INTRODUCTION What is computational design?
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“ Nothing that is worth knowing can be taught “ – Oscar Wild
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It’s your journey What is computational design? I wish I knew the answer. I don’t. Perhaps, it is best kept that way. If design becomes completely computable there will be no use for designers. An understanding of computational design will help you understand why this will not happen. Yet an understanding of computational design is increasingly important. I strongly believe that designers need to develop their own computational philosophy, as it will play an increasing role in defining the quality and character of their work. Learning about computational design has been a long and interesting journey. I hope you will find your own journey interesting, engaging and forever evolving.
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“Truth is one. Sages call it by various names “ So says the Rig Veda. I find the concept that the same truth can be discussed in various ways relevant to computational design. I see computational design at the centre of a fruitful intersection of three somewhat independent bodies of knowledge: computation, design theory, and biology. They each have their own language and frameworks to describe and discuss what we call design.
Computation
Why design is a human activity Can nature design? Can computers design? What will we do if they can ? Simple; we will disqualify them, because, we make the definitions. We have a way of writing ourselves into every definition we make. For example, we no longer refer to the computation required to book our airline ticket as “Artificial Intelligence (AI)” anymore. It once was. However, one ever lasting definition of AI is that it is “what computers cannot currently do”. Because, the moment computers do it, we re‐define the definition. I guess we do this to protect our human dignity – that has taken a good battering in chess, general knowledge and other stuff that computers are now better at. It is all the same for “computational design “. The moment computers do it (I am not implying that they can) , it will no longer be considered design. Design is strictly for humans. We don’t like our roles messed up. Creation was God’s business, and designing is ours. Likewise, computation is for computers. We rarely call the immense amount of calculations that we make while we take a step (that most walking robots are yet to master) as computation, neither do we
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refer to the constant combinatorial experiments of nature as computation. We like to keep things separate – so that we don’t get confused. It taxes us less when we think of them separately. But we cannot afford to. We will next look at how biologist, design theorist and engineers look at design, but before that how the ancients saw it. The pre‐modern view Well before the advent of biology, religious believes anchored our thoughts on creation and through that our thoughts on design. But these beliefs were as diverse as the religions and philosophies that discussed it. The most familiar of this, is the Western Christian perspective – that still continues its long drawn conflict with the way scientist see creation. It is believe by “creationist” that the complexities of natures designs cannot be achieved without divined intervention, not too dissimilar to the view held by a vast majority of designers, that the complexities of human creation cannot be achieved by computational processes. Designers in many ways are a type of creationist , may be we should call them “Designerist” as they replace God with themselves and cannot imagine design happening without their divine guidance. How biologists see design The word design crops up in the 17th century to distinguish human creation – as opposed to God’s creation and perhaps also to distinguish the gentlemanly class that was differentiating itself from the cruder craft/working class mainly thorough their ability to conceptualize stuff without engaging in the dirty work of doing it. Nature by far has developed the grandest strategies for design and her ways are worthy of study.
“Design” Invented
Richard Dawkins
Charles Darwin
1600 1850 1970 1980 2020
Gregor M endel
Jhon Holland
PC revolution
Sadly, many researchers have ignored for too long the understanding that biologists have made about design. So I summarise them here. Charles Darwin figured out that design can happen without direction. Gregor Mendel figured out from pea plants how the design code was carried. He called it genes. Then John Holland found out that he can mix and match numbers instead of genes, provided we know what we want – as an alternative to mathematical optimisation. He called it genetic algorithms. Then came the PC revolution. Finally, we automated the drawing board. Richard Dawkins created tiny creatures that bred on screens, at home in his Mac – that showed that designs can be evolved with computers.
