Encefalus

The last summer I was reading this book: The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics

The book was dealing mainly with the complexity of economic systems. It actually tried to introduce a new field of economic analysis Complexity Economics, that is inspired by the recent trend of complexity science and has strong roots into the theory of evolution.

One very interesting idea that caught my attention was that of causality and expertise in the field of economics and business. In fact, what caught my attention was the implications that this idea could have in the general field of epistimology, both from a philosophical-theoritical point of view, and in a more applied setting. But, let me first introduce you to the whole concept.

What Eric Beinhocker says in the book is this: many experts are not experts, but just lucky. What makes look like experts, is the fact that they get it right. But getting it right, has nothing to do with knowing why you’re right or being right for the right reasons.

Let’s say that there are a 100 companies in the stock-market and there are a 100 stockbrokers. Each one of them chooses a stock at random and bets on it. It is inevitable that some of the stocks will go well and some won’t. Those stockbrokers who made the right choices are considered experts, even though the chose it at random. You think that this is far from reality but read this first: http://www.marketwatch.com/story/indexes-beat-most-actively-managed. Actually, this has also been argued by Nassim Nicolas Taleb in his book The Black Swan.

What is very interesting about this whole idea, is how it could be applied to virtually anything. Surely, there are statistical tests that allow us to derive probabilities and degrees of confidence about our assumptions, but I mostly want to make a philosophical argument here. What if, the whole world was nothing sort of a bunch of random coincidences that we thought were making sense, just because our brains try to make sense out of everything (Split Brains, Consciousness and Michael Gazzaniga) ?

Maybe this sounds a lot like epiphenomenalism applied in a causality. Epiphenomenalism is the belief that mental states are by-producs of physical ones without any causal relation. Maybe, the world could be described by a set of random physical states with no causal relation between them, that are epiphenomena to some underlying structure that generates them.

However, while something could be created entirely at random, it doesn’t mean it was created this way. Actually, this might be a problem of the generative approach of doing social science that Joshua M. Epstein has advocated. That is, the impossibility to know for sure which initial conditions lead to a final state by reverse engineering the final state . In Encefalus, I covered a similar problem in http://encefalus.com/philosophical/truth-pure-computational-models-social-life/ which you might want to take a look at. 

But, maybe this argument is going out of control . Anyway, it’s something that I’ll try to keep in my mind while doing my research, especially science focused on the generative approach. Chance is a powerful force, not to be ignored.

Lately I have started dabbling with fuzzy logic and fuzzy set theory. You’ll probably start wondering what these are. I won’t try to give you a definition, but rather I’ll give you a few examples to help you understand yourself.

I don’t like the mathematical way that concepts like fuzzy logic are first presented. A mathematician will probably first present you some topics on set theory. However, I prefer the way that an engineer thinks about them. That is, instead of basing their validity on axioms, base it on usefulness. If a tool provides results, then it is useful. Therefore, I will provide you with examples in order to realize why fuzzy logic might not be another theoritical abstraction, but something really connected to the way our brains work.

Not this kind of fuzzy

You’re talking on the phone with a friend and you are trying to arrange what will you do this evening. Your friend tells you he has some work to do and so, he will be out somewhat late.

What does "late" mean?

For some people "late" might mean after 11 p.m. For others it might mean after 10 p.m. And for some people it might mean 1 a.m.

Let’s define late as after 11 p.m. If your friend goes out to have a few beers at 10:55 p.m., would you call him a liar? Of course not. If he did that at 10:30? At 10? At 9? At 7:15p.m.?

This is like the Sorites Paradox.I especially like the "baldness" variation. That is, let’s say that a man loses one hair from his head. Would you call him bald? Deffinitely not. But if he lost 2? How about a 100,or a 1000? Maybe 10.000? What is the exact threshold of "baldness"? Does a number X exists so that everything above X is not-bald and everything below X is non-bald?

Britney Spears: bald or not?

As you see, regular "crisp" logic, can many times create such paradoxes. Most things in life don’t have clearly-cut boundaries. Most things in life are not black and white. This includes both descriptions of physical objects and sizes ("large","small","tall"), as well as abstract notions, such as democracy. How democratic can a democratic state be? It’s something difficult-to-impossible to define.

You might think that these boundaries cannot be simulated adequately mathematically.  However, this is wrong.

All this changed by Lotfi Asker Zadeh,the man who created fuzzy set theory. In traditional logic an element is mapped to a set via a membership function that can give the value 0 (doesn’t belong to the set) or 1(it is part of the set). In fuzzy logic, all membership values are defined in a continuum in the domain [-1,1]. So, element X can have membership 0.7 to the set A.

Lotfi Asker Zadeh

Let’s think about it for a while in real-life. An orange might be 0.7 sweet. A man might have a membership of 0.6 to the set of tall people. This means that an orange is sweet, without being the sweetest thing you can eat, while a man might be slightly above average, but not really tall.

Fuzzy sets are inherent in the way we think and we interact with the world. People are constantly using them without even realizing it. Very few of the notions we use at our everyday lives are crisp. Yet, we get along fine. This may come as a revelation to many people who think that we cannot use a notion if it is not properly defined. I had many conversations where the other person tried to prove that an argument is invalid because a notion could not be described fully and have its boundaries clearly drawn. Yet, you don’t really need to know what peace, nature, or friendship are in order to move around in your everyday life. You can have many friends without really being able to give the definition of  "friendship".

