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Co-authoring ArchitectureDesigner vs. So ware

Niroshan Gunasingam

Front coverImage from my design studio, script used to analyse arial photograph of my site

New Technology New Technology What has already been produced by New Technology? Technology - just a digital pen or something more? Tools Scripting Design and Generative Art - What does History show us? Art Fashion Music Devolution of the Author Authorship Man vs. Machine Is there an answer? Bibliography Further Reading Image CreditsGlossary

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Table of Contents

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New TechnologyHaving been out of further educa on for almost a decade and returning to study for my Diploma in Archi-tecture in 2010 I was amazed at how far technology had progressed. I was introduced to new so ware and digital fabrica on techniques that were simply not available to students when I studied for my Degree in Architecture. They were so amazing to me that they felt, and s ll feel today, magical. Last year I spent a lot of me learning about this new so ware and these new digital fabrica- on techniques and was especially keen to focus my

learning on Scrip ng so ware. The possibili es that it seems to present are exci ng and apparently without limita ons other than those required to make the end product ‘real’ and able to stand up according to physical and engineering laws.

During the course of my recent studies of this new lan-guage of scrip ng it became clearer to me that there is a current debate in today’s architectural world: Who is driving whom? The human or the scrip ng? The De-signer or the So ware? The ‘Man’ or the ‘machine’? For the last 50 years the speed of growth and development in computer technologies along with the rise of coder-developed CAD systems and designers with snippets of their own code, has le us with this ques on:

To what degree is the design authored by the so ware itself, the so ware designer or the so ware user?

It is this ques on that I shall be trying to answer during the course of this essay.

New

I should clarify a key term early on in this essay so that the a en on of the reader can be focused on the ‘meat’ of the argument rather than the o en circular and not always produc ve argument of etymology. On the face

of it ‘New’ is a seemingly neutral word. However , in much of my research it seemed to be a regular source of disagreement in terms of what actually cons tutes ‘new’ or rather ‘newness’ when people talk about it. What is new to one person is clearly not the same kind of new to another. The technologies that I discovered as new to me last year are far from new to those that have en-countered them already, or indeed, those that wrote the programs themselves. The ‘newness’ that I encountered in my detailed learning of it is diff erent again to the kind of ‘newness’ it is for someone who is reading about the existence of the technology for the fi rst me in these pages, or be er s ll, the ‘newness’ of it all for someone that has not even become aware of it yet. Whilst all of this is valid and could lead to a hiatus in the use of the word ‘new’ I am reques ng that you, the reader, take for the dura on of this essay, the word ‘new’ to refer to both ‘new to me’ and ‘newer to the realms of architecture in the context of the meline of architecture throughout its history up to its current state’.

I will simply refer to James Steel then, in the Epi(mul )logue of Algorithmic Architecture (TERZIDIS, 2006) and agree with him that “etymology works as a “trace” but not as a way to ensure, preserve or resurrect any “truth”.

There is a detailed glossary at the end of this essay, which should be referred to for explana ons of key words/ terminology and some mes to take as my use of a word in the context of this essay.

Technology

My personal journey into this newer world of computa- onal architecture began in the fi rst year of my Part 2

studies at Greenwich in ‘Atelier 13’. Prior to this me my knowledge of computers in architectural prac ce was limited to AutoCAD for 2-D drawing and the standard Microso Offi ce suite for documenta on and emailing. I had briefl y touched upon 3-D modeling using Autodesk’s

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3D Studio Max but in prac ce I had never had a call to use it. The Greenwich School of Architecture had not only the latest so ware technologies but it also had cut- ng edge equipment such as a 3D scanner, laser cu ers

and 3D printers. In ‘Atelier 13’ we learned about these wonderful new technologies with great vigour. It en-abled me to appreciate the nuances that can be found within this digital realm and how it can benefi t the archi-tectural process from digital manipula ons through to the actual fabrica on of my design.

Scrip ng genera ve algorithms that mimic processes in nature is infi nitely easier for architectural design-ers nowadays due to an increase in the computa onal power of modern computers. Designers can now explore new shapes using genera ve algorithms with these vari-ous so ware packages. I discovered the Grasshopper so ware during ‘Atelier 13’ studies and learnt that it is an incredibly eff ec ve mass-market plugin si ng over the Rhino 3-D modeling so ware and it therefore brings this visual scrip ng tool to a wider audience whereby you don’t need to be a programmer to produce programmed output. “Grasshopper is for designers who are exploring new shapes using genera ve algorithms, Grasshopper is a graphical algorithm editor ghtly integrated with Rhi-no’s 3-D modeling tools. Unlike RhinoScript, Grasshopper requires no knowledge of programming or scrip ng, but s ll allows designers to build form generators from the simple to the awe-inspiring.” (Grasshopper - Genera ve Modeling for Rhino)

