Distributed Intelligence In Design

Tuba Kocatürk, Benachir Medjdoub, Tuba Kocatürk, Benachir Medjdoub

• Publisher: Wiley-Blackwell
• Year: 2011
• Print ISBN: 9781444333381
• eBook ISBN: 9781444392388
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Construction & Architectural Engineering
• Index: Technology & Engineering

The book contains the papers developed from the presentations at the Distributed Intelligence in Design Symposium, held in Salford in May 2009.In this context, Distributed Intelligence refers to the interdisciplinary knowledge of a range of different individuals in different organisations, with different backgrounds and experience, and the symposium discussed the media, technologies and behaviours required to support their successful collaboration.

Thebook focusses on:

• how parametric and generative design media can be coupled with and managed alongside Building Information Modelling tools and systems
• how the cross-disciplinary knowledge is distributed and coordinated across different software, participants and organizations
• the characteristics of the evolving creative and collaborative practices
• how built environment education should be adapted to this digitally-networked practice and highly distributed intelligence in design

The chaptersaddress a range of innovative developments, methodologies, applications, research work and theoretical arguments, to present current experience and expectations as collaborative practice becomes critical in thedesign offuture built environments.

Part 1

1 Of sails and sieves and sticky tape

Bryan Lawson

This chapter concentrates on creative conceptual design and will not deal with downstream issues of detailed technical development or the generation of production information. The title of the Distributed Intelligence in Design symposium used only the word ‘design’. It is not until we got into the description of the conference theme that the word ‘production’ appeared. From then on ‘design’ and ‘production’ were as inexorably linked like ‘love and marriage’, as the song would have it. I challenge that assumption, all the more dangerous because it is implicit rather than explicit. In particular, I am concerned about the dangers of developing knowledge structures and applications for the production stages of construction that then wash back into design.

In a paper very well known in the design research world, Nigel Cross asked us: ‘Why isn’t using a CAD system a more enjoyable, and perhaps, also more intellectually demanding experience than it has turned out to be?’ Nigel argued that CAD may in some cases be quicker, but it is more stressful and there is no evidence that the results are better (Cross 2001).

I have taught in schools of architecture that are privileged to have the most able students of their generation. Whether in Sheffield, in Singapore and China, in Holland and Norway, in Sydney or America, I find the same thing. Students no longer think computers are either difficult or extraordinary; they are just a fact of everyday life. Many architecture students find that computers are not a very appealing part of their design lives. My graduates regularly give voice to a tormenting dilemma. Listing their considerable CAD skills in their CVs often helps them to get a job. But they live in fear of their project leaders discovering this, especially during their years of practical training. They return telling tales of being sat for months in front of a computer exploited as ‘CAD monkeys’. They have a plethora of terms for the abuse of computers in design, from ‘Photoshop rash’ (the over-application of textures and photorealistic skies) through ‘Macfontopia’ (indiscriminate proliferation of fonts made so easy by the Mac) to ‘Modelshop bargains’ (an over-reliance on 3-D modelling forms). I have censored the names they have for principal partners who insist on all this nonsense to impress their clients but are unable to do it themselves.

Our students were further discouraged when one of their number won a major national award for his use of CAD and yet, with the same submission, failed his master’s degree.

My professional experience is hardly more encouraging. I am part of an international consortium that won the competition to masterplan about 100 hectares of central Dublin known as Grangegorman. The lead architects, Moore Ruble and Yudell, are in Santa Monica; the transportation planners, Arups, and conservation consultants, Shane McCaffrey, in Dublin; the landscape architect, Lutzow 7, in Berlin; the sustainability engineers, Battle McCarthy, in London; and I am in Sheffield. We met as a team roughly once every six weeks, but otherwise relied entirely on IT to communicate across continents and time zones.

What software did we use? Obviously we had an FTP server that held jpegs, Microsoft Office documents and pdfs. The size of such files was already a problem and exchanging CAD files or other active documents was impractical. We largely relied on Word and Acrobat Reader. We used some very basic 3-D modelling software but created inert pdf files for exchange. We often sketched over them by hand, digitised and returned similarly dead files. It worked OK, but relied heavily on the trust established in the face-to-face workshops where we sketched by hand and looked at physical models. How disappointing after all these years!

