Distributed Intelligence In Design E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 474

Veröffentlichungsjahr: 2010

Beschreibung

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. The book 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 chapters address a range of innovative developments, methodologies, applications, research work and theoretical arguments, to present current experience and expectations as collaborative practice becomes critical in the design of future built environments.

Leseprobe

Contents

Note on editors

List of contributors

ForewordPaul Richens

Introduction: Distributed intelligence in designTuba Kocatürk and Benachir Medjdoub

PART 1

1 Of sails and sieves and sticky tapeBryan Lawson

2 Distributed perspectives for intelligent conceptual designVolker Mueller

3 Distributed intelligence or a simple coherent mental model?Chris J. K. Williams and Roly Hudson

4 Sharing intelligence: The problem of knowledge atrophyPeter Brandon

PART 2

5 Pedagogical frameworks for emergent digital practices in architectureBrent Allpress

6 Emergence and convergence of knowledge in building production: Knowledge-based design and digital manufacturingEduardo Lyon

7 Artifact and affect: Open-ended strata of communicationMatias del Campo and Sandra Manninger

8 Digital tools for creative hingesSean Hanna

PART 3

9 The effects of integrated BIM in processes and business modelsArto Kiviniemi

10 Integrated building design for production management systemsRita Cristina Ferreira

11 Flexibility, semantics and standardsRobin Drogemuller and John H. Frazer

12 Examples of distributed intelligence on large-scale building lifecycle projectsMartin Riese

PART 4

13 Rapid practice expansion through strategic design computationCristiano Ceccato

14 Algorithmic modelling, parametric thinkingNeil Katz

15 Interview with the Specialist Modelling Group (SMG): The dynamic coordination of distributed intelligence at Foster and PartnersHugh Whitehead, Xavier de Kestelier, Irene Gallou and Tuba Kocatürk

16 Interview with Lars Hesselgren, Director PLP ResearchLars Hesselgren and Benachir Medjdoub

17 Geometry, topology, materiality: The structural parameters in a collaborative design approachManfred Grohmann and Oliver Tessmann

Index

Distributed Intelligence in Design

This edition first published 2011

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Library of Congress Cataloging-in-Publication Data

Distributed Intelligence in Design Symposium (2009 : Salford, Greater Manchester, England)

Distributed intelligence in design / edited by Tuba Kocatürk, Benachir Medjdoub.

p. cm.

Includes bibliographical references.

ISBN 978-1-4443-3338-1

1. Building–Information services–Congresses. 2. Architecture–Information services–Congresses.

3. Distributed artificial intelligence–Congresses. I. Kocatürk, Tuba. II. Medjdoub, Benachir. III. Title.

TH216.D57 2011

720.285'63–dc22

2010029073

A catalogue record for this book is available from the British Library.

This book is published in the following electronic formats: ePDF [9781444392371]; ePub [9781444392388]

Note on editors

Dr Tuba Kocatürk an architect and a Senior Lecturer at Salford University, UK. She currently leads the MSc Programme in Digital Architectural Design at the University of Salford. Her previous academic appointments include Middle East Technical University (Turkey), Delft University of Technology (The Netherlands) and Harvard Graduate School of Design (USA). She has taught, conducted research and published extensively in the areas of digital architectural design. Her current research interest is the emergent socio-technical and cognitive frameworks in architectural design and production.

She co-founded and is currently co-chairing the Free-Form Design Sub-working group of the IASS (International Association for Shell and Spatial Structures). She is the co-editor of Virtual Futures in Design, Engineering and Procurement.

Dr Benachir Medjdoub is a qualified architect with a PhD in Computer Science from Éole Centrale de Paris. In 1997, he joined the Martin Centre at the University of Cambridge as a Research Associate, where he has worked on several funded research projects in the area of parametric design and multi-objective optimisation techniques. In 2001, he was appointed as a Lecturer at the School of the Built Environment, University of Nottingham, where he taught and led research in the areas of digital architectural design. Benachir’s research work has included the development of software solutions applied to architecture and building services, and the use of virtual and mixed reality in architectural design representation and communication. He was the Principal Investigator of several projects funded by the EPSRC and industry, and he has published extensively in the above areas.

