Non-Linear Thinking and Structures

The Design and the Designer – Part 5

In the last post, I made a brief mention of Nasruddin, Heuristics and Non-Linear Thinking. I shall continue in this post on the same theme and establish the role of semantics in Design and Non-Linear Thinking, and explore some techniques of practicing non-linear thinking.

First, here is a very brief synthesis of the previous posts on this subject: In the previous posts, I applied law of 2 and tried to demonstrate the underlying unity of the theme in various disciplines – which is referred to as Plausible and Demonstrative, Creative and Logical, Synthesis and Analysis, Right Brain and Left Brain, Linear and Non-Linear, Heuristic and Rational and so forth. Largely, the conclusion that one can reach is that there are two distinctive types of thinking – which are interdependent on each other, but at the same time have very different functions and applications. We termed the functions of these two types as – recognition of problems and finding solutions to problems. We also presented a few laws of synthesis – from various fields – particularly societies, management, computing science and consciousness.

Before we get into Semantics, let’s examine linear thinking and non-linear thinking in some detail – with some examples and techniques of how to switch from one to another.

Logic – at least the way Socrates and his disciples developed it – is largely linear. This is carried over into mathematics as well. Logic mostly depends on reasoning from evidence. The early Artificial Intelligence (which is neither artificial nor intelligence) applications ran into some problems with the linear reasoning and there are now several attempts to develop non-linear reasoning systems. Such logics in AI are called “non-classical” reasoning systems. Here is a classic example of linear and non-linear reasoning – it involves a very well known logic puzzle.

Three monks and three cannibals were traveling together because of some strange circumstances – even though naturally there cannot be any friendship and trust among such a diametrically opposite groups. If at any time, the cannibals outnumber the monks – they will eat them. Now, they came to a river bank and they had to cross the river. There was only one boat. The boat can only carry two people at a time. Now, your problem is to devise a strategy to transport the monks and the cannibals safely across the river.

The usual linear reasoning system will start with River Bank-1: 3M, 3C, River Bank2: 0M, 0C as the initial state of the system, and will try to devise a series of moves that will establish the desired final state - River Bank1:- 0M, 0C, River Bank2: 3M, 3C. It is a simple puzzle – you start with something like first two cannibals will travel, one will come back, two monks will then go etc., and you can easily arrive at the final state.

Suppose you give the problem to Nasruddin, what do you think he will do? He will listen to your descriptions, and even before you have completed your narration, he will jump from his chair and shout with the excitement of a child “I know, I know - the monks will take the bridge, and the cannibals will take the boat”.

It is a perfectly valid solution to the problem – isn’t it? Then you tell him “look Nasruddin, I did not say that there was a bridge”. Nasruddin will reply, “Well – you did not say that there was no bridge either”. Now, you modify the problem description, and you will add another constraint to the problem – there are no bridges. “Well, in that case, the monks take the helicopter” will be Nasruddin’s answer. By this time, you get very frustrated and shout back at him – “I want you to solve the problem – not avoid it”. But, for Nasruddin, there was no problem there to be solved. Can you see how he eliminates the problem instead of trying to solve it?

No matter, how hard you try, you cannot contain Nasruddin. He will always think of exploiting some constraint that is not included in the problem definition and use that as a means to eliminate the problem.

The AI community in the last thirty years tried and discovered several techniques for “programming Nasruddin type behavior” into the computer programmers – with some reasonable success. I have no intention of boring you with the Non-Monotonic Reasoning systems here. But what is the technique of Nasruddin?

One, Nasruddin does not depend on “evidence” as the only way of establishing the existence of something. All formal logical systems depend on evidence as the only means of establishing “truth”. For example, if I tell you that all visitors from Canopus are fools, and you know that Mr. X is a visitor from Canopus, you can confidently establish the truth that this particular Mr. X is a fool. But, there is a catch. Suppose, if this particular Mr. X is not a visitor from Canopus, then what are you going to do? You cannot establish anything. He may or may not be a fool. You can conclude Mr. X’s foolishness, only if you know that he is a visitor from Canopus.

We need facts to recognize truth, but Nasruddin does not rely on such petty things like facts to recognize truth. According to Nasruddin, some thing does not have to be a fact for it to be true. Kurt Gödel proved this mathematically – it is known as Gödel’s incompleteness theorem. The incompleteness theorem states that in any formal system, there always exists a statement which is “known” to be true, but cannot be proved.