Fuzzy the way you think is, young padawan

Your brain might make complex philosophical arguments of why you cannot define love of friendship, but you socialize nevertheless. This is the important point here. While fuzzy logic might not seem so "logical" to many people at first, it is, nevertheless, working. And this is what proves it right. Some people like to think like mathematicians and convert such a strict way of thinking to other areas of science and life. That is, we start from a set of axioms and reach a set of conclusions. However, life on Earth has evolved through millions of years without using axioms or complex arguments.

Our everyday lives are much fuzzier than we might think at first. Indeed, it could be said that it’s almost impossible to predict most important events that will happen in the future, even if we know that they will happen for sure. We can’t predict our death or the death of others. We can’t predict economic collapses and wars. We can’t predict all those Black Swans Nassim Nicholas Taleb has been talking about. How can we tread these dangerous grounds every day, yet come out victorious? It’s simple. We don’t really try to predict what’s going to happen. We just estimate what’s going to happen. Nevertheless, this proves just to be enough.

I believe that the greatest scientific revolution of the 20th century was the introduction of vagueness and ambiguity in science, through probability theory, statistics, neural networks (in artificial intelligence) and other theories or approaches. The 21st century will be the century where these theories from simple tools, will become the mainstream. Our world is inherently ambiguous; it is inherently fuzzy. Yet, our role as scientists is to try and analyze it. Fuzzy logic is just another tool in the toolbox, but a very good one indeed

Hello there guys (and girls)!

It’s been a month and two days since I wrote my last post. I am really short on time, but as you can see I always write when I have the time and an interesting subject on my hands

My hands

What I want to talk about today is the future of training in psychology. I am not talking about clinical or school psychology or any other applied fields here. I am talking about psychology’s standing in science as it is now and as it will be in the future, according to the current scientific trends.

Psychology is not a pure science. While it is true that it has a field of study, that of the behavior and the mind, it consists, nevertheless, of an amalgam of schools and methods, those, sometimes, are very different.

All sciences experience paradigm shifts. Physics, for example, has experienced the leap from Newtonian physics to relativity and then quantum mechanics. However, physics always had a certain tool in its trade, mathematics, and a certain subject, the physical world and the forces that act upon it.

Psychology on the other hand, suffers from the fact that it doesn’t have a predominant tool of analysis and scientific inquiry. Psychology’s methods have ranged from Wundt’s analytic charting of the elements of human consciousness, to Freud’s psychoanalysis, to discourse analysis, to cognitive psychology and computational models of the mind, to statistics, to pretty much anything .

What I am trying to show, is that while other sciences had a specified “toolbox” and a field, psychology has a very wide field, with an even wider toolbox.

Pretty much anything…

Some people might argue that this is good, since the human mind and human societies cannot be analyzed by any single method alone. However, how could someone compare for example, discourse analysis, with a statistical research on the same subject, with psychoanalysis? He probably couldn’t. Many articles and books on such matters will simply mention all the different theories and that’s it.

I believe it’s pretty obvious there is a problem there. In a more concrete and advanced science, we would use evidence, experiments and a certain set of mathematical theorems and proofs to make conjectures about the future course of research and how we can reach a final solution to a certain enquiry.

But this is not the case in psychology where anyone can say anything he likes without any final conclusion. I truly and wholeheartedly believe that science exists in order to find answers, and it uses the power of reason to do that. Instead, psychology seems to find questions, then formulate a bunch of theories about that, and then forget about it.

For about a year I have been thinking about these things and I read quite a lot of books and papers on the subject. I believe that psychology in the 21^st century can already start to walk towards becoming a more complete and concrete science. My view is that in order to advance psychology as a science, we must achieve these goals:

• 1)      Find a certain set of tools that we must use
• 2)      Find a certain method of work that we should follow, towards scientific experimenting
• 3)      The method and tools that we use should be able to adapt in the demands of newer research

Let me explain for a while what I mean.

I am once again inspired by the sciences of the natural world. Let’s talk once again about physics that is the most complete science yet. Physics has

• 1)      A powerful tool in its disposal: mathematics
• 2)      A certain method: the experimental method
• 3)      Both the method and the tool have evolved over the centuries, without changing the core of physics

One the other hand, no-one can say that cognitive psychology and computational models of the mind have many things in common with humanistic or social approaches in psychology.

Science is my ally and a powerful ally it is…

What I describe here is an oversimplification, but I hope I make my point clear. Psychology’s methods and tools are weak, and we need new tools. However, the reason that they are weak is because, according to my opinion, psychology is a thoroughly complex matter that cannot be analyzed by ancient and traditional tools, such as pen-and-paper algebra.

Computers have come to change all that. While computers changed the way psychologists think about the human mind and brain, I believe the greatest change has yet to come, and it will be the tools that psychologists use in order to understand the mind and the brain.

Agent-based modeling, chaos theory, complexity theory, neural networks, all these are modern tools that provide a way to analyze and think about psychology in ways never before possible. While all these tools might seem different, in fact I think that they are simply another way to think at computation, what might become in the future, the main tool of psychology.

So, what all this has to do with the training of psychologists? It’s simple. Psychologists are now trained in a bunch of theories. So, when they graduate, they have a lot of questions, but no answers and no methods to find these answers. On the other hand, graduates of schools like computer science and mathematics, hold in their hands powerful tools and years of training in fields that can’t be mastered in one or two years alone. Yet, the latter ones can deal with problems that psychologists face, while psychologists would never be able to do so.