Grasshopper works within Rhino and uses standard Rhino geometry but has its own slick interface window. Algorithms and manipulators are dragged, dropped and connected, as if they were being wired together like components on a circuit board, but with a simple visual ‘menu’ much like the Toolbars available to users in the Microso Offi ce suite of so ware. It is about as easy as it can get to use however it does s ll require a method-ology and understanding of geometry to get anywhere near the desired result.

fi g. 1‘Lightwall’ from the ‘House in Turin’, by ecoLogicStudio Architects

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An example of one of my workshop projects using this so ware last year was to model the ‘Lightwall’ from the ‘House in Turin’, by ecoLogicStudio Architects (fi g 1). In Grasshopper I scripted a single component le contain-ing a square that rotated around the ‘z’ axis. This indi-vidual le was then led onto a membrane surface and each le reacted to an a ractor point that mimicked the sun by varying degrees of rota on. An instance (i.e. one of an exponen ally large number of possible outcomes) of the results of the script was “baked” into a 3D model in Rhino and this model was then printed on the 3D Printer. This isolated project eff ort demonstrated to me that computa onal programming is indeed now available to anyone that may wish to inves gate it. It has already been consumed into a ‘user-friendly’ tool that simplifi es the underlying complexi es for the user without los-ing the value of the complexity that underlies it. It also demonstrated quite clearly to me that real structures can be built with these types of tools. They are not just for design as a form of what might be possible, but they are able to produce structures that will stand according to the laws of engineering and physics.

fi g. 2My fi nal 3D printed model

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What has already been produced by New Tech-nology?

When I was doing my Degree I discovered a ‘new’ view of Frank Gehry’s Guggenheim Museum(fi g 3) (Forster & Dal Co, 2003). It breaks from the long-standing 20th Cen-tury architectural tradi on that form should follow func- on. Gehry’s work begins with form, and the func on

adapts to it—but does so in ingenious ways, such that the func on is not only uncompromised by the form, but is augmented by it.

Technologically speaking, Gehry’s ability to create such a spontaneous, organic design is due to a rela vely new computer advancement, CATIA (Computer Aided Three Dimensional Interac ve Applica on). Simply put, this so ware, developed in the 1980s, allows architects to manipulate three-dimensional solid models, permi ng the freedom to create curved forms where architects of the past dealt primarily in angles.

“Gehry made sure that the “organiza on of the ar st” remained paramount throughout the process. That is to say that the design and construc on was less about engineering than about an ar s c vision. Architects have long debated whether their role was more that of an ar st or that of an engineer. Ideally there would be ele-ments of both - the building should look great, but also should not fall down. While a standard apartment build-ing can be designed by an engineer so that it func ons and has no structural fl aws, there is li le or no ar stry to it. Likewise a painter could design a wild building, but would lack the engineering know-how and mathemat-ics to make it work. Gehry could aff ord to let his inner ar st loose because the CATIA so ware overcame the restric ons that had held architects of past genera ons in check.

Now that I have returned to study my Diploma I fi nd that technology has taken this concept further. I had as-

sumed ins nc vely that what was happening is a simple further ‘freeing up’ of the inner ar st of the architect to ‘design’ since the rest is taken care of. However in researching for this essay, I now fi nd myself ques on-ing whether it is in fact a further blurring of the lines between the architect, the scrip ng tool or the scripter themselves as to whom, or what, is the actual Author of the output.

fi g. 3Guggenheim Museum, Bilbao

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Looking at another example of what has been success-fully realized should help to develop this train of thought. The ‘Island City Central Park Gringrin’ in Fukuoka, Japan by the architect Toyo Ito and his structural engineer Mutsuro Sasaki shows how clear parameters set by the architect, the context of the landscape in which the structures were to be built, and the exper se of the structural engineer all combined to produce the 3 undula ng greenhouses on this piece of reclaimed island. The process through which the structures were realized consisted of working towards a single inten on as directed by the architect: to “lightly wrap a huge space with an amorphous thin concrete shell, as though with a single piece of fabric”. (Burry & Burry, 2010) This inten- on was already then placing a future structure within

the context of the landscape (undula ng) and the me in which it was being built (pushing the boundaries of what had previously been considered ‘buildable’).