Contributors

Brent Allpress

RMIT, Australia

Peter Brandon

University of Salford, UK

Cristiano Ceccato

Zaha Hadid Architects, UK

Matias Del Campo

SPAN, Austria

Robin Drogemuller

Queensland University, Australia

Rita Cristina Ferreira

DWG Arquitetura e Sistemas, Brasil

John H. Frazer

Queensland University, Australia

Irene Gallou

Foster + Partners, UK

Manfred Grohmann

Bollinger + Grohmann, Germany

Sean Hanna

University College London, UK

Lars Hesselgren

PLP Architecture, UK

Roly Hudson

School of Architecture, Dalhousie University, Canada

Neil Katz

Skidmore Owings & Merrill, USA

Xavier de Kestelier

Foster + Partners, UK

Arto Kiviniemi

Salford University, UK

Tuba Kocatürk

Salford University, UK

Bryan Lawson

University of Sheffield, UK

Eduardo Lyon

Universidad Católica, Chile

Sandra Manninger

SPAN Architecture & Design

Benachir Medjdoub

Salford University, UK

Volker Mueller

Bentley Systems, Germany

Martin Riese

Gehry Technologies, Hong Kong

Oliver Tessmann

Bollinger + Grohmann, Germany

Hugh Whitehead

Foster + Partners, UK

Chris Williams

University of Bath, UK

Foreword

Paul Richens

The symposium at Salford in May 2009 brought together around 100 experts on the use of digital technology in architectural design. They included architects, CAD experts, people from the software industry and academics. The overwhelming impression was one of transition: people are experimenting, techniques and tools used last year will be superseded by the next, each project is handled differently from the one before. Everything is fluid: representations, tool sets, workflow, team structure, personnel and even philosophy. Consensus was certainly far away, but two ideas were clearly gaining significant traction. One was building information modelling (BIM) and the other parametric design (PD). As the symposium got under way, it became clear that there was considerable polarisation: most speakers (those from the software industry excepted) were proponents of one or the other.

BIM was described as bringing the discipline of database design to bear on the documentation of a building prior to construction. The model is shared by the entire team, describes everything just once, and includes semantic as well as geometric information. It facilitates interoperability, and avoids the inconsistencies that easily arise from multiple redundant representations. It is seen by its proponents as a platform for all kinds of analysis and production processes – and why not design as well?

PD is fundamentally a geometric technique. A design is represented as a Euclidian construction, where certain relationships are fixed, but other quantities (the parameters – positions, angles or lengths) can be varied. PD software allows the parameters to be adjusted and works out the consequences.

Support from speakers at Salford was measured; unlike BIM, PD is not seen as a universal problem-solver but as one of many tools useful for conceptual design and the geometrical aspects of design development. Their disagreement with the BIM people centred on the issues of multiple as opposed to single representations. Models, they say, are abstractions, and you need to use different abstractions for different purposes, different modes of thinking; a ‘federation of models’, as Hugh Whitehead eloquently said. Ambiguity is rather a benefit when you are working things out. BIM is an abstraction highly suitable for ordering materials and constructing a building, but not for designing it, and should perhaps be built by the contractor (as we heard was happening in Hong Kong) rather than the architect.

PD is clearly generating a lot of excitement. It offers an essential plasticity (easier to manipulate than clay or a sandbox) while simultaneously enforcing rules of arbitrary sophistication. This is what interactive CAD was always meant to be and, having at last got there, several distinct ways of using it are emerging. One is to explore many variants of the same basic design, by altering the parameters in a systematic way and inspecting the results, perhaps through drawings, 3D printing, or some kind of environmental or structural analysis. When coupled to analysis, this leads to the possibility of some sort of optimisation, or at least sensitivity analysis. In the design of tensile structures, engineers call the analogous process ‘form finding’, and it was interesting to hear the term being used in the seminar by architects.

A second use is to defer certain decisions, perhaps quite important ones such as controlling dimensions, to late in the design process. If a thoroughgoing PD model is employed, the change can be made and the consequences computed automatically. This can be very important; indeed, at Foster’s ‘change propagation is the issue’. There are many ways to construct and parameterise a model, and the choice you make encapsulates a decision as to which kinds of future change will be facilitated and which not.