The results of bad mathematical education

Maybe this explains why many interdisciplinary programs in universities seem so promising, since they combine the skills of some students with the theoretical background of the other half.

However, I really believe that this should change. We should no longer train psychologists to find questions, but search for answers. We should really see how we can turn psychology into a more rigorous science. Psychologists should be trained in mathematics and in programming. We should not treat psychology as if it was one thing. We should provide them the knowledge to analyze psychological problems from a new perspective that belongs to the 21^st century, and not to the two previous ones.

I’d like to see psychologists graduate from the school and the seek graduate programs that deal more with computer science or mathematics, rather than enroll in simple research programs, that will they will provide valuable experience, they will not teach them more advanced scientific methods to deal with problems that remain yet unanswered.

Other science students continue their education by learning more advanced methods and tools, while psychologists will simply drive on some research using the default statistical techniques, reaching one or more uncertain conclusions. It’s time that we consider mathematics and computation an integral part of the sociological and psychological enquiry of the 21^st century and act accordingly.

Related Links:

Society for chaos in psychology : A group of scientists that I share many common thoughts with.

Hi there folks!

This time I am writing, because I just had an idea that I need to discuss. I was just reading the book Social Emergence: Societies as Complex Systems. I just read the first 4 pages, when I came across a paragraph that dicusses the nature of emergence and the philosopical debates around it. Yesterday, I was reading this article from Scientific American Mind: A "Complex" Theory of Consciousness.

This article in Scientific American Mind describes a theory by Giulio Tononi, called Integrated Information Theory (IIT).

IIT is based on two axiomatic pillars.

First, conscious states are highly differentiated; they are informationally very rich. You can be conscious of an uncountable number of things: you can watch your son’s piano recital, for instance; you can see the flowers in the garden outside or the Gauguin painting on the wall. Think of all the frames from all the movies you have ever seen or that have ever been filmed or that will be filmed! Each frame, each view, is a specific conscious percept.

Second, this information is highly integrated. No matter how hard you try, you cannot force yourself to see the world in black-and-white, nor can you see only the left half of your field of view and not the right. When you’re looking at your friend’s face, you can’t fail to also notice if she is crying. Whatever information you are conscious of is wholly and completely presented to your mind; it cannot be subdivided. Underlying this unity of consciousness is a multitude of causal interactions among the relevant parts of your brain.

Giulio Tononi

Tononi claims that since consciousness is information, we can use mathematical notions from information theory, such as entropy. Scientific American gives an equation that describes Φ.

Measured in bits, Φ denotes the size of the conscious repertoire associated with any network of causally interacting parts. Think of Φ as the synergy of the system. The more integrated the system is, the more synergy it has, the more conscious it is. If individual brain regions are too isolated from one another or are interconnected at random, Φ will be low. If the organism has many neurons and is richly endowed with specific connections, Φ will be high—capturing the quantity of consciousness but not the quality of any one conscious experience. (That value is generated by the informational geometry that is associated with Φ but won’t be discussed here.)

When I was reading the book Social Emergence: Societies as Complex Systems, a few thoughts came to me concerning the notion of emergence. Emergence is an elusive concept, but from what I’ve read so far, these are the first things that come to my mind that all can agree upon

1) It is produced by the effects of autonomous interacting agents, with no top-bottom guidance.

2) It must produce something that is more than the sum of its parts.

The first premise is pretty straightforward. The second however, isn’t very clear. The book for example says that the are three views. Some believe emergent phenomena have to be unpredictable, some irreducible, and some, novel. Joshua Epstein disagrees with the concept of irreducibility, since, if, for example, we executed an agent based model, we could, in theory, track the production of the phenomenon to the interactions of the agents. In this regard, he discards completely the notion of emergence. I agree that irreducibility is the wrong concept, but I can’t discard the notion of emergence, because it seems all too real to me.

I agree with the other two definitions, unpredictable (cannot be predicted given the properties of the constituents) and novel (none of the constituents holds the properties of the emergent. A society is composed of people, but a person is not a society).

More than the sum of its parts

Maybe we could formalize the phenomon of emergence through the use of information theory like in Tononi’s IIT. Maybe this theory can show the way for a quantification of the notion of emergence.

However, emergence, might really not exist, but not as Epstein put it. Emergence is a property of complex systems. Wolfram seems to support and idea that is a mixture of pancomputationalism (all the universe is a large computer and every process in it is a computation) and a belief in the purity of computational forms, pretty much like Plato’s belief it the purity of abstract forms.

Should this conjecture be right, then, the emergent phenomeon could in effect be belong to a class of scalable systems, that share the same properties in all constituents and in emergent phenomena as well.

System upon system

To explain this idea better, the behavior of individual people is dictated by their neural networks. The interaction of people, is the interaction of different neural networks among them. The same properties that are exhibited in a neural network, could be exhibited in the emergent phenomenon of society that is produced by the interaction of the neural networks among them. Of course, this is a simple example, since the interaction among people doesn’t involve neural networks in their purity, but physical objects as well (which constitute the "economy"), as well as other factors (geographical location, weather conditions, etc.).

Anyway, these are some things that just came to my mind and I had to share them with you! I hope you found this article inspiring!

