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Thursday, 24 January 2019

An Easy Life Is Not Our Friend

My Brain Hurts

Cloud cuckoo land, where all the happy people go to play (source: Paul Harrop).

Sometimes it seems to me that people are detached from reality, living in cloud cuckoo land. Some people, especially politicians, even seem to have made a permanent home in cloud cuckoo land with no idea how the real world works.

When people are so out of touch with reality they make stupid decisions. I was wondering why people make stupid decisions, as in decision that are obviously stupid. So, I investigated a little. Psychologist, fortunately, have done quite a bit of work into stupidity and the first book I found on the subject is “Understanding Stupidity” by James F Welles, Ph.D , which was a good starting point and well worth the read. There are, of course, many other books on stupidity and related phenomena such as group think. 

This all got me interested in thinking and the problems humans have with thinking. Fortunately, again, there has already been a lot of work done in this area. Buster Benson has put together a nice cheat sheet covering the problem. He basically summaries the problem as:

                          1.    Too much information
                          2.    Not enough meaning
                          3.    Not enough time
                          4.    Not enough memory.
As he says “thinking is hard”. Part of why thinking is hard perhaps has to do with the way that our brain evolved. If we view intelligence as grounded in the real world, we can think of (or define) intelligence as an augmented reactive system.

On the Evolution of Intelligence

If we start with a simple reactive system embedded in the real world with sensors and actuators we can see some simple “intelligent” behaviour. Say, for example, if we had a mobile robot with a bump sensor. As it went its merry way around a room and bumped into something the bump sensor could trigger a “reverse – rotate random angle – forward” behaviour. 

If we added another sensor we could get a little bit more complex, and, therefore, a little bit more intelligent behaviour from our robot. As it wondered around its world and bumped into something it could have different behaviour depending on whether or not it was the left, right or both sensors that were activated. So, we could have, for example, left sensor activated triggering a “reverse – rotate random angle to the right – forward” behaviour. And then the opposite direction for the random angle for the right sensor and the original behaviour for when both are activated.

We could add more sensors such as a light sensor or sound sensors and then produce even more “intelligent” behaviours but the system would still exemplify a purely reactive system.
What if we augmented the system with memory? Now instead of reacting purely to sensor input it could also react to memory of sensor inputs. So, for example, if the robot bumps into an object and its left sensor triggers the left sensor behaviour it could remember its actions. When it wonders around the room and ends up back where it bumped into an object instead of waiting for the left bumper to be activated it reacts to its past memory of bumping into the object before. So, it triggers the left sensor behaviour before its left sensor is triggered. It would then appear to anticipate the object and act more intelligently.

What if we argument the system even more. Say with the ability to take memories and produce expected encounters? Then the robot would not just react to sensor input nor memories of past sensor inputs but also expected out comes of what it was doing. 

We can add more augmentation such as learning and real world modelling. Now the robot could react to events that it didn’t experience itself but learnt from others. Or react to models of the world that it created (sort of fantasies). 

Layers of augmentation evolve and become more and more complex, creating (or allowing for) more complex, intelligent behaviours.

I expect that intelligence in humans evolved something like the above (although I presented the idea very simplistically). Thus, our ability to think about things that don’t involve past experiences is a later augmentation to our brains. As such it is the more complex and more difficult to run part of our intelligence and takes more effort. Far easier to bump into an object and react than to think about the long term consequences of our actions.  

But I was wondering if there was more to it than that? As intelligence is embedded in the real world, perhaps we also have to experience the world in order to develop our intelligence? Our ability to think?

Common Sense Not So Common?

A cute cuddly cat (source: Dantheman9758)
I’m wondering if the easy life we lead is not our friend? We live in nice warm houses that keeps use safe and out of the rain. We eat well, never having to kill to survive. We live in a world so easy when we look back and compare ourselves with the world of our ancestors. We become so separated from the consequences of our actions. If our hunter gatherer ancestors had though a sabre tooth tiger was just a misunderstood cute cuddly cat, the consequences of such are error would be realised quickly and our hunter gatherer ancestors probably would not have got to breed. But today. If we made such an error we are protected from the consequences of our actions, thus we don’t learn nor develop as a result. It is like our easy life results in breaking the feedback loop that regulates our stupidity. The feedback loop that stops us from being so stupid that it becomes dangerous. 

Like gold needs fire to purify it, perhaps we need adversity to fully develop as a human being? Through hardship we learn about the world, we develop our common sense and we develop our thinking ability? 

As G. Michael Hopf says in Those Who Remain”
“Hard times create strong men. Strong men create good times. Good times create weak men. And, weak men create hard times.”

 I think that is over simplifying the situation but could well contain a core of truth. Have a look, for example, at the Strauss–Howe generational theory. Strauss and Howe theorise that societies go through four phases:

1.      High, which starts at the end of a crisis and is characterised by cooperation with strong institutions and low individualism.