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Internet/ + Cloud
Nothing much seems to have happened after that, expect for a churn of journals, books and funny forms – because folks think that it’s got to do with nature, like creepy crawlies, lizards and fish. Now that we have gone past it all, we need to take a fresh look. Because, now we know a lot more about how design works in nature. We are able to appreciate its grandeur and its complexity. We know more and more about genes, how they evolve, and how they operate. Thanks to the that mathematicians and computer scientist who plunged into genetics ‐ we now have a good computational understanding of its marvels. We now have an abundance of computational power to explore design ‐ as an evolutionary phenomena. But then, biologists don’t talk about design. They talk in terms of genes, evolution and populations. We need to understand their language, for they see design differently, as an autonomous process without direction. Now this is not very useful for designers, mainly because design is a human directed activity and nature is not. While we envy their understanding of the breath taking sophistication of natures design processes we are unable to apply even a fraction of it to design. Because they talk in terms of the “genetic code”, “populations” (instead of individuals), “species”, “evolutionary trees” and “ morphogenesis “ all of which provide very useful ways for us to think about design. We will discuss them in greater detail. We have a lot to learn from them, because they are now in the brink of creating complex life forms. Not random ones that you see in science fiction movies, but ones with desirable properties. Organisms that will eat up oil spills, create protein for fodder, convert sludge to oil and a host of other amazing purposes. They seem to have cracked it. They have figured out, how to hijack a directional less design process to create life forms with desirable properties. I now regret skipping biology. Design as design theorist see it Design theory has its origins in the 1960 as a part of an attempt to rationalize design. Its late start had an unfortunate effect, in that it had to justify its ‘rationality” to more established fields of engineering and sciences that were borne out of the culture of rationality ‐ that we call science. The classic book “Engineering Design: A Systematic Approach”{Gerhard Pahl, 1977 #41} is a classic example of this approach, implying a disdain for “unsystematic” and irrational design processes that designers are yet to be weened of. It breaks down the design process into 1) 2) 3) 4)
Task clarification Conceptual design Embodiment design Detailed design
..to be followed in an orderly systematic way – which is then cycled through till one gets the right results. While this approach is helpful in solving routine design problems, it systematically eliminates any creative solutions that might otherwise occur due to the unsystematic practice and behaviour of designers. In a way, the authors would have done better by providing engineers a cane instead of this book to whip designers till they submit themselves to systematic processes. While most engineering students are thought these
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processes it is doubtful if it is used in practice. If everyone follows the same process, they are likely to come up with same answers – and an intense global competition has been driving the value of such nondescript designs to zero. Human creativity is now gaining a lot more respect, but the damage of rationalisation continues primarily on the academic community, which was for some time very fond of the now much discredited “Waterfall Model” where design is seen as a sequential process moving systematically from one to the other. Thankfully this is now regarded as a flawed idea, because: “Many of the [system's] details only become known to us as we progress in the [system's] implementation. Some of the things that we learn invalidate our design and we must backtrack.” As explained in the paper by David L. Parnas “ A Rational Design Process: How and Why to Fake It”, a few important realizations have now been made by the design research community. They are: 1) Routine design problems are very different from creative design problems‐ which are referred to as wicked or ill‐defined design problems 2) Co‐evolution of the understanding of the problem and potential solutions (we do not know the problem when we start on it. The discovery of the problem and solutions develop together) 3) Emergence –that design is based on unpredictable issues that arise out of design activity itself These more recent realizations undermine design as a systematic process – despite a large amount of engineering based research is seen squandering its energies along this old track. But a strategic report of the National Science Foundation indicates that the winds have now changed. “In 2030, designers will work synergistically within design environments focused on design not distracted by the underlying computing infrastructure. Designers will interact in task‐appropriate, human terms and language with no particular distinction between communicating with another human team member or online computer design tools. Such environments will amplify human creativity leading towards innovation‐guided design.” The human designer, with highly “irrational processes” is now scheduled to get back on top.
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Concept Knowledge Theory Routine design has now lost its value as it is something that programs can do. Hence new and better theories that are able to represent creative design are now emerging. The most convincing amongst them is C‐K theory , where C stands for concept and K stands for knowledge. It was also borne out of the realization that there is a commonality amongst design problems and approaches to its resolution in a way that is independent of its domain (architecture, engineering, circuit design etc). This is accomplished by discussing design only in terms of concepts and knowledge.
Image from : Wikipedia.
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Design is seen here as a process of exploring concept and knowledge space (we will be discussing the concept of space latter on). What it means is that, as we explore design possible we enlarge our understanding of the design problem creating new knowledge ‐ which in turn influences the nature of our exploration. Design exploration is seen as a knowledge creation activity. This is indeed a much better conception of the design process that could explain many of the complexities of design. It also works well within the “Truth is One” perspective, if we elevate design issues above its various fields. We begin to see its commonality.
Design as computer scientist see it Computer scientists see the world and life in it as computational problems – by doing so, they have helped transform the world. The way we see knowledge and our relationship to it has gone through a radical transformation. This happened because computer scientist developed the data structure behind knowledge. With it came the ability to create new knowledge. But with every field of science comes a culture, some of which are helpful and some are incompatible with the cultural complexity of design. Let us look at the incompatibilities first. These are some of the obsessions of science that computer science carries deep within its belly. 1. 2. 3. 4. 5. 6.