The fi nal piece “comprises three con nuous free-curved reinforced concrete shells with an overall length of 190m, a maximum width of 50m, and a thickness of 40cm.” (Sakamoto & Ferre, 2008) This type of structure had not previously been conceived of in this way or built in this manner. The process further involved con nuous and numerous itera ons of the geometric and struc-tural performance through the use of the so ware from which the architect chose the fi nal output/outcome. It may seem then that it is a collabora ve exercise with no single ‘author’, however it is clear to me in this par cular instance that it is the architect who has clearly defi ned the founding parameters of the build and it is the archi-tect who has done this in the context of the site itself.

Furthermore it is the architect that has chosen the fi nal structure from all the possible op ons that were gener-ated by the so ware. Whilst the output could not neces-sarily have been achieved without scrip ng or the struc-tural engineer, neither of these would have had anything to work with without the architect’s authorship of the inten on within its context. The original ques on that I

am a emp ng to answer cannot, however, be answered through any one example.

fi g. 4 - Opposite pageIsland City Central Park Gringrin’ in Fukuoka, Japan

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Technology - just a digital pen or something more?The following is an a empt to provide an introduc on to the current cultures of digital design tools and computa- on within architectural design.

Tools

A tool is primarily defi ned as something used in the per-formance of an opera on, or to assist in this opera on or ac on. The capabili es and limita ons of a pen or brush are presumed to be well known in advance of its use; the tools are never perceived to be alive in their own right or have any ac ve control over the outcome that is produced. Their par cipa on is passive. The control, skill and ar stry is le fi rmly in the hands of the designer and what they intend to produce. For instance, a calligrapher has learnt over me the characteris cs of the nibs of each of his pens. When he makes a stroke it is with pur-pose and a strong foreknowledge of the outcome. Unless something like the pen nib breaks in mid-stroke the outcome is guaranteed. This foreknowledge and control around an expected/ guaranteed outcome is the result of prac ce. This throws up an interes ng concept: that the more you use something and perfect your use of it, the less random it becomes when thinking about tradi- onal tools. Could the computa onal programs therefore

be the ul mate tools in that no ma er how much the human prac ces with them, by their very nature they ensure ‘randomness’? They can handle the millions and billions of possibili es in a way that cannot be “prac sed out” by the human mind and body?

Architectural prac oners have digitalized their conven- onal modes of output, in an eff ort to maximize effi -

ciency. We have become consumers of more and more advanced ‘tools’. The advancements that are digital in nature have led to a profi ciency in the use of such tools,

but not necessarily an understanding of the computer that contains these tools, or rather the computa on that is inherent in the opera on of these tools held within the computer. This condi on seems to suggest the design-ers have an ignorance of the computa on that underlies the tools they use. This ignorance has been referred to in many ways, most o en as a “black box” (Cruse, 2009) mentality. The term refers to something that is agnos c about the method; it is merely concerned with the input and output itself and is also one of the key concepts in Cyberne cs.

Concurrently the origins of such tools may also act to infl uence digital design further, fragmen ng and obscur-ing the scope within which designers work. To expand on this point, dra ing applica ons such as AutoCAD have been designed for the purpose of producing detailed technical drawings. The computa onal opera ons within the ‘tool’ of AutoCAD employ preconceived solu ons, based on ‘problem-solving’ and engineering pragma- sm. This type of computa on does not suggest that

the computer is anything other than a signifi cantly more complicated tool than its predecessors: the pen or the paintbrush. The architect seems as in control of what is produced as ever.

So the tools are more complicated but are nevertheless s ll just tools up to this point. What I wish to inves gate is; can they be said to just support our design process or do they actually supplant it? It would seem that com-puta onal geometries have developed so far that they can now be said to have provided the conceptual under-standing of form AND func on. As a result, these newer, emerging techniques are challenging the culture of the computer within design. The direc on of digital design is experiencing a paradigma c shi . The design methodolo-gies and techniques now being developed transcend the ‘blob architecture’ of the 1990s (TERZIDIS, 2006). These new architectural designers are computa onally liter-ate or rather a shi has taken place “from ‘architecture programming ‘ to ‘programming architecture’” (TERZIDIS,

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2006); perhaps mo vated in part by Moore’s law (1965), which states that computer power doubles every two years. Some designers are beginning to generate their own applica ons and opera ons, making the transi on from tool-user to tool-maker. Designers are increas-ingly communica ng directly with the computer. John Maeda has famously said: “To use a tool on a computer, you need do li le more than point and click; to create a tool, you must understand the arcane art of computer programming.” John Maeda, cited in (Reas & Fry, 2007). The purity of Maeda’ s approach lets aspiring designers step right outside the increasingly bloated commercial so ware standards. Such behaviour has led to the ‘hack-ing’ of applica ons and use of open system pla orms, allowing architects to construct their own digital tools, in support of the design process. They are exploring new ways to iterate and generate new forms to overcome the perceived defi ciency in the applica ons. This off ers an exci ng future for those that are programming-astute but what of the ‘masses’? To provide the possibili es to the many rather than just the few there needs to be an automa on and simplifi ca on of the programming.