The vast majority of the software most architects use today is generic. We manipulate pixels and vectors and occasionally use crude solid modellers and generic word processors and spreadsheets. The few big CAD systems are not specifically architectural, although some have what you might call an architectural accent such as the Bentley suites. Even these are really AEC rather than architectural in their way of thinking and working. When we recently did research with architects in the UK using the Bentley suite, we struggled to find any operating the latest version or making sophisticated use of its supposed architectural features.

Design as a cognitive task

From a psychologist’s perspective, our view of the possible role of the computer has changed and I want to suggest it is now in need of another paradigm shift to take us forward. The first people in this field (Whitehead and Eldars 1964, Auger 1972) expected that long before now computers would be designing buildings.

More recently, I have worked with cognitive scientists who are in what we might call the ‘computation theory of mind’ camp. This artificial intelligence theory in essence claims that eventually we will make computers do what our brains can do; the only problem is we have not yet got big enough and powerful enough machines and sufficiently sophisticated software languages. Many of us have felt uncomfortable about this for a while, but each time we threw a new challenge down they would eventually rise to it. ‘OK,’ we said, ‘computers can play noughts and crosses, but they can’t play draughts.’ They did, so we challenged them to play chess. Of course they did that too. Then we cheated and demanded they beat the best human players. Guess what? They did, although no one seriously claims the software uses human-like cognitive processes.

At last cognitive scientists are seeing design as the challenge that collapses this house of cards. You could trace this argument through Jerry Fodor’s The Language of Thought (Fodor 1975) and then on to Dreyfus’ What Computers Still Can’t Do (Dreyfus 1992) and Vinod Goel’s Sketches of Thought (Goel 1995). AI claims that we can represent all useful knowledge through symbol systems and thought through the manipulation of those symbols. Our view now is that it does not seem possible to represent design knowledge and processes in this way. The leap from chess to design is not the same sort of thing as the step from draughts to chess. It is fundamentally different. This is beautifully illustrated through the famous paradox that Bar-Hillel advanced to show the unfeasibility of automatic language translation (Bar-Hillel 1964).

He asks if we could understand the sentence ‘The box was in the pen’. At first it might sound like a transposition error. But if it was in the context of a child looking for a toybox and possibly being in a playpen, then we can work it out. However, there simply is nothing in the symbol collections themselves that gives this away. We have to bring other knowledge into play and the symbols give no clues about that knowledge, what it might be or how it might work. We do not know how to make a computer that could work this out; and yet we find it easy. Designing is full of this sort of knowledge and this sort of thinking. In fact, they are at the very heart of creative designing.

At an RIBA CAAD symposium a software developer prefaced many remarks with the phrase ‘the trouble with architects is…’ I suggested that if the vast majority of architects behaved in the same way there were two possible explanations. The first was that all the most stupid people in the world had by chance chosen to become architects. The second was that perhaps they had adapted to their situation intelligently. So we had better darned well try to understand not just how architects think, but why. This idea offers a small creative leap that may help re-orientate us here. Once we start to think about the cognition of designing rather than of generating production information, we might not see the architect as part of the construction industry but rather as part of the design industry. This is quite a paradigm shift and I think a necessary one.

Lawson and Dorst lay out a description of what constitutes design expertise (Lawson and Dorst 2009). The model we develop shows a series of levels, rising from the novice through the advanced beginner and competent up to the expert and master and, finally, the visionary. One key finding is that designers operating at higher levels of expertise do not simply do the same things as lower-level experts. They are not quicker, better, more accurate or efficient. They actually do quite different things. In a curious way, they think less.

This model fits into a more generic set of ideas about cognitive expertise. De Groot showed that chess grand masters did very little analysis of board situations but rather recognised them (De Groot 1965). Advanced architects similarly recognise design situations. They can see parallels with other situations they know well. That knowledge about situations also incorporates ideas that in chess would be thought of as gambits, or bits of solutions that can be used, each having advantages and disadvantages. Complex situations may be made up of many of these. Architects talk of precedent, by which they mean the panoply of previous situations that can be brought to bear on the case in hand. Unlike lawyers who seek to show the accuracy of precedent, architects seek to interpret it more creatively and to draw it from apparently remote sources. This is a key feature of what we normally describe as creativity.

What this model also shows is that the cognitive support we might need as novices is quite different from that we might need when we are competent and certainly when we are masters or visionary designers. Since I seek excellence rather than the mundane, I am interested in how this affects education and the impact that such ideas might have on the higher levels of architectural design.