A third use is within a design, to represent elements that are repeated not exactly but with some systematic variation in size or shape. It is striking how architecture has for thousands of years depended on regular repetition of identical elements – columns, arches, windows, vaults. The very first PD building (Grimshaw’s Waterloo Station) demonstrated systematically varying trussed arches, and the considerable potential PD has for revolutionising architectural language is increasingly being recognised – perhaps most eminently by Zaha Hadid’s office.

Another entrenched architectural tradition, a dependence on straight line and circle and the simple extrusions and surfaces of revolution they can generate (the Phileban solids), has already yielded to some extent to PD with the rather controversial development of ‘blob’ architecture. This new-found freedom is being exploited rather tentatively, for reasons of constructability. ‘Design for manufacture’ has entered the conversation, and a new process called ‘rationalisation’ is everywhere under discussion, meaning the breaking up of curved elements into pieces which are piecewise developable, and preferably cylindrical or plane. Two approaches are available under PD, and the preferred mode is becoming a rather significant differentiator of design style. In ‘pre-rationalisation’ the parameterisation is based on lines and tangential arcs, so that only simple surfaces can emerge. In ‘post-rationalisation’ an arbitrary doubly curved surface is processed into simpler panels by an optimisation procedure.

The theme of the seminar was distributed intelligence, and quite a number of views emerged as to where intelligence is to be found. For the BIM people intelligence is in the data; for PD it lies in the system of constraints and freedoms that ‘capture the design intent’. For Chris Williams it lies in the software, a sharing of knowledge by the programmer who put it there for the benefit of the user who employs it. As for the network, ‘information systems reflect management systems’ we were told, so perhaps the PD/BIM divide is a reflection of the shift in design/build responsibilities that has come from modern methods of procurement. Designing a team organisation and workflow is seen as crucial to the delivery of a project (particularly for the propagation of change), so in that sense there is intelligence designed into the network.

Peter Brandon discussed the nature of expertise. Bryan Lawson reminded us that intelligence resides in the people, and that design intelligence is peculiarly hard to characterise. One thing is certain: expert designers think in substantially different ways to beginners, and the kinds of cognitive support an individual finds helpful change as experience develops.

Several speakers from practice reported on how they are forming specialist modelling groups in order to deploy PD. It is possible that a distinct discipline is beginning to emerge, that of architectural geometer, with a rather wide range of modes of interaction with other design team members. Indeed, designing the workflow for a particular project is perhaps the major responsibility, ahead of construction of a parametric model. Students are emerging from the universities with a high degree of fluency in scripting and parametric tools, but they need to acquire a considerable amount of architectural or engineering project experience before they can fill the specialist role.

As to the future, there seemed to be agreement that the next step in PD is to integrate some structural, environmental and constructional intelligence into the underlying geometrical framework, so that form-finding can proceed in a balanced way, following the principles of concurrent engineering rather than the sequential processes encountered most often in architectural practice today.

Introduction: Distributed intelligence in design

Tuba Kocatürk and Benachir Medjdoub

In the world of architecture, the emergent digital technologies have taken a significant role in how we create, collaborate, design and produce. This book attempts to address the current socio-technical transformation in the architectural industry, as a new paradigm. The increasing use of advanced 3D knowledge-rich parametric/generative tools, combined with information modelling systems and digital prototyping technologies, is already enabling radically new ways of designing and coordinating among the many actors in architectural design and production. Architectural and engineering design is becoming more and more a digitally networked practice. This has led to more distributed activities within and across disciplines and involves embedding intelligence in the formation and actualisation of spaces. Innovation in design is no longer recognised as the creation of a single product by a single designer, but as the outcome of an iterative and dynamic coordination of a cross-disciplinary intelligence that is distributed across various digital tools, people and organisations in a social context. The book tries to uncover the ways in which digitisation and digital tools have recently been adopted within the work practices of multidisciplinary firms and the evolving socio-technical networks and organisational infrastructures in architectural practice.