This emergent digital architecture can be most clearly seen in the language of ‘scrip ng’.

Scrip ng

Scrip ng as a defi ni on is a very broad term and it can encapsulate computer programming at many points between both ends of a very wide spectrum; for novices it is the capability off ered by all modern design so ware to adapt and reconfi gure the so ware to their desired workfl ow by simply automa ng rou ne ac ons and mun-dane repe ons so that a more complex design inves -ga on can be undertaken in the same (or less) amount of me. For the more advanced user it is the ability to integrate massive sets of live data, genera ve algorithms, libraries of prescribed func ons and materials which leads to an emergent architecture. It is this area that

excites me. This paradigm shi is currently seen in the scrip ng so ware within architecture. ‘Scrip ng’ for me now conjures up images of a super intelligent computer algorithm that will solve your en re design needs with a few clicks of the mouse bu on. Thus the term Script-ing has taken its place in design vocabulary because of its broadness encompassing such a large fi eld. It is now accessible to more people precisely because of the fact it represents diff erent things to diff erent sec ons of the ‘masses’. This is similar to the use of the term ‘Programming’ (in terms of computers) which conjures up images of coders and endless lines of syntax machine code but which even a layman expects to be produced almost on-demand in some industries. The crea on of the design programmes (such as CAD, 3D modelling and Image processing) and user-friendly scrip ng programs (such as Grasshopper, paraCloud and Python) now allows designers to delve into the complex world of computer programming through the means of a so -user interface, thus freeing up the design thought process. Instead of being buried under code or having to become advanced themselves in computer programming, the architect is felt to be free to engross themselves more fully in the design element.

There are two fundamental posi ons one can take on the new synergis c use of scrip ng by designers; one is the more intui ve idea that scrip ng is simply just a new tool in the designer’s toolbox. The other is that the “code” is ac ng as a kind of mirror of the human mind, both in terms of the mind that is using the scrip ng code and in terms of the mind that created the scrip ng code itself. From this second posi on comes the view that what is created by the script is so developed in nature that it becomes a co-author of the design itself. This second idea is o en proposed and many believe it to be true or verging on a truth so convincing as to portray the script-ing as being ‘alive’. Terzidis challenges this second posi- on in his Algorithmic Architecture book by sta ng that

“we shouldn’t consider the computer as an extension

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of the mind, but rather as a partner in the design pro-cess with fundamentally diff erent ap tudes and ways to reason. The computer is the Other of the human mind, not its mirror”. (TERZIDIS, 2006) In making this challenge Terzidis is taking the posi on even further to state the proposi on that it is the realisa on of what we cannot yet know of our human minds. That it is revealing to us what we cannot yet know but that already might exist if we were able to know more of the unconscious. More of this stream of thought later, but fi rst to con nue with the debate around the ‘tool’ concept.

The capabili es and limita ons of a computer are not that easy to es mate nor understood by most design-ers, in fact it is stated in ar cle a er ar cle (please refer to the Bibliography at the end of this essay for some sources of this) that most people are frequently amazed by the processes performed by computers. Indeed some of these processes do show some intellectual character-is cs by revealing unpredictable events and outcomes to the designer. Scripts created by a designer and run on computers usually off er alterna ve sugges ons and/or solu ons to a problem that the designer may never have thought of. As has been stated “In such a synerge c re-la onship the unpredictable, impossible, or unknown are not factors of fear but rather invita ons for explora ons”. (TERZIDIS, 2006)

I feel the computer is comparable to our unconscious. (Subconscious and unconscious are o en confused– for this essay I will use the proper term of unconscious and it should be taken to mean that part of the brain that we don’t yet have full access to). It is from this unconscious that for me ideas magically bubble to the surface. One could argue that the designer’s unconscious is making millions of connec ons between all the informa on and experiences that the designer has stored in his memory and to a design problem; and off ers these connec ons up to his conscious brain for evalua on. That is to say

that the “parameters” of the scrip ng are the par cular memories experiences and processes par cular to that person, and that the scripted outcome is defi ned by these parameters. In a similar vein scripted design ideas are just another avenue for explora on by the designer. What does this mean for an architect to be the author and what is he authoring? Perhaps we should look back a li le at the history of genera ve art for further under-standing.

