The Design and the Designer – Part 6
A gap of more than two weeks interrupts the flow. But, the gap is probably required because from here – the approach is very different. Until now, I largely covered a lot of breadth, and was able to give examples in one paragraph – an approach that may not be sufficient from now onwards. It is like getting into the second chapter of a book – by nature, it gets a little deeper and a bit more boring.
The difference between Architecture and Engineering is like the difference between Music and Sound. Architecture is a word that is associated with many disciplines today – we talk of architects of nations, architects of enterprises and corporations, architects of cities, plantation forests, gardens, buildings, computers and information systems. Sometimes, this word is also used in relation to effects produced by an individual or a group of people – architects of success or failure, architects of war and of destiny. After the last Great War, this discipline seemed to have become main stream.
Even though, these days we use the term in its verb form, actually it exists only as a noun. The architect produces architecture – what he does is not architecture, but design. Therefore, the process used is the process of design, but the end product is “Architecture”. All architects are designers of a particular kind.
What does really an architect do?
Let’s consider the traditional architecture of buildings as an example. Even though the structural engineers deride architects as people who basically add unnecessary embellishments that do not have serve any functional purpose, in reality the job of an architect is one of transformation much like the work of an alchemist.
What the alchemist is to science, the architect is to engineering.
His work involves understanding the essence or meaning of space and transforming this understanding into an engineering problem.
Sounds abstruse even to me. We need some detailed explanation.
An architect basically brings meaning to space. An engineer does not make any distinction between kitchen and living room – both are basically enclosed spaces as far as the engineer is concerned. But, for people living in a house, kitchen and living room have very distinct functions, how they relate to these spaces is very different, the time they spend in these spaces is very different. It is the job of the architect to understand the function of a kitchen or a living room, and their relation to the people who use them and then somehow be able to express it in terms of certain ‘spatial’ characteristics – their geometry, placement, the equipment provided in that space. Basically, the architect defines what a kitchen is in certain engineering terms.
In short, the mysterious craft of architecture is very simple to express in words. The architect performs a series of semantic transformations; the last transformation achieves the feat of converting the problem into a structural engineering problem. If the alchemist transforms lead into gold, the architect transforms gold into lead – in a manner of speaking.
The reason why structural engineers do not respect architects is perhaps because of the fact that over the years, the community of architects was successful in creating a set of transformations that are universally accepted and understood, and the engineers themselves understand the difference between the kitchen and living room without the help of an architect. So, they do not see the necessity of an architect for the most common problems like the construction of a house, or a bridge any more.
In short, architects create new abstractions. An abstraction is an information structure – that codifies meaning objectively, an information structure that is universally understood. The power of abstraction is such that – if we have to state in one single line the difference between human being and an animal – we can say that the difference is the ability to come up with an abstraction.
What is an abstraction? A “tree” is an abstraction. ‘A Tree’ does not exist anywhere in the physical world – there are mango trees, there are lemon trees, there are all kinds of other trees, but there is no such entity called ‘tree’ – it is a pure abstraction that exists only in our consciousness. It helps us to group all mango trees, all lemon trees and all other trees in one sweep, and capture the ‘essential treeness’ that all of them share. Similarly, ‘A Man’ does not exist any where except in our consciousness – there is a John, there is a Joe, there is an Adam – but where is ‘Man’?
It took several thousands of years for us to come up with some very simple abstractions that we take it for granted today. One such example is the number system and the simple arithmetic of additions and subtractions. In ancient times, when people did not know the basic math, the methods they used for trading were very funny. If one goat equals two bags of rice (purely a concept of quantity decided by its value, there was really no such thing as ‘one’ goat and ‘two’ bags of rice) and if you want to want to exchange two goats, then what do you if you do not understand what is one and what is two? You give one goat, take two bags of rice, and then give one more goat again and take another two bags of rice. A very cumbersome process indeed – isn’t it?
But, what can people do if they do not know what is one and what is two? The numbers are very powerful abstractions.
An abstraction is valid only if it is completely objective. This condition means that an abstraction must mean exactly the same thing to everyone. The difference between an abstraction and a concept is in how strictly this condition is applied. A concept is not very strict in imposing the condition of objectivity. For example, “world” is a concept – but what I mean by world and what you mean by world can be somewhat different.