Complexity theory says otherwise

So, where does complexity apply? Almost everywhere, since complexologists believe most phenomena to be complex. What methods does it use? Many methods, which we are not going to describe here, because there is not enough space to get technical. My belief (and hope), however, is that the main tool of complexologists in 20 years where complexity theory will be (as I predict) a mainstream science, will be artificial intelligence. But these are just hypotheses about the distant future. Only time (and science) can tell

Hey, I return after nearly missing for a month. This time, I won’t write about my current interests which revolve around computation in social sciences. This time I am writing to revisit politics. Actually, I don’t know why, after a month not having published an article I feel the urge to throw some random rant. So please, bear with me.

You know what, people are stupid. People are utterly stupid. And the problem is that they are so stupid that they don’t even realize it. I’ve started thinking that people are not much smarter than monkeys. Sometimes, I feel like stranded on an island with monkeys as my sole companion.

Home…

It wouldn’t be an overstatement if I said that most people resemble airplanes with deficient auto-piloting systems. They go straight to nowhere without even realizing where they are.

Now, let me tell you why. Psychology exists as a science for over a century (1879). Through its existence we have started to uncover many of the mechanisms that we use to survive in our every day environments.

But, why do I use the word mechanism instead of something other word? Because, you don’t have to see people as something more than that. And let me explain myself.

Why don’t you hear very often every day people arguing with mathematicians and physicists about science? Because no-one really cares about maths and physics in their every day lives. But, the huge amount of self-help and pop psychology books shows clearly how much interest exists about psychology in our every day lives. This is natural, since in order to interact in a social setting we all have to become amateur psychologists.

Your everyday reasoning and its results

In our efforts to do that, we create theories about others and how people interact. We create theoritical notions like "free-will" and some of us end up using political theories in our cognitive arsenal, as a means to explain social phenomena.

However, while we believe that these theories are correct, in fact, science has proven most of them to be absolute crap. Yes, they might help us get through the day, but they are not correct.

Of course, being scientifically correct is not what life is all about. Life is just about one thing: survival. Yeap, so simple. This is what the theory of evolution teaches us. And this is why people are so utterly stupid. We don’t need anything too much sophisticated to survive in our environment. We just need some simple heuristics to survive.

Yet, this is exactly the very reason everything seems to go straight to hell. Our brains have built societies and civilizations that are far more complex than anything our brain has been evolved to face. This is why we need to start trusting science when we are making big decisions. However, I haven’t seen too much science in politics. I haven’t seen too much science in warfare. I haven’t seen too much science in the recent economic crisis.

John Rambo knows how to survive even though he knows jack about science

Someone will surely argue that science is indeed present in all these three occasions: politicians speak with scientists, warfare is based on technological advance and economics is a science in itself. Yeah, but it’s pretty obvious that this is not what I am talking about here. I am talking about how we can use psychology or any other scientific means (like computation sociology I have explored in previous articles)  in order to make decisions that are based more on facts, than on theory.

The problem here is that we have a giant gap between society and science. Psychology has experienced the major paradigm shift of subconscious non-logical mechanisms of action that govern our lives, decades ago. On the other hand, society and politics have not. The most tragic of all is that I am not sure even if they are able to do that. It seems more probable to me that most people are not able to grasp some concepts that will be used by corrupt officers in power in order to create their own vision of society, rather that people can abandon archaic concepts like free-will and spiritualism.

Fuck yeah

Maybe we can see many things in the police state of Great Britain and in the juridical system of the USA, where stupidity reigns supreme above all reason and logic. The fight against terrorism in the recent years has created many comical examples of cops raiding homes or goverments spying on their citizens. Somehow, many people believe this will make the world safer, while if you think about all the terrorist strikes that have happened in the last 10 years, you will see that they are not that many at all.

I can’t really tell what course shoudl society take. I can only tell what I observe: that we are creating policies based on irrational decisions, ignoring all scientific evidence.

The title of this article was inspired by an article on Cracked: What is the Monkeysphere?

You can find more articles about irrationality and human stupidity in Encefalus:

Subliminal messaging, subliminal advertising and subliminal learning for a subliminal post

A different view on economics: maybe all we really need

Lotteries, poverty AND credit cards this time along with the proper social and scientific analysis

Lotteries, poverty and social implications

As I had said in my previous post, I am very busy this time. Now, you are going to see why

Lately, I decided to learn more about computation models. This will probably be reseach focus in the upcoming years. I created two models, which I want to present to you. The models were created using NetLogo. NetLogo is a very simple language based on Logo. It is specifically for creating agent-based models. The two best features are that its programs can be exported and run on the internet in a simple java interface and that it can be connected to mathematica via tha MathLink. Mathematica not only is a very powerful application, but, it can also be connected to other computer languages, like those of the .NET protocol. This expands the horizon of possibilities.

The first model I made, is called the Three Species model. It’s a model where there are three species, the sugar eaters, the meat eaters and the grass eaters. These species, eat resources on the map, kill each other and reproduce asexually like bacteria. The model has many parameters and may seem a little bit confusing at the beginning. The reason I made so much parameters was to study the functions of NetLogo.

Don’t get too confused. I have incorporated detailed instructions on how to use the model inside the model.

The Three Species model: http://encefalus.com/the_three_species.html

The other model I created, is called the Walker Traffic model. It was based on a native model of NetLogo called traffic (simple). It has an one way road, and walkers that want to go across. It is simpler than the previous model. Not only it has fewer parameters, but it’s behavior is simpler as well. The three species model contains many stochastic interacting elements that produce all sorts of interesting dynamics. In fact, you’ll see that even if you hold all the parameters the same, the results each time change. On the other hand, the walker traffic model has simple dynamics that, I suspect, could be described by a stationary law.