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Design and Genera ve Art - What does History show us?We need to re-focus our a en on on the crea ve ele-ment of the design now that we have inves gated some of the topics around the ‘tool’ component of its makeup. The history of genera ve design is believed to be as old as art itself. There are many examples of historical per-sona who have used genera ve processes that allowed them to relinquish control of their end product, but also allowed them to produce their art.

Art

The mid-twen eth century ar st Jackson Pollock liked to use the technique of Drip Pain ng (fi g 5), a form of ab-stract art in which paint is dripped or poured onto the canvas fi g . Pollock devised paints of diff erent fl uidly and viscosity, and would make use of such unconven onal tools as s cks, hardened brushes and even bas ng sy-ringes to create large and energe c abstract works. Pol-lock could never “sketch” or precisely predict what the fi nal piece would ever be, only set out parameters of the canvas, paints used, tools used and the type of his own movement. (Wikipedia - Jackson Pollock)

He only ever created a script or ‘manuscript’ of his pro-posal. Pollock is shi ing from the tradi onal autographic pain ng method (where the pain ng is directly created by the ar st) to an allographic method (for example music wri en by a composer is created via the perform-ing ar st). What other forms of Art are there that might help me to elaborate on this concept then?

fi g. 5 - Opposite pageJackson Pollock

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Fashion

Fashion is seen as a ‘physical’ form of art. There is the everyday art that is worn that serves a func on and there is the more conceptual art that is more focussed on the form. This everyday art can be described as inno-va ve but in fact is o en just a re-inven on of a previous ‘period’. For example the 1960s, ‘70s and ‘80s fashion trends have all be re-revealed in the last few years. Com-pare this to the art form that is produced by the likes of the late Alexander McQueen such as the dress made of black duck feathers that was part of his ‘The Horn of Plenty’, 2009–10 autumn/winter collec on (Alexander McQueen - Savage Beauty). (fi g. 6)

In Terzidis’s Epi(mul )logue (TERZIDIS, 2006) where the debate is focussed on fashion and design, James Steel suggests that “Fashion does not result from design’s reliance on a star ng point, because that would mean that fashion has a star ng point”. I take this to be refer-ring to the freedom that fashion apparently might have from the single restric on that design has: it needs to start somewhere. I can see the validity of some of the debate but fi nd it hard to ignore that fashion does have a star ng point – that it must be worn by the person, and it is therefore not as free from all constraints as perhaps thought. In this same way, even the most radical of ar-chitecture has to retain as one of its fundamental param-eters the need to house the form of human life or serve any other such purpose. A bridge can be pushing the limits of known engineering but it must s ll be a bridge.

fi g. 6Alexander McQueen dress made of black duck feathers that was part of his ‘The Horn of Plenty’ collec on

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Music

In the world of music, the German composer Wolfgang Amadeus Mozart developed and employed a composing technique that has all the elements of a genera ve tool. (fi g. 7) shows a piece of music by Mozart “The piece car-ries the explanatory sub tle Composing waltzes with two dice without knowing music or understanding anything about composing. For this, Mozart composed 176 bars of music, from which sixteen were chosen from a list using dice, which then produced a new piece when performed on a piano. Sixteen bars, each with eleven possibili es, can result in 1,116 unique pieces of music.” (Ihmels & Riedel, 2004)

Musicologists have found a work sheet for Adagio KV 516 that shows development of the piece from principles derived from this musical game of dice. This methodol-ogy in musical composi on in which some element is le to chance became known as ‘Aleatoric’ music.

It seems then that Mozart was a emp ng to randomly generate his music before computers existed to do this for him. He was adding an element of chance to the fi nal composi on of his music, whilst retaining authorship of the piece as a whole. Taking this a step further, once created, the musical score is subject to interpreta on by the performer and/ or the conductor. Could Archi-tectural Scrip ng be compared to wri ng a music score from which a song might be performed then? In that it is an interpreta on of the original authored piece? Or is it actually authoring the architectural equivalent of the musical score?

This ‘ pping’ point between who is considered the au-thor was discussed by Walter Benjamin many years later in the 1970’s but in rela on to the wri en word rather than music. Let’s explore Benjamin’s posi on now then.

fi g. 7Composing waltzes with two dice without knowing music or under-standing anything about composing. Mozart.

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Devolu on of the AuthorIn Benjamin’s essay “The Author as Producer” (Benjamin, 1970) he discussed the wri ng of journalists and their rela onship with the reader through the medium of the newspaper: “So the indiscriminate assimila on of facts goes hand in hand with the similar indiscriminate assimi-la on of readers, who see themselves instantly raised to the level of co-workers”. I take this to mean that by the simple act of reading words already wri en, the reader has become a co-author of the piece. What then of the architect and his building?