Precision Certainty Determinism Measurability Problem solving Procedurisation It is the low tolerance to imprecision that gave modern science its defining character. Nature is something that early scientist loathed for its lack of predictability and complexity. They looked up to God first and then to the heavens. They found order in the movement of planets. They found harmony. It must have delighted them. They called it Musica universalis (Music of the spheres).The langue of mathematics was able to describe it. Their behavior was predictable. This was the way the heavens worked. The faith in God was replaced by science.
Western astronomers were they envy of their Chinese counterparts, because they could precut the eclipses with great certainty. While science is not particularly western, it is currently culturally so – especially in the way we understand it now. Western language arts and architecture reek with evidence of high ideals associated with the qualities that we discuss here, causing a division that is with us today into science and humanities. One built on the ‘religion of scientific rationality’ and the other on ‘irrationality ‐ politely called humanities, so that they can both co‐exist without conflict. Designers are the poor souls torn between these two words, one that feeds their spirit and the other
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they need to deal with, whose culture they often despise. It is this other culture that we now need to understand. Determinism Computation is built on ‘rational models’ of the world and is seethed in the culture of determinism. Stuff like if “A is equal to B then C is this”. There is no nonsense involved. Everything is crystal clear – that is because you are operating at a sub human level. But it is this rationalistic determinism that gave birth to modern science. But... “What makes computation so problematic for design theorist is that it maintains an ethos of rationalistic determinism – the theory that the exercise of reason provides the only valid basis for action or belief and that reason is the prime source of knowledge – in its field. Because of its clarify and efficiency, rationalistic determinism has been a dominant mode of thought in the world of computation {Terzidis, 2003 #39}“ Now, the world of design is very different, as it involves our species, our intentions, and desires that are yet to be computationally understood, owing to the inherent complexity. While we can handle complexity, computers find complexity difficult, causing a fundamental difficulty in involving computers in design. We must not forget that computing machines was the realization of a long cherished dream ‐ of the Western worshipers of scientific rationality ‐ to build a construct of pure rationality. This has now been achieved. It has transformed the world. But unfortunately in design, we seem to have a problem with this “rationality” (not with the machine) “The problem with this approach is that it assumes that all computational activity abides by these principles. In contrast, intuition as defined in the arts and design is based on quite different if not opposing principles....In addition they often defy the rules of precision, planning and scheduling. This mode of thought comes in contrast to the dominant computational model where methodical, predictable, and dividable processes exist.{Terzidis, 2003 #39}” Design as a problem to solve This is a blooper. Because designers do not know what problem they are trying to solve. As design (except the trivial type) deals with large amounts of complexity, it is difficult to define it and is exceedingly difficult to define it numerically and impossible to define it precisely. Hence such design problems are now classified by design researchers as “Wicked Problems”. The word wicked here does not refer directly to cruelty of any kind but it does in a strange, indirect way. The nature of wicked problems is widely discussed in design research. I think it refers to the cruelty it inflicts on “rational minds”. Understanding this wickedness is of upmost importance if we wish not to be tortured by the religiosity of systematic, rational thinking and be comfortable with our own wicked ways of designerly thinking. By far, defining the problem is the real problem in design. “If I had an hour to solve a problem and my life depended on the solution, I would spend the first 55 minutes determining the proper question to ask, for once I know the proper question, I could solve the problem in less than five minutes “ Albert Einstein.