The Walker Traffic model: http://encefalus.com/walker_traffic.html

My models are top baby!!!

First of all, I’m sorry for not having written for so long, but I am really busy. Anyway, this time was not wasted, since I have passed a large part of my free time dealing with new ideas.

These ideas revolve around computation and a possible formal framework of methodology in social sciences.

In this article I want to discuss some thoughts that came to me after reading A New Kind of Science.

In this book, what Wolfram is essentialy proposing, is that simple programs like cellular automata can be the answer to all our prayers He believes that they could replace mathematics, or work alongside with them.

This is an interesting approach (even though its claims have been criticised as overly too extravagant) . What I want to discuss here is if this could be possible in social sciences.

Stephen Wolfram

The main idea behind A New Kind of Science is what is called the Principle of Computational Equivalence. This means that all systems that are not obviously simple (therefore hold some complexity), have been produced by a set of rules that are simple.The additional complexity is due to the additional computation that has taken place, not to more complex rules. More complex rules, as Wolfram says, as he presents many examples (but no formal proof), do not lead to greater complexity.

This means for example, that the evolutionary process that has given birth to millions of species is not governed by zillions of factors as one might have imagined, but rather, by a simple set of rules that have been simply interacting with the environment.

Furthermore, Wolfram, through the study of complex systems with simple rules, is lead to some more conclusions. For example, the reverse engineering (reducibility) of complex systems belongs to the NP-complete class of problems, which means is practically impossible. This means that one might have thought that we can just create an algorithm to analyze a system and discover its rules, Wolfram says that this is higly improbable.

Rule 110 one dimensional cellular automaton belongs to Class 4 rules (complex ones)

According to Wolfram, most systems in nature are complex and irreducible, but we haven’t realized it until now, because mathematics have been used only in occasions where we knew they would be successful beforehand. According to Wolfram, even systems in mathematics belong to this classification.

For example, the solutions of polynomial equations of higher degrees in algebra are complex systems, according to Wolfram, and therefore there can never be a solution for them. The only thing we can do, is to run the program and witness its evolution.

The Principle of Computational Equivalence creates more problems than solves. And this, because, it poses strict limits on what we can learn and what we cannot. However, on the other hand, Wolfram, through the study of simple rules and complex systems, tries to create a new kind of research. While, like we said above, complex systems are irreducible, Wolfram proposes that we should do pure NKS (New Kind of Science). That is, to study computational programs as they are, without any direct reference to something, pretty much like we study mathematical equations and functions, without any direct reference to a system.

The book leaves many questions unanswered, since Wolfram doesn’t clearly explain how this would exactly help us to create better models of reality. So, let’s be a little more specific in this article, by providing some thoughts on this framework.

Let’s take the case of agent based models. It is obvious that these are computation models. However, all agent based models are based on parameters that can become even more complex as the models advance. What if, as Wolfram proposes, these systems are governed only by a set of simple rules and the interaction with the environment. These rules, if Wolfram is right, will be simple than the zillions of rules computer scientists tend to use in complex simulations.

Agent based modelling

This would essentialy mean that we could create a new kind of social science, where we are not based on any human notion, but rather on simple rules. Additionaly, what Wolfram proposes, these rules could be abstract representations, like mathematics. A function can be used in econometry, but it can also be used in physics. If programs, like the ones Wolfram proposes, are indeed ubiquitous, then we could use them to analyse, and predict, social procedures, without caring about specific notions.

So thing for example, of an artifical community, where it advances via simple cellular automaton rules on a grid that represents a certain geographical region. If what Wolfram proposes is correct, maybe we could create a simulation of the core of evolution of this society, just based on a few simple rules.

I don’t know if this idea holds any truth, but it is certainly interesting. It actually proposes that we can formalize the study of social systems with computational programs that hold no inherent meaning. If this is true, then it could mean a revolution in social sciences, which, probably, hold the greatest envy towards physics, than any other sciences, because of the complete lack of any formal framework of research or methodology.

However, what really concerns me is the degree of accuracy between abstract computational models and real life. So, for example, while simple rules can generate complexity, we can’t be sure if a certain set of rules is enough to create some specific kind of complexity.

When modelling car traffic for example, we don’t simply care about finding a bunch of simple rules that create complex behavior, but, rather, we want to find rules that create complex behavior that is like the one we observe in real life traffic.

It is actually a question between general complexity and specific complexity. If general complexity is just the fact of a system being complex, specific complexity represents the fact that this system can provide an abstract, but accurate representation, of a specific process.

Let’s consider, for example, every system as a computational one, just like Wolfram proposes. We can think that are brains are performing computations or the weather performing computations, as they represent systems that interact with their environment based on a certain set of rules.

Then, we can say that the system of car traffic holds general complexity and is specifically complex to the system of car traffic. This means that it represents itself and is tautologous, pretty much like proofs in logic and mathematics.

However, rule 184 has often been used to represent traffic. It is generally complex, but it is not specifically complex to any specific traffic of any specific city.

Therefore, the question of whether we can implement A New Kind of Science in social sciences, is how specific our generally complex models can be.