Rabindranath Tagore – with the brevity that a poet alone can command – says it beautifully.

“If I say that the earth is flat – you inform me that my near sight is false.
If say that the stars are the fireflies attracted to the moon, the candle of the sky – you inform me that my far sight is false. My dear logician – in your presence, I prefer to be blind”.

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The second principle that Nasruddin mastered is the System’s Principle – understand the problem by studying its relationship to the larger environment in which it is only but a part. I wrote about this principle in part 2 of this series of articles.

In the specific case of monks and cannibals – all Nasruddin does is to bring his knowledge of the larger environment to solve the problem. The minute you tell him about the river and the boat, he can think of a bridge. He can bring his knowledge of traveling in the air, or swim in the water. Or, he will say that the monks – using their magical techniques – will vanish and reappear on the other side. Or, he will say that the monks will use their secret herbs and put the cannibals to sleep. His possibilities to come up a solution are infinite.

The study of system level relationships requires knowledge of semantics – or the “meaning” of things. There are basically two types of relationships – structural and semantic. It is important to distinguish between these two types of relationships. Though, in logic and other sciences, we are mostly taught how to study the structural relationships, in fact, our mind works naturally very well with semantic relationships.

A few examples from various fields may be in order here.

In language, grammar defines the structural relationships. In English, a valid sentence must have a subject, a verb, an orbject/predicate. And, there are various rules that define the relationships between various parts of speech. These relationships are basically structural – they govern the structure of the sentence. We can say that water is triangular – it is a grammatically valid sentence, but completely meaningless.

In information systems there are basically four types of structural relationships. By information systems I do not mean just software applications. Any system that organizes knowledge and depends on that organization is an information system. By this definition, societies, cultures, various disciplines of study are all information systems.

The first – and simplest structural relationship is hierarchy. This relationship in information systems is called “IS-A” relationship. A “IS-A” B. This could be interpreted in several different ways:

• B is the parent of A
• B is the boss of A
• B is part of A
• B is subsumed by A
• B is the root of A

Entire systems, organizations, societies are modeled based on this one particular relationship. Most hierarchical structures use this relationship as the primary relationship. The different sections in this blog-page have a parent-child relationship with the master page. There are basically five sub-sections – header, footer, posts, author information, archives – each of them is a “child” of the main blog page. Similarly, many corporations have a hierarchical structure – with the owner of the corporation at the top. The “semantics” of this relationship connotes ownership and protection.

The second structural relationship is network relationship. In such a structure, elements, or objects at the same level can be connected. This is called “sibling” relationship. A “IS-A brother of” B. The relationship basically means that two things are at the same level. It connotes competition and/or collobaration.

There are two other types of structural relationships in information systems hyper-text and groups. Both these relationships are somewhat non-linear relationships, but nonetheless, they are structural relationships.

The Set, and Hyper-Text are more complex structural relationships than a simple hierarchy and a Network. A set uses a function to create a structure. For example, you can say that all integers belong to a set. You can then define a function that determines an integer and therefore, the membership to the set. The members in the set may not have any particular relationship – they have something in common – that’s all. This is how most social groups are formed. The function gives an identity to the set and therefore to all its members. All people “born” in US are “Americans”. “Being born” in the US determines the identity of the set called Americans.

A Hyper-Text relationship is much more interesting relationships. It does not relate two nodes, but instead it relates content from one node to another node. All web pages use this structure extensively. For example, I can provide a link to an article in wikipedia in one of my articles in this blog. This does not mean that this blog as a whole and wikipedia share any relationship; it also does not mean that this article and the wikipedia share any relationship, and it also does not mean that this article as a whole has any relationship to that article in wikipedia. This relationship connotes friendship. There is no function, there is no responsibility, and there is no ownership in this relationship.

Using these four relationships, we can explain almost all “order” in our world. We defined the basic family relationships (parent-child, sibling), groups and friendships.

So, where is the place for Semantic Relationships?

We conveniently left out the most important, most complex, wonderful, problematic and the most beautiful relationship of all– that of the lover and the beloved. None of the above relationships explain that relationship – do they? What is the relationship of a husband and wife? What is the relationship of a teacher and a student? Friendship comes closest, but these relationships transcend friendship.

This is the realm of semantics – which is the topic of next post.