Abstractions, concepts or semantic types – are all information structures. It is a unit of information that retains the meaning of something, and is made accessible to everyone.
What is interesting is how we as humans acquire concepts and abstractions. We do it so naturally – we do not even realize that we are dealing with abstractions and concepts all the time. But, it is an amazingly complex process.
When as children we learn our alphabet – all we are shown is one particular shape of the alphabet. Your teachers writes ‘a’ in your notebook, and you practice recognizing ‘a’ and writing it yourself. That’s about it – after that you can recognize ‘a’ in what ever shape, size and form it appears – and you can recognize ‘a’ instantaneously. What you as a child accomplished is an amazing feat – by understanding one particular ‘a’ – you somehow extracted the ‘a-ness’ and then can apply that understanding of ‘a-ness’ like a flash. You can recognize ‘a’ in which ever font it is written, in millions of different handwriting samples. You do not need to be taught to recognize ‘a’ by going through several thousand samples, and various complex rules of recognition.
Such a simple act of extracting the meaning by understanding from one single illustration and then apply it on the fly to recognize millions of variations is an amazingly human ability – something very difficult for machines to do. Computers cannot even recognize their own hand writing!!
It is easy for a computer to produce millions of different ways of writing – you can type a word into a document, and then change the font any number of times. Computers are quite good at such manipulations. But, they are miserable when it comes to ‘recognition’ – at least until now. Suppose you take a printout of a document – and then use a scanner to scan the same document, connected to the same computer, and then try and reproduce the document in its original form ( a process called optical character recognition) – almost always you get a document with too many ‘errors’. The OCR programs are very complex where as the document creating programs (like Microsoft Word) are relatively simple. The OCR programs use several thousand ‘sample’ character sets, and ‘train’ the computer to recognize the ‘a-ness’. But, till now there is no foolproof method to accomplish this.
What makes us so good at pattern creation, extraction and recognition? Let’s leave that question to psychologists. However, this particular ability is at the heart of problem solving. In a most generalized sense, architecture, design, engineering, diagnosis are all a form of problem solving. Problem-Solving and Design involves an innate ability to recognize and categorize patterns, abstractions and concepts. Patterns, abstractions and concepts require associative thinking.
In the earlier posts, I mentioned about two kinds of thinking, two different processes of problem solving and so on. I tried to make a distinction between demonstrative reasoning, and heuristic reasoning. It is well recognized that the art of problem solving involves heuristic methods – for example, using analogy, generalization, reduction, specialization and so on. We also described in some detail about various forms of non-linear thinking – be it creativity, right brain thinking, lateral thinking, out of box thinking and so on.
Associative thinking and heuristic/plausible reasoning are the most generalized forms of non-linear thinking and problem-solving.
How does associative thinking work really and how can we use it systematically?
Here is a small exercise:
Let’s pick up some word randomly – let’s say it is Sun. Write down ten other words that come to your mind (without thinking) when you think of Sun – for example, star, heat, light, earth, round, fire, red, day, night, energy, Egypt, Japan and so on. Now, how is Sun connected with
In the last post, I discussed about four structural relationships – hierarchy, network, hypertext and set. The relationship between Sun and
Nasruddin – while solving a logic puzzle uses his associative network to come up with a completely out of the box solution. We need such an associative mental network to work with analogies, to work with induction, to generalize something, and from generalization to specialization and so on.
Another advantage with the associative thinking is that – you can recall your entire memory starting at any point. I suggest doing this as a fun exercise. Start with Sun – and write down all the words that come to your mind, and then for every word connected with Sun, write down all the words you can think of. For example, expand
Unfortunately, we are never taught how to make and keep an associative memory consciously. We are taught how to practice organizing our knowledge using the structural relationships, and we are taught how to use demonstrative (logical) reasoning, even though our brain uses an associative structure to organize its own memory and experiences. We are naturally gifted with the ability to organize and relate to our experience using associative networks. But, we are never taught how to practice it formally. As a consequence, our memory is a very randomly formed associative, semantic network that we cannot use efficiently.
The real trick of problem solving is nothing but consciously organizing our knowledge and experiences as an inner semantic network of concepts and relationships. In other words, if we can make and keep associative networks of our knowledge and experiences, then we have a better chance of becoming better problem solvers.
More on this in the next post.
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