For quite some time now we have been debating the impact of new technologies on architectural practice and the emergent formal vocabularies. The generative, representational and collaborative potentials of various digital media and embedded computing are already well documented and discussed in various conferences, biennales and publications. Yet it would be fair to say that although the potential is huge and endless, the technological transformation the architectural profession is going through at present has not been as smooth as one would have hoped. The institutional and social structures of the building industry, as well as the high variation in its technical systems and practices (e.g. construction technologies, fabrication tools, computing software etc.), build up multiple barriers to utilizing the collaborative potential of new digital environments fully (Shelden 2006). Moreover, different digital media and collaboration styles offer radically new and, most often, varying methodologies to merge design with execution. Many practices struggle with the adoption of technologies into their work, as there is not yet any formulated method or theory of how to choose the best possible tools and organisational structures that will suit the designers’ preferred design approaches or preferred set of media. Moreover, there are more fundamental issues in the utilisation of these diverse sets of digital media. For example, although BIM (building information modelling) systems provide better data transfer and integration, they do not entirely support the creative processes occurring during the conceptual design stages. Similarly, there is a computational limitation in the design aspects that cannot be addressed parametrically with the current capabilities of various parametric and generative software packages.

How is the architectural industry responding to the possibilities offered by these technologies? How is the industry adopting and utilising these technologies and how is this adoption transforming the dynamics of practice? One obvious observation is that innovative practices are not necessarily merely adopting design technologies but are finding innovative mechanisms to structure and coordinate multidisciplinary design intelligence through various media, customised workflows, organisational structures and complementary activities. With this book, we are not aiming to start yet another anachronistic debate on ‘architectural design’ and technology, as the two are already inseparably linked. The book rather attempts to discover the controversial relationship between design innovation and technology. Technology is indeed a critical enabler of innovation, however new human networks and work practices, in their turn, facilitate the emergence of new methods to deal with the emerging knowledge and complexity affecting the ways in which the technology is adopted and used. This instrumentalisation entails the ways in which humans mediate between different media, facilitating new coordination mechanisms across various interdisciplinary actors and representations. Consequently, we can observe the spontaneous emergence of highly complex socio-technical systems where both the human/organisational structures, and the IT capabilities are distributed, diverse and heterogeneous. In these varying socio-technical formations, the interaction of the architect(s) with different project participants through different media at different stages of the design process and the extent to which this interaction contributes to product and process innovation both vary.

We introduce the concept of ‘distributed intelligence’ to further investigate the socio-technical and techno-organisational repercussions of digitally driven processes in building design and production at large. Here the use of the term ‘intelligence’ has been a very careful and conscious selection which has become the current ‘intellectual dominant of early twenty-first-century post-vanguards’, as famously put by Michael Speaks in his Intelligence after Theory article (Speaks 2007). In this text, Speaks mentions a new group of intelligence-based practices and their unique design intelligence that enables them to innovate by learning from and adapting to instability. This group is more concerned with ‘plausible truths’ generated through prototyping than with ‘received truths’ of theory and philosophy. Here, plausible truths refer to a quick way of testing ideas by doing, or making them (prototypes), and are thus the engines for innovation. In other words, prototypes create a ‘design intelligence’ by generating plausible solutions that become part of an office’s overall design intelligence. For example, a series of rapid prototyping models or generative design codes can enable the mass production of unique design solutions invented and deployed by an architectural design firm. In such a practice, design becomes more than a problem-solving exercise and creates new questions and solutions simultaneously, where the creative process is driven by an embedded intelligence.

We add a ‘distributed’ dimension to ‘design intelligence’ to end up with an even more complex entity with multiple interacting dimensions which need to be managed and coordinated accordingly. An important aspect of this complexity is the distribution of ‘design knowledge’ – the availability and orchestration of tools and ideas from different disciplines. Another aspect is the spatial distribution of ‘interacting agents’, which could further be distributed temporally when an artifact is being repeatedly modified by different user-creators over time. Finally, technological distribution involves understanding and distinguishing which medium, tool or technology is better suited for particular phases of a design. It is also important to note that architectural production is not just market, theory and/or technology driven, it also has a critical socio-cultural dimension which typically changes more slowly and incrementally than science and technology. The change is continuous, incremental and multifaceted. Therefore, in the context of this book, the uncovering of distributed intelligence refers to a multitude of interdisciplinary design knowledge constituted by different individuals with different backgrounds and experience, the media and technologies that support their individual thoughts and inter-individual communication and the social network that links them together.