Non-Linear Thinking, Nasruddin and Polya

The Design and the Designer – Part 4

In these series of articles on Creativity and Design, my intention is to explore if there is a “formal” model of creativity. I am not interested in the psychological aspects of creativity, how it works and so on. The Psychology of discovery and invention is wonderfully described by Mihaly Csikszentmihalyi in his classic book called Creativity.

My interest is to discover a method of consciously practicing it. In the last few posts, I tried to provide a basic framework that I am working on. Basically I am trying to bring together all my experience under one unified theme. Design is the name I gave it.

I studied mathematics and more importantly I studied how to ‘do’ mathematics. I studied computer science and information systems – I designed some very large and complex software systems. I studied design theory – product design, appliance design, communication design, aesthetics, user interfaces, ergonomics etc. I studied philosophy – Western Philosophy, Indian Philosophy and Sufi Philosophy. I studied systems thinking. Basically I am a problem-solver. Given any problem, I can come up with some kind of a solution. I met many people who are fantastic problem solvers. Many of these people can almost instantaneously identify a line of attack and can come up with a solution almost immediately.

In my experience, problem-solving can be taught and can be learned – even though we generally think some people are gifted with this ability. But, teaching problem-solving has been one of the toughest problems for the teaching community. There does not seem to be a discipline for teaching problem-solving. Even the most beautiful subject – mathematics – has not addressed this problem.

How are we taught mathematics? The mathematics teacher presents the proof of a theorem in a step by step manner. First, he defines the theorem, and he has the proof in front of him, and all the teacher does is to explain the ‘logical flow’ of the proof. In the course of several years, various problems and solutions are demonstrated as examples, and somehow the student is expected to ‘understand’ problem-solving from these examples. There is no conscious attempt at teaching problem-solving.

The ‘doing’ of mathematics is not taught. This is what makes Mathematics difficult to learn for many people. The best reference works ever written about this are Polya’s books on mathematical method: How to Solve It and Mathematics and Plausible Reasoning. For some strange reason – these books are not part of the mathematics curriculum.

Polya makes a very useful observation. According to him – rightly so – the process of problem solving is a heuristic process. The difficult part of problem solving is to ‘recognize the problem’ correctly. This recognition is not a “rational”, “logical” process. It is very irrational – if you are good at it – you can immediately recognize what the problem really is in an instant, and you decide on the line of attack. How do we normally recognize the problem? We generally use a set of heuristics. For example, you may recognize that the problem is “similar” to another problem you solved before, or you may recognize that the problem belongs to a class of problems that are already solved and so on. These are all heuristics.

Here is an illustration of how heuristics are applied. Archimedes first discovered the formula for calculating the area of the circle. The area of the circle is PI*r2. In Mathematics texts, the proof is presented using some complex coordinate geometric equations. Archimedes proof is rather very simple and can be explained in one line. He drew several lines from the center of the circle to its circumference. Now, the area enclosed by two such lines and the arc of the circle looks like a triangle. The area of the triangle is (base*height)/2. Now, the height in this case is r. And, the base of all the triangles put together is the circumference of the circle – which is 2*PI*r. Therefore, the area of the circle is PI*r2. Beautiful – isn’t it?

A mathematician will not agree to a proof like this – because, the way Archimedes divided the circle into different regions are not exact triangles – they only look like a triangle. Archimedes used a heuristic.

Now, let’s look at the process that Archimedes used to solve this problem. First, for Archimedes, the problem of calculating the area of a circle is a real problem; it is not a theoretical problem. He had to calculate the area of agricultural land for calculating taxes. Second, given a particular circle, he knew how to come up with answer. So, he has some data in hand. He has the areas of different circles in front of him and he was looking for a common “pattern” that explains all the answers. Third, he knew that the two fundamental properties of the circle are its radius and its circumference. The last step is the important one. He asked himself a question – can I formulate this problem in terms of problems that I already know how to solve? In other words, he knew how to calculate the area of a square, a rectangle and a triangle. Now, he is trying to “reduce” this problem to the problem of a square, a rectangle or a triangle. He also knew another important fact about areas – they are always expressed as a product of the two different lengths. He used four different heuristic techniques – generalization, analogy, reduction and induction.