Further Reading:

A New Kind of Science Online

What is a cellular automaton: http://mathworld.wolfram.com/CellularAutomaton.html

The NKS Blog: http://thenksblog.wordpress.com/

Hi there guys It’s been a long time that I haven’t written an article. The reason is that I have SO many things to do, that I really don’t have the time to update all my projects as often. Between my new projects, like Raskolnikov’s Dream and Musikality Net, I had to deal with university exams, as well! But, as you see, I still post updates when I can

Today, we are going to talk about a concept I was thinking about the other day. That concept is called the "E" factor.

The E factor is a concept I created to describe evolutionary fitness. Evolution is a pretty simple theory. It revolves around only survival and reproduction. However, there has never been a single factor that determines the evolutionary fitness of an organism.

Of course, the reason is simple. Evolution, while a simple theory, describes a complex procedure. Let’s think for a moment about IQ for example. IQ is a scale that psychologists never actually managed to describe what measures exactly. There is also the so-called g factor, which determines general intelligence, and has been related to all sorts of stuff, but never has there been any real definition of what this "g factor" actually is.

The same goes for the E factor. Could there be an E factor? And how can we define it?

Pretty complex stuff

Let’s start by hypothesizing that the E factor is not a quantitative value. How can we know that an organism has a high or a low E factor? The easy answer would be to say, that once an organism has lived its life, we can deduce that if it reproduced successfuly, it has a high E factor, otherwise it does not.

However, this would be the logical fallacy of petitio principii, or cyclical argument. This means that we know that something has a high E factor, because it survived and we know that it survived because it has a high E factor. This is absolute non-sense. Our E factor should allow us to predict whether an organism has chance of surviving and what is that chance.

In order to calculate that chance, we start with the simplest case possible: we ask the question if this organism has a probability greater than 0% to survive. This would allow us to give an E factor of "0" to all organisms without a reproductive system. Of course, nowadays we got nasty things like cloning and stuff , but for the argument’s sake we have to keep it simple.

Now, how could we determine the chance of an organism surviving and reproducing, that is, its E factor? He would have to get all the factors down, calculate them and use computational approaches to find the result. However, this seems somewhat improbable to happen. It looks like the equivalent of the determinists’ dream of the 19th century that we could determine the course of the universe.

Nevertheless, an E factor is an interesting philosophical idea. First and foremost, concerning evolutionary psychology. Should we be able to identify an E factor, maybe we could validate the theories of evolutionary psychology. Furthermore, we could determine the evolutionary efficacy of behaviors as they happen.

Maybe not only that, but the very idea of an E factor, can help us contemplate which behaviors help us adjust to our environment and which ones don’t. Many of the behaviors that we deem in high esteem, are culturally promoted, while others, are shunned upon. However, the shunned ones, might be a lot more adaptive than the promoted ones.

For example, let’s compare and contrast two different cases: A geek with a Phd and a playboy bunny. Alright, this is the clash of the century

The Phd geek, has a lot of studying to do. He must miss many parties, and many opportunities to find mates. However, he is willing to sacrifice all that in order to become a university professor. This feat requires an above the average intelligence, discipline and concentration.

On the other hand, the playboy bunny, is simply beautiful by society’s standards. She doesn’t really have many things to do. She just participates in a few contests, or photos, and BANG, she earns more money than the guy above.

VS 

What this could mean, is that while intelligence and education are highly-esteemed in our society, beauty might be all more important. The problem that most people face however, is that beauty is a genetic gift, while qualities like intelligence and discipline, are thought  to be more flexible (even though they might not really be).

Maybe it is a self-esteem mechanism like the one that Leon Festinger proposed, that works here. However, should we have an E factor, maybe we could see that our playboy bunny really owns the professor

One nice thing about evolution, is that it is a nihilistic theory. It really doesn’t matter who you are, or what you do. There is only on law: survival and reproduction.

All of society’ structure can easily crumble down like dust in the face of evolution. However, every scientific explanation crumbles down like dust as well, in the absence of evolution.

That’s one nice reassuring thought. You can see disputable things like art under a new light, through evolution. For example, it is a fact that each one has his own taste about art. Maybe some people dislike it all together. You have surely participated in meaningless conversations about who is the best singer/painter/actor/anything.

Evolution might help you understand that all this really doesn’t matter. Art was for the artists a means of increasing their E factor. Ancient art that can now be found in museums, is a way for a bunch of other guys to increase their E factor: art professors, art lovers and museum security guards

A nice attempt to increase one’s E factor

I find this kind of thinking really liberating. Marx for example had created a social theory of everything based on the struggle of classes and economy. Freud tried to create a social theory of everything based on his dark mechanisms of the subconscious. Why not create a theory of everything based on evolution?

After all, evolution doesn’t constitute a simple theoritical model through which we face a set of events.

Through the theory of computation, most theories impose a certain set of simple rules, which we have to discover and let the whole thing compute itself to find the similarity with reality in order to test and validate our theory.

Evolution describes a process. It not based on equations, but rather on the fact that some agents survive and reproduce and some do not. Evolution doesn’t predict, it describes. We are the ones who have to try and make the predictions based upon a theory of E factor.

Therefore, I believe evolution to be much more valid than the social theories above.

Maybe a social science of an E factor is all we really need after all

Of course many will say that evolutionary psychology does exactly that. I disagree, because evolutionary psychology is based on the premise that old behaviors, held by our ancestors, are still alive in our genes today. What a science of the E factor should do, is to alow the study of evolutionary adjustable behaviors as they happen, not on hypothesis on the past. It is a study of the social evolution of present, not of past adjusted to the present.