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This is the kind of split that Einstein whose mind travelled well beyond the universe would make between understanding the problem and resolving it. His creative insights were a result of thinking deeply about problems. But those who go to school are fed on a diet of solvable problems. Designer researchers continue this practice. They have a habit of choosing solvable problems. Tha’ts Ok. But out of it they propose universal methods. It is not uncommon to see a cross section of a shock absorber with a diagrammatic model accompanying paradigm shifting proposals in design processes. Most design problems have huge complexities – but you can choose to ignore them. There are two reasons why design problems cannot be defined. One is their inherent complexity – the second is the diversity of opinion of its value even after the design is completed. Eifel Tower and Sydney Opera house are today considered as very successful designs. But during initial days, they were not well received. The French press was full of critical and scathing comments on the Eifel Tower’s design as soon as it was built. The Sydney Opera house presents an even more interesting example. There were significant controversies as the project broke quite a few of established design rules set by the competition committee. These examples illustrate the difficulties in defining a design problem and in assessing its solutions even after they are completed. Design as a procedure Computer programs are based on procedures. Procedurisng is the key step in destroying all activity previously done by humans. Once it is procedurised, it first moves to lower cost centres of the world and then vanishes altogether from human experience. Once knowledge is captured, it can be procedurised. All knowledge with regards to design that can be captured is pretty much captured now and has become a part and parcel of CAD packages. Some believe that complex procedures can be broken down into steps making it easier for us to solve the smaller bits in the hope that we can put them all back together. Decades of research efforts have gone into producedurising design leading to brad agreement on the basic stages of design development. The early stags of design are know to be chaotic and latter stages more orderly and somewhat more procedural; because at that stage, design is no longer happening. Its just implementation that is left. But what about procedurisation at early stages of design? If we managed to do it, would our jobs would be gone ? Would we be replaced by software programs ? Fear not. It would never happen. Design is fundamentally messy. That is its saving grace. It protects it from the onslaught of automation. I guess you know that when you are designing, that not only do you not know what you are doing, you also do not know which direction you are heading. The day you know how to do it – you will no longer be doing it. When you teach computers do what you do, your set of skills will be rendered useless, because computers will do it better, faster, and cheaper.. When you combine the procedural desire and a low level understanding of the complexities of design we create a particular type of pipe dream. May we call it the – “ programmer’s pipe dream”. We see in various manifestations. Often these are step by step deterministic programs that involve optimisation guaranteed to give you the “Best Solution”, on its course of find the best solution – it may churn out form, simulating design exploration. But if we manage to point out its acute shortfalls, COMPUTATIONAL DESIGN
the programmer will resort to even more programming. The code gets longer. Many of such efforts end up as Phd Thesis long boring and complex. Design as humanities Design for good reason for a long time belonged to the department of humanities. It had qualities’ that science did not want to deal with it and wise verso. The issues involved are very significant, but fundamentally cultural in nature – with each culture seeing certainly and value only within its own frame work. An appreciation of both cultures will help us understand the issues better. But places where it is in conflict will help us understand these differences even better. Design is one such place. Here the central tenants of science with its intolerance for uncertainty and its relentless pursuit of the one truth ‐ and the one and only truth, conflicts with the core qualities of humanities, where truths are both multiple, relative and impossible to define. We may look at it in another way. That old world science lacked the sophistication to comprehend issues addressed in humanities. I tend to take this view. The great advances in computer science, now makes it possible for us to manage multiple truths and observe complex behaviour. Google and credit card companies understand and can predict our behaviour better than we can. The new economy is built on these new capabilities. Massive amounts of data obtained through transactions, telephone calls and surveillance monitors enables organizatons to study us like the way genetist would study lower organisms. First they watch them through microscopes and then with their pals in computer science model them as computational elements and soon reach a point where they cannot tell the difference between the two. At this point they can correctly claim that they understand these organisms –which is now us. Developments in space syntax enable us to predict human behaviour with buildings with great certainty (in a macro sense). Traces of human movements from Spacesyntax
Design as a connected activity Much of design today is collaborative and most of it is web based. The creators of design and consumers of design are now connected intricately and intimately through the fabric of the web. Online design tools play an import role in this. This makes it possible not only to enable broad based design but also watch what is being created by. Those who watch also know in detail what we are most likely to consume. Companies like goolge, amazon and your local bank are now able to construct accurate computational models of your good self. Despite your notions of individuality, you happen to be a good fit – a reliable predictable data point. Statistics allows those who process data to develop an understanding that without detailed understating of your inner‐self or the status of
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your liver. Statistical methods enable a computation of a different type. Such computation does not require detailed understating of the aspect that are being studied. But this requires large amounts of data from which it can generate useful knowledge. This means that we are able to extract and apply knowledge without knowing the basics – which was previously thought to be necessary. Such approaches to complex problems now allow computational methods to understand, predict and manage our vaguarties within a solid computational frame work. Uncertainty, complexity, individual differences are all well within the capacity of current computational frame works. Being human is no longer a valid excuse. The great revolution of renaissance that replaced God with us as king pins of the universe is now over. We are now bacteria, understandable and immensely predictable. We have so far discussed contradictory cultures of science and design. We have a better understanding of their incompatibilities. We have witnessed the growing powers of computation and the internet that connects computational machines is now central to modern life. But is this computation a suitable medium for design? Should we discuss design in the langue of computation? It is possibly is the worst language that we can choose to discuss design. Yet it is the one we must choose, for a very simple reason; that it is already the platform in which we now design in. We are wedded to it. We use it badly. We deny its existence. We should not.