Polya calls this type of reasoning “plausible” reasoning as opposed to “demonstrative reasoning”. Different disciplines may have different names for this. Psychologists call it right brain thinking, designers call it creativity at work, scientist call it intuition at work, systems people call it “systems thinking”. In popular literature, this is called “non-linear thinking”, “out of box thinking” and by many other similar names.

No matter what name you give it – the process of recognizing the problem, and the process of actually solving it involve two different kinds of thinking altogether.

Polya’s books are the best reference works on this subject. He tried to formulate a systematic method of “problem-recognition”. Unfortunately – thanks largely due to the American experiments with modern mathematics – the world today suffers from cultural isolation of mathematics. Polya’s achievement is remarkable. With the precision of a mathematician, he formulated a “dictionary of heuristic”. This means – if you have some patience – you can learn the heuristic thinking like learning the vocabulary from a dictionary.

Another dictionary of heuristic that is particularly enjoyable to read is the collection of Nasruddin Stories. These stories help us to break our usual linear and cause-effect thinking. Even just remembering the stories has the remarkable effect of constructing a different kind of associative memory. The stories ‘just’ pop up by themselves when we need them most.

More than 700 tales of Nasruddin are collected by Idries Shah and are published by Octagon Press. Here is one story of how Nasruddin describes the “two modes of thinking” that we have been talking about:

One day Nasruddin stormed into the tea house and announced with lot of excitement that he discovered a very important truth.

People asked him what it is.

Nasruddin said – “The moon is more useful than the Sun”

Everyone was taken aback, and asked him why he thinks so.

“Because we have more need for light in the night”

Nasruddin Stories make sense at many levels, and it is said that there are at least seven interpretations for each story. Here is one interpretation that is relevant in our context. Moon is the agent of synthesis. He synthesizes the sun light and reflects it back to earth. Sun is the source of light – when he is there – we have no need for light because it there everywhere. Your need is more when something is not available – right?

There are people who are experts at synthesis. Polya synthesized mathematical method, Will Durant synthesized history, Ackoff synthesized management, and Christopher Alexander synthesized Architecture. I am trying to synthesize Design. In order to synthesize a domain, you need to be a super-specialist in that domain and you need to be able to absorb the entire domain completely.

Both modes of thinking co-exist and compliment each other. I am not indicating that synthesis is more “important” or “superior” to analysis. Like the Sun and Moon, they are interdependent on each other. The linear and the non-linear, the creative and the logical, the plausible and the demonstrative co-exist together.

In order to synthesize Design – we need an understanding of Semantics. We have to understand the meaning of things, and how different things relate to each other.

This will be the topic of the next post in this series of articles.

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Nasruddin on cause and effect:

One day Nasruddin was waling along a street with his students. As Nasruddin was walking past a two story building, a man fell down from the first floor – and he fell on Nasruddin. Nasruddin’s neck was badly hurt.

His students asked him what lesson they can draw from this incident.

Nasruddin was in pain and he was now angry at such stupid questions. He shouted – “fools – can’t you see? He falls from the building, and it is my neck that is broken”.

The Joys of Freelancing

Many people ask me how to become a successful freelancer and how and why I became one. Most often I had to repeat the same story with some variations every time. So, I thought it wouldn't be a bad idea to write a small note on "Joys of Freelancing". Later, it struck me that it is an ideal opportunity to experiment with Fiction.

This is my first attempt at writing fiction. Let me know what you think.

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Chapter One

In the summer of 1999, we moved from California to India. The reasons for relocation seemed quite obvious - at least and strangely - only to us. My wife Padma and I work in the technology industry – we were in the land of opportunities for more than three years by that time, and both of us fared reasonably well. That was the time of the dotcom era – everyone was really mad - bordering on the insane. The whole of Silicon Valley was buzzing with activity. We used to work sixteen hours every day, at least six days and almost seven days a week. The family life was non-existent at the least, every one would talk about stock options, career jumps, number of patents filed, products that they developed, hundred percent salary hikes, the newest swanky cars that they bought etcetera, etcetera. The only break from this routine is when some friends call you for lunch and they would invariably throw in their wedding video for free, and gently insist that you watch it.

In short, we were a bunch of boring people. We were ashamed to look at ourselves in the mirror each day morning – we looked like zombies. Once in a while life gets boring and that can be managed, but the worst thing to happen to a human being is when he becomes a boring person. There is no story to tell – imagine what a nightmare you have come to become if the only thing that you can show your friends is your wedding video!!