So, I hope this article increased your E factor

This little lolcat is happy after it increased its E Factor

Sorry for not having written for so long time, but I literally have SO many things to do, especially with my new projects, that I really don’t have time for anything!

Anyway, I am writing this post to comment on an article I found on Scientific American: Exploring Consciousness through the Study of Bees

This article is written by Christof Koch. If you remembered we have dealt before with him in past articles (Introducing Scholarpedia and the Neural Correlates of Consciousness)

Christof Koch

Christof Koch is neuroscientist whose main interest is consciousness. In this article he presents the following argument. We don’t have a complete theory of consciousness, so we should follow an agnostic approach on the subject, since we can’t say for sure which things posess a consciousness and which do not.

His discussion starts with bees. We all consider insects to be utterly stupid. After all, insects are so much different than us. They are small, they have a different social structure, since they are not mamals, and their appereance seems alien to us.

Nevertheless, they are capable of some interesting feats

Bees live in highly stratified yet flexible social organizations with group decision-making skills that rival academic, corporate or government committees in efficiency. In spring, when bees swarm, they choose a new hive that needs to satisfy many demands within a couple of days (consider that the next time you go house hunting). They communicate information about the location and quality of food sources using the waggle dance. Bees can fly several kilometers and return to their hive, a remarkable navigational performance. Their brains seem to have incorporated a map of their environment. And a scent blown into the hive can trigger a return to the site where the bee previously encountered this odor. This type of associative memory was famously described by French novelist Marcel Proust in À la Recherche du Temps Perdu.

Our new conscious friend…

Koch presents a very nice argument here. Our criteria about what is conscious and what is not are highly subjective and instictual. His argument calls us to take a look at the functions and the structure of the species that we know that have consciousness (this is us) and compare it with that of other creatures (like bees).

Based, on this new criterion, we don’t have any reason not to accept that bees have consiousness. On the other hand, we don’t have any reason to accept that bees have consciousness. And this for two reasons: Bees can speak to us, to ascertain our hypothesis and, secondly, we don’t know of what use consciousness would be to the bees.

However, these arguments are not absolutely right. Concerning the first argument, we can’t take communication as a proof of consciousness. A possible artificial intelligence life-form could communicate with us, but this wouldn’t mean that it is conscious.

The second argument is a little trickier, since we don’t know in what consciousness is useful. Maybe consciounsess is useless and it is just an epiphenomenon of neural processes.

Furthermore, we can’t even rule out the case of zombies, which connects the two arguments. The zombie-case in consciousness makes the assumption that a being that we consider conscient, let’s say another human, is exactly as it is, but doesn’t have consciousness. If such a creature could exist, then we maybe we could accept that consciousness is just an epiphenomenon, and it is useless. We would also be sure that communication would not mean that a creature is conscious, even though we have verified this hypothesis with the AI argument above.

The undisputable future of neuroscience…

So, we are at the point we just began this conversation. We don’t know jack about consciousnes , and so, we don’t any reasons to accept or reject the hypothesis that bees are have consciousness and are our friends .

However, at this point I want to make a connection with an older post: Can computation be the answer? The violation of the second law of thermodynamics

At this post, we had talked about Stephen Wolfram and his approach to science that circles around simple systems and cellular automata. If simple systems can describe the neural networks that govern our brains, maybe they could explain the existence of consiousness as an emergent phenomenon.

Complexity out of simplicity

Cellular automata are characterized by the fact that by a set of simple rules, complex patterns emerge. This explanation doesn’t require consciousness to be evolutionary adaptive (even though it might be). It doesn’t require consciousness to perform some special functions. It only requires that neural networks are governed by some simple rules, and these rules eventually, seem to give rise to the phenomenon of consciousness.

So, that was it for today! Until next time, try to be more gentle with the little bees. They might conscious you know!

As you may know, I also run two more projects, besides Encefalus.

I am a musician, not only a psychologist, and my first project, can be found here: Raskolnikov’s Dream.

It is a melodic electronica project. In the official site you will find more information and you will be able to listen to samples of my music.

The other project I am currently running is Musikality Net, a blog with resources for independent musicians, including articles and tutorials on various, subjects like music theory, software and promotion.

I’d be very happy if you could just pay a little visit to see what these are all about

I found this interview in scientific american the other day: Inside the Savant Mind: Tips for Thinking from an Extraordinary Thinker

This interview is with Daniel Tammet, a world-known savant.

Daniel Tammet

For those of you who don’t know what a savant is, they are autistic people with extraordinary abilities. If you’ve seen the film Rainman, then you’ll understand what we are talking about. Dustin Hoffman represents in the movie the archetype of a savant. In fact, this movie was based on a real savant, Kim Peek.