Authorship

The established idea that a meaningful authorial rela on can be sought between an architect and the architecture of a building, by way of iden fying with the persona of the architect, can be traced back to Leon Ba sta Alber- ’s De re aedifi catoria - On the Art of Building, 1443-52

AD (Anstey, Grillner, & Hughes, 2007)

Alber only a ributes to the architect authorial control over representa on of the building, detaching him from the physical construc on. “To make something that appears to be convenient for use, and that can without doubt be aff orded and built as projected, is the job not of the architect but of the workman. But to preconceive and to determine in the mind and with judgement some-thing that will be perfect and complete in its every part is the achievement of such a mind as we seek.” (Rykwert, Tavernor, & Leach)

Others have considered this topic too. The French phi-losopher and historian Michel Foucault in his 1977 essay, ‘What is an Author?’ drew a en on to the fact that the no on of the ‘author’ is socially constructed. Foucault claimed that the literary author was invented during the eighteenth century and isolated “ownership of the text” as one of the characteris cs of the rela onship between

the text and the author. (Donald, Simon, & trans., 1977) Foucault urged us to imagine a culture where discourse would circulate: without any need for an author, a world where it did not ma er who was speaking. Is this pre-sen ng a case that it does not ma er which is the author of the design, the human or the script? Perhaps the crucial outcome is what should be the valued item i.e. the produc on of the design itself. Does it ma er “who” created it? Why is there the need for ownership of this tle “author” at all?

“Roland Barthes in “the death of the author” in 1968 challenged this no on of authorship altogether. Barthes suggests the emergence of a new authorial persona. He disconnects the crea on from the Author and assigns to it autonomous voice in the realm of a mul - dimensional space where it is in the consciousness of its interpret-ers that meaning is to be a ributed. Once the crea on comes to light the author, according to Barthes, “enters into his own death”. (Barthes, 1977)

This theory could be connected to collec ve authorship where there is not one author but many and that “once published, the text is no longer under the control of the author” making the author have limited control on the future of the text. This could be argued for within gen-era ve design where the designer can set parameters to leave his mark on the work and therefore demonstrates that his art lies in the original code, not the outcome.

Man vs. Machine

Another complexity in this discussion of humans and the computa onal so ware of machines involves the simi-larity or lack of le and right side of the brain – one is logical and computa onal. The other is ar s c, linguis c, emo onal and crea ve – random we could say. So per-haps the computer is the ul mate representa on of our logic side of the brain. The randomness that it maintains is actually a computerised randomness. Perhaps this is

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what those that object to the computer being seen as a “co—author” are really objec ng to but are not able to ar culate: that a logical computer that mirrors the le side of the brain can never replicate the right side of the brain and its ar stry.

It has been the view that the genera on of a novel design is the result of human intui on. Christopher Alexander has famously stated “A digital computer is, essen ally, the same as a huge army of clerks... there is nothing a computer can do which such an army of clerks could not do, if given me.” (Alexander, 1964) Alexander viewed the computer in architecture simply as a tool de-void of human thought and intui on, he further argued: “Anybody who asks ‘How can we apply the computer to architecture?’ is dangerous, naive, and foolish. The computer as a tool is subordinate to human intelligence.” (Alexander, 1964). To put this in context; Alexander was speaking at the me when computers were fi rst emerg-ing in the 1960s and the discourse on the use of comput-ers in architecture and urbanism was beginning.

There are many aspects of the Philosophy of Mind that would both agree and disagree with this viewpoint. In par cular is the area of Computa onal Philosophy of Mind as proff ered by Hilary Putnam in his life’s work. To cover the detail of this area of Philosophy is not possible within the limita ons of this essay. I will over-simplify somewhat then as a refuta on of Alexander’s stance, through using a quote from Professor Randall O’Reilly from the University of Colorado (who wrote regularly in rela on to Putnam’s philosophy) and stated that: “

“My [research] work comes out of a tradi on that says people’s brains are nothing like computers, and now all of a sudden as we look at them, in fact, in a certain respect they are like computers.” (Human Brain Region Func ons Like Digital Computer - ScienceDaily, 2006)

Digital computers operate by turning electrical signals into binary “on and off states” and fl exibly manipula ng

these states by using switches. O’Reilly found the same opera ng principles in the brain.” (Human Brain Region Func ons Like Digital Computer - ScienceDaily, 2006)

The genera ve process at a cogni ve level can be the re-sult of both processes of intelligence of the human mind and of ar fi cial intelligence emergent within computa- onal systems. While the human mind may exhibit an

inherent ability to aggregate relevant informa on, in the design process such capaci es do not achieve competen-cies within the environment of an increasingly complexi-fi ed problem space. Nor has ar fi cial intelligence been able to demonstrate a rate of formal thinking, or learn-ing, which can be said to equal the performance of the human mind. Therefore, it is argued that: the inherent capaci es of computa onal systems to ‘follow exactly millions of precisely defi ned opera ons’ (Alexander, 1964), may allow designers to extend beyond their own intrinsic ability to deal with complexity. The computer and the designer form a synerge c partnership (TERZI-DIS, 2006). These views in themselves help to provide the context in that they are wri en decades apart and show how thinking has changed and evolved over a rela- vely short period of me in the history of mankind.