But the Wedding Videos had a concealed message for us. The people in India seemed interesting, happy, boisterous, cunning, good looking and even charming. I wanted to be in the video – not watching it. I wanted a part of that action. So, one fine day, just like that I snapped my fingers and decided that it is time to go back home.

I had to communicate and then convince my wife. It is easy for captain Picard to say their mission is to “boldly go where no one has gone before”, but how do you tell your wife that you are about to “do boldly what no one had done before”? I knew instinctively that it was not going to be easy. She has an inherent mistrust when it comes to my radical ideas that disturb the already well established family rhythm. She can touch my ideas like a spoon dipped in honey. She will then take it out, drip it off the honey patiently, throw it into the dish washer and set the washing temperature to one hundred degrees Celsius. So, if one reason is sufficient to convince my friends, I need a million reasons to convince her and plus one more.

I thought about it carefully for a couple of hours, rehearsed it many times in my mind. Padma was busy in the kitchen. I slowly got up from the sofa in the living room, went to the kitchen walking like the ET. I cleared my throat a couple of times. “I have been thinking about this for quite some time now. I am now convinced. We are going home” I said as sweetly and as resolutely as I can.

She didn’t pay any attention. I repeated again. She seemed to consider it and I saw a flicker of pleasant thoughts shine in her eyes – I was hopeful. “I also want to go home, but it is impossible to get a vacation now” was her first response. Then I had to break the bad news. “No, not for vacation!! I mean we are going back for ever, for good, permanently, never to come back again”. She dismissed me with a simple “Okaeey. We will think about it. What is the hurry?”

For the next couple of months, we had many arguments, discussions, different points of view, and counter points of view. Padma’s logic is very simple and straight forward. Her point is we made such an enormous effort in coming to US, we were there just for about three years, just settling down to that life style, we just bought a car, both of us had very good jobs – both from a work content, and salary perspective, and we just started to see some real savings. She never wanted to settle in the US, but she wanted some more time. On my part, I had no logic at all – only a very deep, inner need to get out of that mad place, and an instinct that it is the right thing to do. May be she was right – but, I didn’t want to find out. More and more reasons only strengthened my determination. For once, I was the instinctive wife and she was the logical husband. Finally she relented and even convinced of it herself.

To be continued ... though I don't know when I will get around to write the second chapter.

Innovation and The Principle of Inversion

The Design and the Designer - Part 3

In the last post, I made an observation that the design of complex products has a higher probability of success than the design of really simple applications. I believe it is an important principle from the context of creativity and the modern professional design.

If you are a professional designer – you may not get a contract to design a Stethoscope. Most certainly you will not get a contract to ‘design’ a new mathematical concept. Such things are innovations by the experts in the same domain. So, there is a well defined line between ‘revolutionary concept’ and ‘improvisation through innovation’. Most professional design today is more or less improvisation. It all begins with some one being able to specify what the need is and there already exists the product in some form or the other.

Most designers may take offense with a statement like this one. But, let me explain.

Something like a Fountain Pen, Printing Press, and Stethoscope are not simply products, but they are very fundamental concepts. Coming up with a new concept is a much harder task. Let’s call this creativity of the highest order. Or, let’s simply say that it requires genius. I really do not know how this works.

Next comes Innovation. What is innovation really? A Russian scientist (I forgot his name) studied this subject in great depth. He analyzed more than 20,000 patents to understand what innovation really is. And, he came up with a very beautiful definition:

“Innovation is eliminating an inherent contradiction”.

Suppose you were living in the late 19^th century and you were working for an automobile company. You are asked to design a car with two contradictory parameters – performance and fuel efficiency. This means that the engine should be powerful enough, but at the same time it must also consume relatively less fuel. Common Sense dictates that as you increase the speed of the car, you have to give it more fuel to keep it running faster. You break your head for some years, and finally you come up with the design of a gear-box as a solution. As the speed increases, the engine has to do less work there by reducing the fuel consumption. This eliminates the ‘contradiction’ that existed between two design variables. From here, you can do many improvisations – like use light-weight materials for the body of the car and so on. (My understanding of the internal workings of an automobile is close to zero. Therefore, my explanation of the gear-box may be technically wrong. But, I am just making a point that everyone can relate to.)