The savant syndrome is defined by wikipedia as follows

Savant syndrome—sometimes abbreviated as savantism—is not a recognized medical diagnosis, but researcher Darold Treffert defines it as a rare condition in which persons with developmental disorders (including autism spectrum disorders) have one or more areas of expertise, ability or brilliance that are in contrast with the individual’s overall limitations.^[1] Treffert says the condition can be genetic, but can also be acquired,^[1] and coexists with other developmental disabilities "such as mental retardation or brain injury or disease that occurs before (pre-natal) during (peri-natal) or after birth (post-natal), or even later in childhood or adult life."^[1]

According to Treffert, about half of persons with savant syndrome have autistic disorder, while the other half have another developmental disability, mental retardation, brain injury or disease. He says, "…  not all savants are autistic, and not all autistic persons are savants."^[1] Other researchers state that autistic traits and savant skills may be linked,^[2] or have challenged some earlier conclusions about savant syndrome as "hearsay, uncorroborated by independent scrutiny".^[3]

Random image I found by googling "savant", apparently referring to a pen and paper rpg

What is so interesting about savants, is that while they have deficits in some basic areas of functioning, they have abilities, that the average human, can never be able even to approach. So, for example, Daniel Tammet which we cited above, has completed the following feats

• He holds the European record for reciting pi from memory to 22,514 digits in five hours and nine minutes
• Tammet claims to speak eleven languages including English, French, Finnish, German, Spanish, Lithuanian, Romanian, Estonian, Icelandic, Welsh, and Esperanto.
• He learned Icelandic in one week

He is also a synesthetic, which means he has some of his senses tangled together. To make things clearer, Tammet, actually, (citing wikipedia) "experiences every integer up to 10.000 as having its own color, shape, texture and feel". He can "sense" whether a number is prime or composite. In his interview in scientific american he says

TAMMET: I have always thought of abstract information—numbers for example—in visual, dynamic form. Numbers assume complex, multi-dimensional shapes in my head that I manipulate to form the solution to sums, or compare when determining whether they are prime or not.

For languages, I do something similar in terms of thinking of words as belonging to clusters of meaning so that each piece of vocabulary makes sense according to its place in my mental architecture for that language. In this way I can easily discern relationships between words, which helps me to remember them.

In my mind, numbers and words are far more than squiggles of ink on a page. They have form, color, texture and so on. They come alive to me, which is why as a young child I thought of them as my “friends.” I think this is why my memory is very deep, because the information is not static. I say in my book that I do not crunch numbers (like a computer). Rather, I dance with them.

None of this is particularly surprising for me. I have always thought in this way so it seems entirely natural. What I do find surprising is that other people do not think in the same way. I find it hard to imagine a world where numbers and words are not how I experience them!

Timothy B Layden-Synesthesia 2007 

So, in Tammet’s mind, information is not abstract, but visual, and, in some strange way, "concrete". What is so amazing about synaesthesia, is that we can have no clue about what it feels like to be like that. It is a phenomenon that belongs purely to the hard problem of consciousness(Split Brains, Consciousness and Michael Gazzaniga). The feelings and procedures that accompany Tammet’s mind are unaccessible to us in a direct level.

Daniel Tammet, however, as a highly function autistic, gives us some descriptions of what is going on inside his mind, as in the interview cited above, but in no-way can we ever really "feel" what it feels like to be him.

All these abilities, however, come with some disorders. Tammet also suffers from Asperger’s Syndrome and epilepsy. Asperger’s Syndrome is a highly functional form of autism. It so highly functional, in fact, that many people can suffer from this syndrome without them or the others, ever realizing it. People with it can just be considered as eccentrics or strange, while not knowing that they suffer from it, can make their lives more difficult, while, however, allowing them to function in a modern society.

Hans Asperger

The savant mind is one of those cases that you know you’ve just stumbled upon something important. Savant minds break many of the barriers of human intelligence, and of the limitations we think that exist, because most of us live with these limitations. While many geniuses throughout time, like pop icons like Albert Einstein, have made discoveries that to most of us seem difficult to grasp, the thing that is amazing about savants, whatsoever, is that their skills are not focused on discoveries, but on raw ability.

However, while the savant mind, obviously causes awe, there are almost no clues, on what is really going on inside their brain to produce such results. Daniel Tammet has a theory of his own which he presents in his interview in Scientific American

LEHRER: You advocate a theory of creativity defined by a cognitive property you call "hyper-connectivity." Could you explain?

TAMMET: I am unusually creative—from visualizing numerical landscapes composed of random strings of digits to the invention of my own words and concepts in numerous languages. Where does this creativity come from?

My brain has developed a little differently from most other people’s. Aside from my high-functioning autism, I also suffered from epileptic seizures as a young child. In my book, I propose a link between my brain’s functioning and my creative abilities based on the property of ‘hyper-connectivity’.

In most people, the brain’s major functions are performed separately and not allowed to interfere with one another. Scientists have found that in some brain disorders however, including autism and epilepsy, cross-communication can occur between normally distinct brain regions. My theory is that rare forms of creative imagination are the result of an extraordinary convergence of normally disconnected thoughts, memories, feelings and ideas. Indeed, such “hyper-connectivity” within the brain may well lie at the heart of all forms of exceptional creativity.

Kim Peek, the real "Rain Man"

While the theory is a psychological one, and it is highly interesting, nevertheless, I believe that when we encounter such amazing feats we also have to look into the brain in a neuronal level.

Cognitive psychology has always proposed a module theory of mind, meaning that the mind (and the brain thereafter) is seperated into different modules, that complete different functions. This could explain why savants can show extraordinary abilities on one domain, while impaired on others, since these domains, according to the theory, are not connected.

However, this doesn’t explain how savant abilities are formed in the first place.

The only thing we can say for now, is that savantism, is one the most amazing phenomena of the human brain. We can only hope that future research will shed more light into this.