The chapters in the book are compiled from the presentations and discussions of the Distributed Intelligence in Design Symposium which was organised in May 2009 by the Mediated Intelligence in Design (MInD) research group at Salford University. The symposium brought together some of the best practitioners, thinkers and educators from around the world to discuss and debate the emerging concept of distributed intelligence in design as an attempt to answer the following questions:

How have parametric and generative design tools moved the boundaries offered by conventional CAD tools and enhanced creative thinking?How is cross-disciplinary intelligence distributed and dynamically coordinated across different design/modelling software packages, actors and organisations?What are the characteristics of the evolving creative and collaborative practices (e.g. emerging skills, organisational and cognitive structures)?How can architectural education adapt to this digitally networked practice and highly distributed intelligence in design?

The chapters are grouped under four main sections, each addressing a combination of methodologies and theoretical arguments, academic research work, innovative developments and state-of-the-art applications and industry experience.

From a future-oriented perspective, the book aims at presenting where we are and what can be expected in the next generation of architectural and engineering design as a collaborative practice.

References

Shelden, D. (2006). ‘Tectonics, economics and the reconfiguration of practice: The case for process change by digital means’. Architectural Design 76(4): 82–87.

Speaks, M. (2007). ‘Intelligence after theory’. In A. Burke and T. Tierney (eds), Network Practices: New Strategies in Architecture and Design. Princeton, NJ: Princeton Architectural Press, pp. 212–216.

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 about CAD but about designing itself and about the complexity of knowledge representation in design. Eventually GABLE failed for a number of reasons, but the main intellectual failure turned on some unwarranted assumptions that are still going unquestioned today.

We must decide the extent to which we expect such systems to be central or peripheral to the creative design process. John Lansdown asked this question decades ago, but few have explicitly attempted convincing answers (Lansdown 1969). He pointed out that there were two fundamentally different strategies we could employ, which he called ‘ad-hoc’ and ‘integrated’. He foresaw a wide range of applications, for example thermal evaluation, daylighting studies, visual form, costing, structure and so on. He realised that such applications need different though overlapping sets of data about features of the design.

Assuming that as designers we might like to be able to see how well our design is working on a number of criteria, how do we input the necessary information? In what Lansdown call the ‘ad-hoc’ strategy, we input the information needed as we use each individual application. So if we want to perform a simple steady-state thermal evaluation, we would need u-values and the areas of the external skin components. If we want a natural lighting study, then geometry, transmission, reflection data and orientations would be required and so on. This means a very halting process for the designer. Every time you want to examine the design along some dimension, you have to stop and input data.

An illustration of how impossible this would be can be seen from simply observing students. They are struggling to develop an integrated response, a task already almost too demanding for their early level of expertise. They need advice from a range of tutors, about architectural form, construction, structures, environmental control and sustainability. At Sheffield we now have this in-house, but previously structures was a service taught by our civil engineering department. To get advice on structures students had to phone up, make an appointment and then go to the other side of the campus. They did not do it, of course, and we saw many projects that were innovative climatologically but very few that were innovative and creative in structural terms. This ad-hoc idea simply does not work for designers. It would not work for the sails of Sydney Opera House. Utzon could never have used it.

So we turn to Lansdown’s ‘integrated’ strategy and link all the evaluation packages to a single database, now variously described as building information models or n-D models. Each evaluation then runs immediately.

Salford and Sheffield universities collaborated on a research project to create support systems to record and make explicit design rationale (Cerulli et al. 2001). There were several objectives. First, the need in a multiprofessional, and often not co-located, team to know who is making what decisions and why. This becomes especially important when things happen in parallel. The classic example is the scenario in which the architect issues a general arrangement floor plan and the M and E engineer starts to run services through routes that the structural engineer is busy blocking. The architect is often left trying to spot this and we all think that CAD clash checking would be the answer.

However, things often get even messier. Our drawings show the decisions but not the reasoning. Later on, someone who may not understand the reasons changes things without realising the damage they are inflicting on the design. Being able to see the thinking behind the design at every stage is far more important than just the clash checking. In the design of Sydney Opera House they built a huge perspex model so everyone could see how spaces were interconnected and related. Today we would think of doing this on a computer. Somehow the physical model still does the job better. Incidentally, this model is now seen as a security risk, since the knowledge it imparts could greatly facilitate terrorism.