Many of the famous algorithms in computing science work on the same basis – a really good algorithm is the one that ‘maximizes performance’ on two counts – speed and storage requirements. In general, in computing science, speed and storage can be mutually traded for each other. This means that if you want more speed, you consume more memory, and if you want to optimize on memory, you consume more CPU cycles. But, the really great algorithms maximize speed and minimize the storage requirements.

Innovation therefore works something like this: there are two or more variables that influence each other in some way – either proportionately or inversely. Innovation is nothing but somehow eliminating that relationship – meaning control both the variables independently, or in some cases, invert the relationship – this means that if the variables influence each other proportionately – then make them influence each other inversely and vice versa.

This requires counter intuitive thinking. The best example of counter intuitive thinking is the binary search algorithm. The binary search algorithm is a very simple algorithm – the algorithm finds whether a search key is present in a sorted input or not. Suppose you are given a set of integers sorted in ascending order – let’s say integers starting from 1 to 10. And, you are also given a ‘particular’ number – let’s say the number 8. What you have to do is to find out whether 8 is present in the input set or not.

The common sense solution goes somewhat like this: you compare 8 with 1, then with 2, then with 3 and so on, until either you find a match, or until you run through the entire input set. This is very expensive – because technically if there are billion numbers, then you may have to a billion comparisons before you terminate your search.

The binary search is a brilliant innovation. In binary search – you divide the input set into two halves – say numbers starting from 1 to 5 in set one, and from 6-10 in set two. And then you compare the ‘search key’ – in this case 8 with the last element in the set one. In this case, you compare 5 and 8. Since 8 is greater than 5, you ‘eliminate’ set-one entirely – because all numbers in set-one are less than 5, and therefore they are all less than 8. Now, you take set two and again divide into half – say 6-7 in set one, and 8-10 in set two. And you repeat this process.

You can search through a billion numbers with in 15 lookups. Because, with each lookup, you are eliminating half the input set. So, if you have a billion numbers – in the first lookup, you throw away half a billion numbers. And, that is a tremendous increase in performance. As the size of the input set increases, the benefit of the algorithm increases.

It is very difficult to think of solutions like this. In fact, there is no other algorithm that comes anywhere close to binary search in computing science. It is because, it is a very counter intuitive way of problem solving. The designer of the binary search is not interested in searching at all. His interest is to find out all those numbers that he does not have to search and ‘eliminate’ them as quickly as possible. Because you don’t have to retain the entire input set until the termination of the algorithm, as the algorithm proceeds with each lookup, you can in fact free up memory as well!! It is in fact an elimination algorithm, not a search algorithm. It is a search algorithm that does not search.

So, here is another systems principle. I call it the principle of inversion. According to this principle – our common sense understanding of the world is inverted. We live in an inverted reality. If you are looking for a best solution, therefore what you have to do is to “invert” your common sense understanding and this conscious inversion almost always leads to a better solution. All of us at first come up with a common sense solution. What you have to do is to then invert the common sense solution to get the right solution. Instead of looking from left to right, look from right to left (The Boyer-Moor sub-string search algorithm does precisely this). Instead of dividing from top to bottom, aggregate from bottom to top – or what ever else. Basically invert your initial solution. Instead of trying to ‘solve’ a problem, ask yourself the question: what can I do to not solve the problem? How can I eliminate the problem totally instead of looking for a solution? If you can eliminate the problem – what need is there for a solution?

If you want a very good application of this principle – refer to my earlier post called ‘Throw the Clock and Save the Humanity’.

If you are a first time visitor to this blog, you have to actually read it from bottom. This means that you actually have to ‘invert’ the page. The design of the blog is such that the part-3 of an article is followed by part-2 followed by part-1. Do you see how inverted the world is?!

Donald Knuth – one of the greatest computing scientists - made a very interesting comment about this inversion principle. He remarked that in computing science everything is inverted – even the trees have their roots at the top and leaves at the bottom!!

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As stated earlier, my primary interest is in applying the design principles to design one’s own consciousness. How can we apply the principle of inversion to obtain a better solution of the self?

Here is one application I found – and my life totally changed after this discovery. Most of us are taught that we reason with the intellect and feel with the heart. This is rubbish, it is totally inverted. In reality, we actually reason with heart and feel with the mind. Sounds intriguing? I am sure it does, and it begs some explanation.