2.      Awakening, which is characterised by “self-awareness” and questioning of institutions.

3.      Unravelling, which is characterised with weak institutions, strong individualism, and relatively low cooperation.

4.      Crisis, which results from the unravelling and is characterised by destruction but also sows the seeds for the next high.

It takes about 20 years to go through each of the four phases. And as we cycle through each phase, they each have similarities to previous phases but each phase has its own characteristics; history repeats like a fractal. A crisis, for example, in one phase may not be as bad as a crisis in another phase but the crisis still occurs.

But it is this idea that it takes a crisis to produce a generation that is willing to cooperate and build a better world and then those who live the easy life that results are the ones to cause the next crisis that interests me. 

People living the good life never full achieve what they could be. As Seneca once said:
 "I judge you unfortunate because you have never lived through misfortune, you have passed through life without an opponent—no one can ever know what you are capable of, not even you."


So, what would all these mean for a future technocratic state? Isn’t the idea to build a sustainable monyless society where everyone has access to a high standard of living? Doesn’t that mean we aim to build the good life? An easy life for people? If so, would we not, as Marx perhaps would say, sow the seeds of our own self destruction?

Monday, 13 August 2018

Why technocracy?

copyright: New Yorker

We define “technocracy” as “rule of the skilled”, that is as a system of government composed of knowledgeable experts. The exact implementation of technocracy can have many forms. There have, for example, been a number of technocratic governments in Europe since the end of the Second World War. These government tend to be caretaker governments composed of civil servants who run the country till a democratic form of government takes over. EOS propose another form of technocracy base on teams of experts in a holarchy. Either way, all forms have the central idea of experts making the decisions.

Experts are knowledgeable in their domain of expertise. They often have studied and worked in the area for many years. We would argue that such a system can form a better way to govern the current systems we use today. I will point out two main reasons as to why; the first has to do with the complexity of society and the other with human cognitive abilities.


We can define complexity as “composed of many parts”, where “many” makes it difficult for us to understand the full workings of a complex system.

Society forms an example of a complex system. It has many parts and we find it difficult to understand society fully. The “many parts” include the individual human beings that make up society but also groups of people that make other organisational parts to society such as families, clubs, societies, institutions, communities, sports teams, and work colleges. All these parts interact with each other following sets of rules that define or govern the behavior of the parts. Some rules have a formal nature such as laws and club rules but others have a less formal nature such as individual likes and preferences. In the end with have systems within systems in a complex, dynamic, network.

Out of the interactions of the parts comes the society we live in. It can take many years of study to understand just part of how these societies work. For example, most universities offer three to five year degree and master cources in subjects suchs a sociology, psychology, computer science, and electrical engineering. But even outside a formal academic environment we only learn part of how a society functions. We learn about our local communities, clubs, and societies through living within those groups. Yes, even for people who have many degrees, we never gain a full and complete understanding of every aspects of society. We become specialists or experts within certain domains but not others.

Many issues that face us today have a complex nature such as global warming / climate change. He we have technological aspects where we have, for example, systems of systems of energy production and use. But we also have other aspects such as social and psychological to do with how we live as well as political dimensions. This make solutions that involve one aspect such as politics or economics unlikely to succeed.

Human nature

We have evolved as social animals. As such we have many built in mechanism to enable us to quickly think and make decisions in a social context. We haven’t evolved to understand the physics of the world. Thus, we tend to have a poor understanding of how the real world works and we make the same cognitive errors over and over again.

Buster Benson did an excellent summary of our cognitive problems:

  • Too much information
  • Not enough meaning
  • Not enough time nor resources
  • Not enough memory

This results in our minds taking shortcuts in thinking, using heuristics and past events to make quick decisions that often serve us well in a social context but are often wrong when we deal with the complex real world problems that surround us.

Our problems with thinking lead to other cognitive difficulties such as the Dunning–Kruger effect, where those who know the least tend to overestimate their cognitive abilities such that people with little knowledge of a subject tend to have higher confidence in their decisions. Thus, the majority are often wrong on many technical problems that we face in society; yet many are confident in their solutions!

When it comes to making decision we tend to get it wrong more than we get it write. This has to do with the fact that there are more ways to get something wrong than right and our cognitive biases means that we tend not to know if something is right or not.

Rule of Experts

Experts are human too. That means they suffer from the same cognitive biases that we all do. That means they can get it wrong, like the rest of us. Or even disagree among themselves. They have the same problem know if something is right or not. However, experts don’t need to get it right. They only need to get something that is workable. “Workable” and “being right” are not the same thing. Many technically wrong decisions can be workable if they are close enough. For example, Newtonian physics is wrong but workable in most situations.

Experts have studied, and even have worked in, their area of expertise for many years. This increases the probability that experts will make workable decisions that non-experts. But following on from the complexity of society, no expert will know all that is needed to make set of decisions necessary to run a society. Thus a technocracy would need teams of expert at various levels of society to make a workable form of governance.