The Sheffield–Salford project worked with the Bentley software and logged the complete state of the model, traced all additions and changes and recorded the rationale. Instinctively, we decided to plug our software into the CAD software. All very logical: as you called a routine to add, delete or edit a model element, you automatically accessed the rationale capture software. However, field trials revealed that this was hopeless. More often than not, key decisions were taken away from the computer model.

By way of illustration, you can see a most creative process at work in the Philadelphian offices of Bob Venturi when designing his famous extension to the National Gallery in Trafalgar Square (Lawson 1994). One of Venturi’s key forming concepts in this design is how the new architecture relates to the existing Wilkins’ building, so famously described by Prince Charles as ‘a much loved friend’; this, of course, when he so unfairly criticised the previous competition-winning design by ABK. Venturi had the original façade computer modelled, plotted out and cut up into pieces with scissors. These pieces were then stuck around his new physical models with sticky tape. How ironic to see a computer metaphor being used far more creatively in its physical reality.

The normal situation, then, is that key design decisions are often made over sketches or physical models, on telephone calls or at meetings, on drawing boards and sketchpads. Mostly they are the results of ‘conversations’ involving much talking and waving hands in the air. Often someone is deputed to input the new state of affairs into the computer model. At that time the rationale is either not available or it is incorrectly guessed. The computer model is simply not where the action is.

A further problem with the integrated model is that it quickly becomes a production tool rather than a design aid. Designers find that you have to specify not only geometry but also materials and construction in such depth that you have effectively generated not a design model but a production model. Does this really matter? Well, yes it does. It is simply unfeasible to argue that tools do not have an impact on processes and that processes do not have an impact on the end product, the architecture itself.

Take the representation of free-form design. Surely this must promote creativity? At last, sophisticated mathematics allows us to compute locations on irregular surfaces. Gehry Technologies have contributed to the migration of ideas from aeronautical design into architecture. Bill Mitchell claims that the use of this in Frank Gehry’s ‘remarkable late projects will ultimately be remembered not only for the spatial qualities and cultural resonances they have achieved, but also for the way in which they have suggested that everyday architectural practice can be liberated from its increasingly sclerotic conventions’ (Mitchell 2001).

Of course he is right, Frank has created a remarkable new form of architecture. But look more carefully and there are two problems here. First, Gehry does not himself use this software in design. Indeed, Zeara claims that ‘the computer was introduced into Frank Gehry’s office in a way that would not interfere with a design process that had been evolving over thirty years’ (Zeara 1995). Lindsey tells us that ‘Gehry does not like the way objects look in the computer’ and that he avoids looking at the computer screens in the office (Lindsey 2001). He not as eccentric as you might think. My work on Santiago Calatrava, one of the most creative minds in free-form design, shows that he also does not like to use computers. This man is even a fully qualified engineer as well as being an architect, but he prefers to sculpt physical models and only relies on computers for finite element analysis.

This is quite understandable, since software driven by the complex mathematics of such esoteric devices as Bezier curves or non-uniform rational B-splines is hardly user-friendly. The input of control point locations and tensions on curved patches is not for the fainthearted! It is certainly not intuitive and far from the ‘conversation with the drawing’ discussed earlier. So Gehry designs with much more plastic materials such as crumpled paper and other expert users have to negotiate these into the computer. Calatrava collaborates with a Swiss watch-maker turned modeller who has become an integral part of his creative process.

The second problem here is in Mitchell’s reference to the sclerotic conventions of architecture. He wants us to believe that all architects, their clients and users are desperate to get away from geometry in architecture. There is no evidence to support such a thesis. Instead, I will present one rather powerful anecdote in contradiction. Having become very interested in what Frank Gehry and Jim Glymph are doing, I realised that a very famous piece of architecture indeed could now have been realised very differently. In his original submission for Sydney Opera House, Jorn Utzon included a model showing irregularly curved surfaces for the sails. It is well documented that once the competition was won, Utzon and Ove Arup puzzled over how to build these (Weston 2002). Eventually they resorted to mapping them all onto the surface of a single sphere. Not long before he died, I showed Utzon that the Gehry technology software would now allow him to build the original design and I asked what choice he would make today. The answer was emphatic. He would keep the geometry and the design as finally realised. He was always looking for some rationality and order. To this day, of course, the stunning result is as he wanted, a combination of romantic reference and yet coherent order. As Utzon said in his response to me: ‘I am not Frank Gehry.’ Thank goodness we have been lucky enough to have both of them, but clearly Mitchell’s implied idea that we all want to become just like Gehry is simply another example of technology push rather than market pull.