The mind and intellect only react – they don’t respond. It is the heart that responds to a situation. Suppose you get into some fight with your wife on some usually very trivial issue. You get angry and both of you fight. After some time, it is your love that comes to your rescue; you realize that you were only reacting to something that is very silly. Which part of you is reacting and which part of you is doing the real thinking?

Suppose you are ‘by nature’ a ‘gentle’ person, or a ‘friendly’ person, or a ‘generous’ person, or a ‘humble’ person. It is this ‘gentleness’, ‘friendliness’, ‘generosity’ or ‘humility’ that decide how you relate to the world and situations – right? These are qualities that normally you do not associate with your intellect and mind. The heart does the real thinking for us – does it not?

The core values that one holds very dear – like goodness, love, friendship – are retained in the heart. And, it is these core values that drive our ultimate responses – not the fickle mind. The intellect is only an instrument of memory – its function is to retain and store experiences and information. The algorithms are resident in the heart. There are temporary algorithms (reactions) that may be initiated by the mind – only to ‘flush out’ the unimportant areas of memory. So, think and respond with your heart and store and retain with your intellect. This is what we normally do, but a realization of this can improve the quality of our lives tremendously.

For a beautiful illustration of this subject, refer to Chogyam Thrungpa’s “Path of the Sacred Warrior”

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In the next post – I shall write about Non-Linear thinking and some techniques for practicing non-linear thinking.

Getting a Handle on Creativity

The Design and the Designer - Part 2

I made a brief mention about systems thinking and associative thinking in the last post. In this post, I shall describe them in some detail, and explain their relationship to creativity.

There are basically two methods of formal thinking – one is analytical thinking and the second one is synthesis.

If you are asked to design a product – and if you are applying analytical mode of thinking, then you start to decompose the product into its parts, sub-systems, the relationships between the parts and so on.

If you apply systems thinking – you don’t start by decomposing the product or system into its sub-systems. First you place the system into the larger environment or the larger system of which it is only a part.

Sounds very abstract? I don’t blame you. Here are some examples:

Suppose you are asked to design a washing machine. An analyst engineer will probably apply law of 3, and divide it into three sub-systems – the control unit, the electrical unit, and the main rotary unit.

But, a designer will approach it differently. The designer starts by asking questions about the environment in which the washing machine will be used. She will ask who will use it. Where will it be used – in a usual apartment house hold, or in a hotel, or in a rural area and so on. Basically, what you are doing is to first study its relationship to the larger environment in which it is a part. These relationships give you very useful design parameters. A large part of the design is the study and understanding of the products’ place in the larger scheme of things. In a technical language, you may call it “usability”. But, philosophically, what you are doing is to apply systems thinking. If you understand this very well, then you can start to apply it as a mode of thinking, instead of usability study, functionality, ergonomics etc..

Some examples of how it is applied in modeling societies may be in order here, just to drive the point I am making. Russell Ackoff made systems thinking into a formal management subject. He is the first one who understood the need for studying the relationship to the larger system of which any system is but a part.

Once, Ford Foundation did a project in India to educate people about the need for family planning. The Ford people would visit many rural parts of India, gather all the villagers, tell them about the need for family planning, give them condoms and a transistor as a gift. All the Indians would attend the seminar dutifully, fully agree with everything that the Ford Foundation people said, nod their heads, smile gently in agreement and collect the condoms and the transistor.

They would then go home, put on the music and make babies.

The Ford Foundation project manager met Ackoff one day and complained that Indians are irrational. He said that they all understood the need for family planning, but they wouldn’t practice it. Ackoff said that may be he was solving the wrong problem.

The project manager was very agitated, and asked – “what do you mean – solving wrong problem??!!”

Then Ackoff showed him a news paper cutting about a Brazilian women who gave birth to her 42nd child. The Ford Foundation project manager gave up – he said “if this is not irrational, then I do not understand what is rational”.

Ackoff’s point was simple – if a woman can give birth to 42 children in a life time, why are Indians stopping at 4.2? This means that they know how to practice control and they do. And, then he explained the reason for the Indian’s approach to life. In a society that has no retirement benefits, no social security – the only security is to have three sons. And, statistically, you need to produce 4.2 children to have an average of three sons.

So, Ackoff asked the Ford Foundation Project Manager – “do you think you can rob them of their retirement planning by giving them a transistor? Who is irrational – you or them?”

