperative species.
Science can have a great deal to say about the mechanisms that give us an ability to make choices, about the fundamental uncertainty underlying all reality, about the illusion of hard causality that many seem to be trapped within.
And ultimately, if morality is to have any meaning, it is about choices.
From another perspective, if morality is to have any meaning, then we must have the power to create, to break the chain of cause and effect that seems to dominate most of reality at the scale of unaided human perceptions, and to somehow have access to the truly random.
It seems that this reality in which we find ourselves is, at the very lowest level, a profound mix of the lawful and the random. It seems that the random is, in most instances contained within very tight probability distributions, and sometimes those distributions have asymptotic tails that allow very unusual things to happen at very low frequencies.
It seems that it may in fact be true that anything is possible, and it seems almost certainly true that some things are far more probable than others.

It seems that every human being has profound access to such creativity, despite our educational institutions doing their best to teach us to obey rather than to be responsibly creative.

For 40 years it has been clear to me that it is logically possible to extend life indefinitely. I don’t know how, and I am confident, beyond any shadow of reasonable doubt, that it is in fact possible. All life alive today seems to be part of an unbroken chain of life stretching back billions of years. My particular form is only about 60 years old, but the egg that I came from spent 35 years in my mother’s body as a cell before a sperm from my father found it. Age related degeneration is an artefact of complex life, not a requirement of cellular life. That being true, it must be reversible.

Politics can be cooperative.
I have just had 9 years in a local political process that was not simply cooperative, but also consensus. It took 3 years to establish reliable communication, and a further 3 years to establish working levels of trust. And it is working, across very diverse interest groups. www.teamkorowai.org.nz
Quite an interesting process – quite profound in its wider societal possibilities.

And I agree that current political systems are in general far from optimal solutions for individual liberty or empowerment.
And that has little to do with science – and much more to do with many levels of social inertia, ignorance and dogma.

And I love that quote [purportedly but not actually from Mark Twain] “It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.”

Added link from June 2017 https://tedhowardnz.wordpress.com/2017/06/13/evonomics-hayek-meets-information-theory/