Unfortunately, that technology push can then extend through into the architecture itself. Take the case of the Opera House in Singapore. The design of this can be summed up as a couple of auditoria in boxes standing inside a huge glazed upturned kitchen sieve. When working at the National University in Singapore, I attended a long lecture from one of the software engineers employed on this project. It was their software that had led the architect to appreciate the feasibility of this design in this context. Remember that Singapore has a hot–wet tropical climate with temperatures around the year in the 30s, very high humidity and often daily torrential rain. A glass dome is hardly the first form that comes to mind in such a climate. Compare such an idea with the environmentally sustainable work of Ken Yeang, who tries to create a new regional identity for south-east Asia (Yeang 2006). In a kitchen sieve every cell is unique, as the square grid is resolved onto a curved surface. So in the Singapore dome every cell must have its own tailor-made shading device shaped to its cell size, and of course orientation in order to avoid unbelievably high solar gain. The software to achieve all this is indeed very clever!

The lecture reminded me of much of the silly technology push that surrounds us. The plethora of applications for the iPhone is a wonderful demonstration. I have an app that gives the phone the wonderful capability of acting as a spirit level. ‘Very clever,’ says everyone who looks at it. Of course, I have never used it. We still treat computers and their smaller palm-top offspring like circus animals trained to perform apparently clever but pointless tasks.

The nature of the computer model itself brings yet further potential remoteness from real design decision making. The art critic Adrian Stokes introduced the delightful distinction between what he called ‘modellers’ and ‘carvers’ (Stokes 1934). These are two distinct forms of thinking about space and form. Modellers would assemble a building from its components; carvers would craft it from its materials. The sculptor, who carves works with the grain of stone or wood, understands the material and even feels the way it wants to be. The great American architect Louis Kahn told us to ‘let a brick be what a brick wants to be’. In other words, he called for architecture that was carved, that worked with the grain of its materiality.

Conversations with the situation

We have a further pervasive problem: a fundamental misunderstanding about the nature of design expertise. In the mid-twentieth century when we first started to explore the nature of design processes. the dominant paradigm was that of problem-solving. Those of us who continue to research this field no longer see this as the only, or even the dominant, way of explaining the creative processes used by designers in general and architects in particular. Sadly, the developers of CAD have not caught up. Implicit in so much of the software is a problem-solving view. The newer view of reflective practice, pioneered and championed by Donald Schön, leads us in quite different directions (Schön 1984). In this paradigm the architect is not so much solving given problems as discovering them in parallel with developing solutions and even through the creation of solutions. In fact, already the words problem and solution are uncomfortable in this world. We now prefer to talk of ‘situations’ in which needs and possible actions are seen as existing in creative tension. Schön talked of reflective practitioners having ‘conversations with the situation’. In the case of architects this situation is often assumed to be represented through drawings, though other media are used too.

If we are going to support this process, we need to understand the methods of knowledge representation used in the drawings architects generate, not for others to see, but to develop their conversation.

Goel has compared the way designers work using ordinary manual sketches with the way they work using very simple computer drafting programs of the vectoring type, namely in this case MacDraw (Goel 1995). Six graphic designers were set the task of designing tourist posters while six industrial designers were asked to design a desk clock and a toddler’s toy. Goel analysed all the drawings produced by both groups of subjects using both manual and computer-based drawing systems. He showed that the drawings done with MacDraw were less dense and ambiguous than those completed by hand. This will not surprise anyone with any skill in drawing who has tried to use such software.

Disturbingly, Goel also showed that this had an impact on the nature of the design thinking and was in turn likely to affect the eventual outcome. The designers using MacDraw made significantly fewer ‘lateral transformations’ than their manual sketching counterparts. That is to say, they tended to persist with an idea for longer, ‘vertically transforming’ it. The inference here is that the less ambiguous MacDraw system allowed the designers less opportunity to ‘see’ different interpretations of their drawings. As a result, fewer ideas were explored in the process in roughly the same period of time.