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Design as modelling Whether we like it or not, a good of design is now authored in computational media. While this approach works well at the latter stages of design, it is of little use in the early stages of design where it is hard to beat the pencil and paper combo. At this stage, the uncertainties are high. They are reduced as the design matures. Virtual building design has become the dominant way in which architects develop designs. We are now into building virtual representations of buildings. This is design – for all practical purpose. It is a good move. Design is now about modelling.
Once the design matures to a certain point, engineers jump in, because they got something to play with, something that they can put numbers on, and something they can analyse. This is what computers are good at. This is where the bulk of the computation happens. But this is not computational design for a very simple reason. Computation design is made of two words, computation and design. At this stage it is pure computation. Design by then is pretty much over. We are not interested in this, as it is the domain of engineers. I am not sure what they call it. They don’t use the word computers any more. There is no computational design in engineering. They don’t use that word. But even after the design is over you can continue to fiddle with it. Engineers love that. Its called optimisation. They do it for a living. They can’t live without it. But they call it – design. They may change the material, thickness here and there and add some features to improve the “basic” design. The effect of these changes are miniscule compared to the changes made in early stage design where most of the major designs are made (with high levels of uncertainty). This uncertainty is gradually reduced to the point where it disappears. Design may even be seen as a process by which uncertainty
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is reduced. Most computational processes require certainty. Some attempt to model uncertainty by considering a series of certainties in appropriate proportions – leading to probabilistic thinking. There has also been some adoption of “Fuzzy Logic” that allows computational process to accommodating uncertainty. But design is not about accommodating uncertainly it is about exploiting it, because precisely in that uncertainly lies unimagined possibilities. What is Computational Design? Now that you are somewhat aware of the different ways in which we understand design, you many be able to appreciate the difficulties in delivering simple answers to the complex problems of design. Neither biology nor computer science nor design theory can help us resolve the great dilemmas of design. But they can all help us think about it in various ways. In developing our understanding we need to discard the dogmas of the past and be prepared to give ‘scientific rationality’ low marks when it comes to design. We however need a language in which we can discuss design. We chose computation – because there is no other, that is useful for the next stage, for realising what we design. Computational Design is not about computation This may be a surprise. Computational Design has very little to do with computation. Strange? While computation relates closely with computer science, its links with design are problematic. Mainly because computation is about deterministic processes, whereas computational design is about the opposite of that. It is “about the exploration of intermediate, vague, unclear and ill‐defined processes; because of its exploratory nature, computational design aims at extending the human intellect “{Terzidis, 2003 #39}. Computational design is about thinking and discussing design using the language of computation. For example, the novel “Invisible Man” discusses the invisible man using the English language. The discussion in this novel is not about the English language though it is written entirely in it. Computational design is just like that, it is written in the language that computers understand, but what’s being discussed is something else. We need to be very clear of this distinction; Especially since the use of computers in architecture is very much about computation. It has virtually very little to do with computational design. Computational design has very little to do with the way computers are used in design today. Ways to think about design While computer science provides us the worst language for discussing design, it furnishes us with incredible tools to practice design. But in early stage design It’s main value is geometry management. Biology on the other hand seems to have nothing other than the inspiration to offer. The way nature it designs is very different to the way designers design. We develop designs through geometry. We draw, sketch and develop the details as we progress. The sketch is a simpler form of the original, only lacking in detail. We are dependent on the visual link with form. Unlike nature, we cannot design in code. Worst still, we cannot even imagine the ways in which we can design other than sketching a representations of the final design.