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Is there an answer?To conclude, it seems that to answer the original ques on I need to avoid the mistake of believing in a false dilemma where things appear to have to be ‘either – or’. Restric ng the answer to choose which of the three (the computer the so ware designer or the so ware user) is the author is to restrict the outcome to something it need not be restricted to. I have wri en of the fl ux through history, of the complexi es around what can be cons tuted as ‘new’ depending on the perspec ve of the person at the me and I have wri en of the human mind in terms of it being partly mirrored by a computer. What I believe we are le with is the understanding that all things are in fl ux. That which is considered verging on the author or design in a computa onal advanced scrip ng technology today is likely to very soon be thought of as basic, literal and not at all crea ve.

This domain can be visualised like a 60s lava lamp: things come together, things evolve, change, appear, disappear and then reappear in a diff erent form, context or process. They are the same and yet not the same. As Walter Benjamin puts it “There have not always been novels in the past, they do not al-ways have to exist in the future” (Benjamin, 1970). In just such a way, there have not always been compu-ta onal programs, and in the future there may be no need for them having been replaced by some-thing that we cannot yet conceive of.

Perhaps I should give Walter Benjamin the last word here in rela on to his concept of ‘Epic theatre’: “Thus the epic theatre does not reproduce situ-a ons, rather it uncovers them.” (Benjamin, 1970) For the world of architecture, I take this to mean that simply because we have not yet conceived of something is not to say that it does not already exist somewhere, in some unconscious mind. Perhaps it does already exist but we simply do not or cannot recognise it for what it is and it is only through the passage of me and evolu on that we can see it be-ing revealed. . Scrip ng then could be seen to assist in revealing things rather than simply reproducing output that could be calculated by the human mind if we understand our own minds suffi ciently.

The design author is at once then human as pro-grammer, human as the user of a tool, computer, computa onal so ware, any one of these, any com-bina on of these and yet none of these. Tomorrow will show us a li le more of that which we do not know today, but tomorrow is not yet here. I look forward to seeing what will be revealed to us over the coming weeks, months and years.

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BibliographyAlexander McQueen - Savage Beauty. (n.d.). Retrieved February 28, 2012, from h p://blog.metmuseum.org/alexan-

dermcqueen/dress-horn-of-plenty/

Alexander, C. (1964). A Much Asked Ques on about Computers and Design. Architecture and the Computer, Proceed-ings of First Boston Architectural Center Conference., (pp. 52-55). Boston, Massachuse s.

Anstey, T., Grillner, K., & Hughes, R. (2007). Architecture and Authorship. London: Black Dog Publishing.

Barthes, R. (1977). “The Death of an Author” in Image-Music-Text. London: Fontana Press.

Benjamin, W. (1970). The Author as Producer - New Le Review. Retrieved February 28, 2012, from h p://round-table.kein.org/fi les/roundtable/Walter%20Benjamin_%20The%20Author%20as%20Producer.pdf

Burry, J., & Burry, M. (2010). The New Mathema cs of Architecture. London: Thames & Hudson.

Coates, P. (2010). Programming.Architecture. Abingdon, Oxford: Routledge.

Cruse, H. (2009, July). Neural Networks as Cyberne c Systems (3rd and revised edi on). Retrieved February 28, 2012, from h p://www.brains-minds-media.org/archive/1841/bmm1841_v2.1_2010-Mar-09.pdf

Donald, B. F., Simon, S., & trans. (1977). What is an Author? - Foucault, Michel. New York: Cornell University Press.

Elezkurtaj, T., & Franck, G. (n.d.). Algorithmic Support of Crea ve Architectural Design. Retrieved February 28, 2012, from h p://www.iemar.tuwien.ac.at/publica ons/Umbau1.pdf

Forster, K. A., & Dal Co, F. (2003). Frank O.Gehry: The Complete Works. Electa Architecture.