Bilda and Demirkan tested designers on an interior design task using both manual drawing and a vectoring-based CAD system known as Design Apprentice (Bilda and Demirkan 2002). A retrospective reporting technique was used to get subjects to recall and describe their intentions by watching a video of the protocol. This study again showed fewer ‘cognitive actions’ when using the digital media.

A reasonable conclusion is that existing CAD systems use symbolic representations that do not map well onto the mental symbolic representations used by designers. As a result, working with such systems leads to a less rich mental world, since the drawings ‘talk back’ to us in less suggestive ways. Put simply, the conversation with the computer was less rich than the conversation with a piece of paper.

Kvan demonstrated something that raises other profoundly disturbing questions for the CAD movement (Kvan et al. 2003). Architecture students worked in groups using computer-based communications. One group had only text-based technology, while the other could exchange graphical information too. The results of the text-based groups were consistently more creative, original and interesting than those from the groups exchanging graphical information.

A more positive approach

So far my analysis suggests that attempting some computer aid that sits right at the centre of the creative design process is deeply problematic. This is perhaps a rather harsh lesson. First we had to give up the idea of computers designing. Now I am asking you to give up the idea of computers even helping us to design, at least in some central role.

So how can we be a bit more positive? The design expertise model suggests that one of the key tasks at the early stages of expertise development is the acquisition of precedent and of schemata that are used to organise them cognitively. In simple terms, students of architecture need to see and study a wide range of buildings, places, designed and natural objects and other cultural artifacts. While a few geniuses may manage without this, most of us cannot. A student who has not studied the Sydney Opera House, for example, is unlikely to be able to appreciate the ideas that it taught us. These would certainly include the notion of rationalising curved surfaces, how to compose them and the very powerful idea of a free-floating form hovering above a solid plinth. Again, I could go on.

Traditionally students learned these things through extensive travel, scouring magazines and journals and so on. They were always encouraged to carry with them a sketchbook. No architect I admire does not carry such a thing for the immediate and quick sketch to record and analyse. Excellent examples can be found from John Outram looking at Corb’s Ronchamp and Bucky Fuller’s Dymaxion House (Lawson 1994).

The digital camera, its connection to the computer and all the easy image-manipulation software linked to internet searches make for a different world. This technical advance also poses huge dangers, however. The student who had to travel saw in the flesh, as it were, a totally different experience to a Google Images file. The sketch relied on an eye–brain–hand process that forced a degree of analysis and brought understanding. We now have a generation of students arriving at schools of architecture who have not learned to sketch, have not learned to see, have not learned to analyse, in fact have not learned.

All is not lost. We have used simple solid modellers in exercises with novice students in which they build models of buildings and then deconstruct them to explore the conceptual structures that underpin their design ideas. In some ways this is very successful and illustrates an important principle of using computers that I have always thought desirable: we can actually do something new. Unfortunately, it is also still very crude. The software is far better at some kinds of geometry than others. It works brilliantly in this example with the architecture of the De Stijl movement. We need to develop software that is specifically targeted for this purpose, not for designing as such but for recording and analysing architectural form.

All this begs another hugely important question about the way we search for information. I used many of the same fundamental concerns to analyse how architects use libraries (Lawson 2002a). There are important lessons that many university librarians find as difficult to accept as some CAD enthusiasts do. My university built a major new library recently, except that we are not allowed to call it that. It is an ‘information commons’. The university then wanted to split our collections between the old and new in terms of undergraduate and postgraduate. When I refused to agree to give the librarian the list of undergraduate texts for architecture, he thought I was just being awkward. Not so. First, there is no overall undergraduate subject textbook for architecture and there never will be. Secondly, our students look at the latest journals. You would not expect either of these things in an undergraduate psychology course. Our students take few books out but spend hours in the library scanning, browsing and then sketching and arguing. The library is actually an integral part of the design studio.

Let us see at another example higher up on the expertise development staircase. When studying the work of one of our most successful and creative architects, I visited the office of his practice and heard three different people use the word ‘belvedere’. There is nothing extraordinary about this word, but even in an architect’s office this seemed too much of a coincidence. It was an example of something we have come to realise more clearly recently: expertise in design is not held only inside single heads but collectively and socially in organisations. This word brilliantly and incredibly efficiently stands for a whole set of architectural ideas that clearly this practice had been talking about. If you were not in on this you simply could not contribute to the design process they were using. This is real distributed intelligence at work in design.