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Mini Man When the sperm was first discovered by Anton Leeuwenhoek (1632‐1723) through hazy view of his homemade microscopes he wrote politely to the royal society : ‘What I investigate is only what, without sinfully defiling myself, remains as a residue after conjugal coitus. And if your Lordship should consider that these observations may disgust or scandalise the learned, I earnestly beg your Lordship to regard them as private and to publish or destroy them as your Lordship thinks fit.’ The Royal society in its wisdom, decided to publish his perverse finding, leading to the belief that the “mini man “ was discovered. The sperm was speculated to be a mini version of man which on fertilization grows to a full man – through a highly visualizable process of scaling, where there is a clear connection between how things start and how things end up. This is the hallmark of the human design process where we do not lose touch geometrically with what we are designing. Our current conception design processes is not very different from the “min man” approach to how we conceive design development. We concieve design development as geometrical process, based on drawing out our designs in lower levels of detail first, and progressing to higher levels of detail as we complete the design. But on the other hand, both nature and computers design with code. One designs with genes and the other with bytes. Computers are now used as tools mainly to represent the final construct. Technically, computers are currently not used for design. They are used mainly to represent designs – aided by algorithms to reduce the labour involved. Interestingly, both nature and computers do not visualize design ‐ they do not need to. We need to. So we use tools to help us with our inabilities. We just cannot imagine other ways of designing – without having to visualize it first. We are stuck on this account. While we are aware that there are other ways of design – we are unable to imagine how we can use it. This is what Prof Frazer calls “The lack of metaphor”. We are at a complete loss when to comes to imagining design process that are different to what we are accustomed to. Hence we rely totally on geometric representations as our grandparents did. Beneath all the sophistication of using computers for design, lies a very primitive design process which is now a few centuries old. So, Lets keep tweaking CAD has so far evolved to support our (highly limited) design process and is increasingly useful at the tail end of the design, where we are able to see design as the representation of the final form. Because at this stage, thanks to parametric design ‐ we can tweak our designs. Thanks to analytical packages, we can also measure the effects of these changes. But at this stage of the design processes, all the important decisions have been made, based on well honed human design processes. Computational design research is now mainly about fine tuning designs once it has acquired a high level of certainty.
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What is not computational design? The good thing about computers is that they do not understand anything. We have to tell them explicitly how to do stuff. They can learn stuff, based on what we teach them. But to get them started, we need to represent what we want them to deal with, in a way they can munch on it. This makes talking to them about design exceedingly difficult because, we in the first place do not know what we are talking about. Such is the nature of design. In comparison, natures work differently. It uses codes to create stuff that creates stuff that creates other stuff. It’s not based on blue prints of the final form. It is s sophisticated orchestration of so many rich and complex activities – else we can fix our nose shapes by finding and modifying our nose gene. We cannot do that. We can only do that in CAD – because the representation is direct. It provides a direct means of representing what we want, it happens to be a very poor way of representing what we can have. Design should be all about what we can do. CAD is very poorly structured for that. CAD in its current form is an impoverished means of representing possibilities or exploring designs. It was never designed to do that. CAD is a by‐product of Computer Aided Manufacturing (CAM). CAM was first developed to control manufacturing machines. Of course you needed nicer ways to input the design data. That is how CAD got started. Because of this, it has excellent capabilities to represent designs – making it ideal to run analysis on – to do what computer sciences would consider as computation. But for us, when we get to that point, it is no longer design; because the representation of the design is finalised. Parametrics may help it to stretch it here and there but that is very little in the vastness of design possibilities that we need to consider first . Lets fake it till we make it Lets for now accept the reality, that computers are dumb tools and that design processes ought to be driven by our own intelligence. We now use computers to construct representations of stuff that we have already designed in our mind. Recently, BIM has taken the level of representations to the extremes. You can now build a building out of a design file. This is not a bad thing in itself. While we are locked‐in to severe inabilities of CAD, we are not totally paralysed by it either. There are a lot of things that we can now do that are useful, provided we do not delude ourselves into thinking that we are using computers intelligently for design. One day we may, but till then, let us focus on using computers optimally for design. Let’s see if we can use its representational capabilities to explore some possibilities around the core representation (which is already designed). The important thing here is to appreciate the significant limitations of this approach. If you want to experience great design exploration, open your window. You will see the diversity that nature is able to produce. Now that is real design exploration. I wish to establish here, the incredibly limited scope of what computational design – so that when greater doors are opened by the good efforts of researchers in the future, you are in a position to appreciate its implications. We take a pragmatic view from now on, to best exploit the representational systems of contemporary CAD systems for computationally exploring desing possibilities. Perhaps, we can justify this approach by viewing CAD systems, as the “natural
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environment” in which designs now evolve. Let us hope that one day this will change – when it’s abundantly clear that there are many, many better ways of designing. Till then, let’s fake it. We will next show you how. But no mention will be made of its serious limitations.
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Books worth reading
Frederick Phillips Brooks Making sense of effective design is at the heart of everything from software development to engineering to architecture. But what do we really know about the design process? What leads to effective, elegant designs? The Design of Design addresses these questions. These new essays by Fred Brooks contain extraordinary insights for designers in every discipline. >My review
Books to avoid By Gerhard Pahl, W. Beitz, Jörg Feldhusen, Karl‐Heinrich Grote, Ken Wallace, A book that degrades engineering design into a sad set of processes – devoid of complexity
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