Grasshopper - Genera ve Modeling for Rhino. (n.d.). Retrieved February 28, 2012, from h p://www.grasshopper3d.com/

Human Brain Region Func ons Like Digital Computer - ScienceDaily. (2006, October 5). Retrieved February 28, 2012, from h p://www.sciencedaily.com/releases/2006/10/061005222628.htm

Ihmels, T., & Riedel, J. (2004). The Methodology of Genera ve Art. Retrieved February 28, 2012, from h p://www.medienkunstnetz.de/themes/genera ve-tools/genera ve-art/1/

Reas, C., & Fry, B. (2007). Processing: A Programming Handbook for Visual Designers and Ar sts. Cambridge, Massa-chuse s: The MIT Press.

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Rykwert, J., Tavernor, R., & Leach, N. (n.d.).

Rykwert, J., Tavernor, R., Leach, N., & trans. (1988). Alber , Leon Ba sta, On the Art of Building in Ten Books. Cam-bridge MA and London: MIT Press.

Sakamoto, T., & Ferre, A. (2008). From Control to Design: Parametric/Algorithmic Architecture. Volume 5 of Verb monograph. Barcelona: Actar-D.

TERZIDIS, K. (2006). Algorithmic Architecture. Oxford: Architectural Press.

Webopedia - Moores Law. (n.d.). Retrieved February 28, 2012, from h p://www.webopedia.com/TERM/M/Moores_Law.html

Wikipedia - Aleatoric Music. (n.d.). Retrieved February 28, 2012, from Wikipedia: h p://en.wikipedia.org/wiki/Alea-toric_music

Wikipedia - Jackson Pollock. (n.d.). Retrieved February 28, 2012, from h p://en.wikipedia.org/wiki/Jackson_Pollock

Further ReadingBurry, M. (2011). Scrip ng Cultures: Architectural Design and Programming (Architectural Design Primer). John Wiley

& Sons.

Carpo, M. (2011). The Alphabet and the Algorithm. MIT Press.

Hensel, M., Hight, C., & Menges, A. (2009). AD Space Reader Heterogeneous Space in Architecture. Chichester: Wiley.

Hensel, M., Menges, A., & Weinstock, M. (2010). Emergent technologies and design. Routledge.

Kolarevic, B. (2005). Architecture in the Digital Age: Design and Manufacturing. Taylor & Francis.

Reas, C., & McWilliams, C. (2010). Form+Code in Design, Art, and Architecture. Princeton: Princeton Architectural Press.

Tedeschi, A. (2011). Parametric architecture with Grasshopper. Le Penseur.

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Image Creditsfront cover Niroshan Gunasingam

fi g 1 ecoLogicStudio Architects website (accessed 28-2-2012)

fi g 2 Niroshan Gunasingam

fi g 3 h p://jubiladolog.blogspot.com/2010_05_01_archive.html (accessed 28-2-2012)

fi g 4 (Burry & Burry, 2010)

fi g 5 h p://www.goldbergmcduffi e.com/projects/artnews/pollock.jpg (accessed 28-2-2012)

fi g 6 h p://blog.metmuseum.org/alexandermcqueen/dress-horn-of-plenty/ (accessed 28-2-2012)

fi g 7 h p://www.medienkunstnetz.de/works/wuerfelspiel/ (accessed 28-2-2012)

GlossaryAleatoric music (also aleatory music or chance music; from the La n word alea, meaning “dice”) is music in which some element of the composi on is le to chance, and/or some primary element of a composed work’s realiza on is le to the determina on of its performer(s). (Wikipedia - Aleatoric Music)

Algorithm “The name comes from Arabic, as does algebra, the AI prefi x being the equivalent to ‘the’. It is normally given as ‘a set of instruc ons that guarantees a solu on or answer to some problem’,” (Coates, 2010)

Gene c Algorithms The study of gene c algorithms originated with John Holland in the mid-seven es. A gene c algorithm is an itera ve procedure that consists of a popula on of individuals, each one represented by string of symbols, encoding a possible solu on to a given problem. Off spring is generated by way of crossover and muta- on. Individuals are selected for recombina on with a probability propor onal to their rela ve fi tness. (Elezkurtaj &

Franck)

Moore’s Law The observa on made in 1965 by Gordon Moore, co-founder of Intel, that the number of transistors per square inch on integrated circuits had doubled every year since the integrated circuit was invented. Moore predicted that this trend would con nue for the foreseeable future. In subsequent years, the pace slowed down a bit, but data density has doubled approximately every 18 months, and this is the current defi ni on of Moore’s Law, which Moore himself has blessed. Most experts, including Moore himself, expect Moore’s Law to hold for at least another two decades. (Webopedia - Moores Law)