What is so different about design?

A key question you might ask here is: ‘What is it then that is so different or special about designing as a cognitive task that makes architects think in such peculiar and infuriating but ultimately fascinating ways?’ The answer to this question is long and complex, but some key points can be developed here with specific reference to how we might develop computer tools to aid distributed intelligence in design.

Design is not like chess. When I was recently designing a garden shelter, I had just spent time in Bali looking at their special way of designing traditional houses and temples. I had seen the Pondoks crafted by rice workers to allow them shelter from the intense midday sun in the open terraced fields dug out of the lower slopes of the sacred mountain. Knowing this, it should be clear that the design of my ‘pondok’ was heavily influenced by ideas from Bali, reinterpreted for our landscape and climate and my purpose. There is nothing clever or extraordinary about this; it is the way architects work. Had I been in Africa or South America rather than Asia, it is likely my pondok would have looked different. Design relies, then, on unbounded knowledge. No statement of the problem can symbolically encode information that gives reliable or comprehensive clues as to the kinds of knowledge that might usefully be employed in solving it.

For more problematic features of this world of design cognition, we turn further east to Sydney Opera House. This building is special because it has become so well loved, memorable and symbolic. It represents the unique place in which it belongs, Sydney Harbour, a new culturally progressive Australia, the time it was built and many other ideas. It is fascinating not just as a product but also as a process that has been well documented and teaches us many lessons about designing.

Central to the design are the great concrete sails that simultaneously perform many tasks for Utzon, the architect. They create a magnificent composition sitting perfectly on Bennelong Peninsula jutting out into the very heart of Sydney Harbour. They act as a perfect counterfoil to the famous bridge against which they are so often photographed for that reason. They subtly reflect the sails of the myriad small yachts that often surround the building. Of course, they also house the great spaces of the opera auditorium, the concert hall, the smaller restaurant and the public domain. They create opportunities for solving the tricky problems of threading services through such a complex and demanding set of volumes. They offer a structural system that is self-explanatory, efficient and beautiful when exposed. I could go on.

How can one mind arrive at a single device that simultaneously does so much on so many levels? In truth, the sails perform far better at some of their tasks than others. They leave spaces that have poor acoustics, though that is not really Utzon’s fault. They insult and discriminate against the disabled. They make life hell for stagehands; ridiculously, the public approach is from the stage end of the opera house. It is well known that Utzon designed the sails before he knew how to build or even draw them and this was one of the factors that would drive the initial contractor to financial ruin. Again, I could go on.

And yet we forgive the building all these inadequacies because it is so magnificent in so many other ways. To have become one of the best-known buildings in the world with all these faults shows just what a fantastic achievement it is. It narrates a very human story of genius that succeeded in the face of so many difficulties and yet also failed our unreasonable expectations of perfection.

So what do we learn here? Design depends on integrated responses to many disparate factors in one single device in ways that could not possibly be predicted from any symbolic representation of requirements. These factors cannot be measured against criteria with any common metric for success. Which of us can say how many more stairs we are prepared to walk up in order to get the memorable view that Utzon creates for the interval promenaders out in the middle of the harbour?

New ways of communicating with computers

Architects must be using extraordinary mental gymnastics when designing. This implies the existence of a multidimensional cognitive structure that enables multiple ideas to be considered and developed. So if computers are going to assist us in designing, surely weneed to converse with them in ways that are at least as sophisticated as we might use when working with other designers. Is this realistic?

Some 30 years ago, my research group developed a suite of CAD programs for designing architecture known as GABLE (Lawson and Roberts 1991). They were founded on the principles of intelligent building modelling and on some key ideas about the nature of architectural design processes. They allowed architects to describe buildings in a variety of cognitive modes observed to be in common usage (Lawson and Riley 1982). Thus one could draw elements such as walls, windows and doors and GABLE would infer a spatial model. Alternatively, one could move, combine or divide spaces and GABLE would update the elemental model.

Back in the 1980s this system was in international use in both practice and education. We learned a huge amount from its use, not so much ...

Table of contents

• Cover page
• Contents
• Halftitle page
• Title page
• Copyright
• Note on editors
• Contributors
• Foreword
• Introduction: Distributed intelligence in design
• Part 1
• Part 2
• Part 3
• Part 4
• Index