Do you see the point? What Ackoff was doing is to study the problem in the context of the much larger social issues, not isolate it and study it as sub-systems – for example - what is going wrong in the project, whether the transistors should be changed to tape recorders, or whether the presentation should have more stories etc..

The results vindicated themselves eventually. As the middle class grew in India – with assured incomes and pension benefits – there was no need to educate people about family planning. They would automatically do it. The issue is not about female discrimination or anything like that, it is simply securing our own lives. This is perhaps the reason why salaried class practices family planning more than the self employed and business people.

Another example, again from Ackoff’s writings. This one deals with the model of the society to explain corruption.

There were a group of Mexican farmers. As it happens with many poor farming communities, they are always at the mercy of the middlemen who buy the produce from them. The prices are in general fixed by the middlemen, who will pay very little to the farmers. The farmers complained to the government. The government duly appointed one official supervisor who is charged with buying the farm produce directly from the farmers at the government decided “reasonable rates”. But, like any government initiative, the farm produce is accepted only if it meets government specified quality standards.

Things went on well for about a week. After that the supervisor started to reject all the produce on the quality grounds. And, the farmers had no other recourse, but to sell it to the old, wily middleman. This time, he had a good reason to pay them even less – because their produce does not meet “government specified quality standards”.

Basically, what happened was the middleman started to bribe the government supervisor.

Now, if you are given this as a design problem, what do you do?

Ackoff provides a beautiful solution. According to him, in a democratic model of the society, the individuals pursue their own goals that may not necessarily be in alignment with the larger society’s goals. Basically, this means that the supervisor is interested in the future of his own family and his children’s education. And, he needs money for that. In essence, he is not a match to the middleman. His social status is that of the farmers. By making a person from the same community in charge, you are not helping that community. It would have been different, if he was chosen by the community itself, but in this case, he was appointed by the government – probably he lives in the nearby city, and not in the same village. The Americans solved such problems very effectively – they encourage more middlemen to compete with each other. Competition is the solution, not control.

Ackoff applies the same principle again – study the larger environment and its dynamics. The solution is not to change the supervisor, or appoint another senior manager who will investigate corruption charges and so on.

Can you see that much of what we call as creativity is nothing but application of this principle. If I had explained these problems without the principle, they would come across as very “out of box” solutions. But, they are produced by a systematic application of a simple principle.

The beauty of the solution depends on how well you understood the larger environment, but that doesn’t take away the importance of the systems principle.

There are some very good references on Systems Thinking. Here are a few:

Russell Ackoff: Re-designing the corporation for the 21st century. This is a fantastic book on the core systems principles. This is not the kind of design book you will read in your design course. It is not about “form follows function”, or about color theory, or about creative thinking. I think the time has come for designers to junk such very old concepts – they only mystify the subject, instead of demystifying it. If you want to understand how to think – then you should read this book. It is about management, but, the underlying concepts are applicable in the design field.

There is another great advantage of this book – you will acquire the necessary terminology to describe your work more successfully to your managers and clients. They understand very well the management terminology of this book. And, if they understand what you do better, you can get better commissions.

Another great book on Systems Thinking is Gerald Weinberg’s General Systems Thinking. This is a must read for any problem solver.

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This is a rather long article. There are still another three posts in this series. In the next posts, I shall write about General Systems Thinking, Associative Thinking and try and define the differences between creativity, originality and innovation. I hope to complete it by this weekend.

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In the meanwhile, here is some food for thought. This is one of the system’s laws (my own discovery):

The more complex the product is, the more the probability of the success of its design.

It may sound contradictory, but it is true. The really simple things are very hard to design. A stethoscope kind of invention takes place probably once a century. But, X-ray machines, better X-ray machines, CT-Scan machines, MRI machines, Positron-Emission Tomography machines etc – they happen every year.

Fountain Pens were used for some hundreds of years before a ball point pen was discovered. Can you think of the next shift in the writing instruments? Can you invent another writing instrument that can fundamentally change the way we write? These are inventions that happen once a century.

There are some inventions that happen only once a millennium – like the invention of Zero. The Indian Sage who gave the world Zero – basically invented “nothing”, or the concept of nothing and how to make use of it. It changed the destiny of humanity for ever. The only other mathematical concept that comes close to Zero is perhaps “e” – the natural logarithm. But, these two inventions had a gap of some thousands of years.

If you are an accomplished designer – you may have one “jackpot” in your entire life. The rest is basically improvisation on the existing themes.