the architecture of ai
archinect speaks to designers pushing forward the integration of self-learning systems into architecture to understand how the rise of artificial intelligence is shaping the profession.
“let us consider an augmented architect at work. He sits at a working station that has a visual display screen some three feet on a side, this is his working surface, and controlled by a computer with which he can communicate by means of a small keyboards and various other devices.” douglas engelbart
this vision of the future architect was imagined by engineer and inventor Douglas Engelbart during his research into emerging computer systems at Stanford in 1962. At the dawn of personal computing he imagined the creative mind overlapping symbiotically with the intelligent machine to co-create designs. This dual mode of production, he envisaged, would hold the potential to generate new realities which could not be realised by either entity operating alone. Today, self-learning systems, otherwise known as artificial intelligence or ‘AI’, are changing the way architecture is practiced, as they do our daily lives, whether or not we realise it.
If you are reading this on a laptop or tablet, then you are directly engaging with a number of integrated AI systems, now so embedded in our the way we use technology, they often go unnoticed.
As an industry, AI is growing at an exponential rate, now understood to be on track to be worth $70bn globally by 2020. This is in part due to constant innovation in the speed of microprocessors, which in turn increases the volume of data that can be gathered and stored. But don’t panic — the artificial architect with enhanced Revit proficiency is not coming to steal your job. The human vs. robot debate, while compelling, is not so much the focus here but instead how AI is augmenting design and how architects are responding to and working with these technological developments. What kind of innovation is artificial intelligence generating in the construction industry?
Assuming you read this as a non-expert, it is likely that much of the AI you have encountered to this point has been ‘weak AI’, otherwise known as ANI (Artificial Narrow Intelligence). ANI follows pre-programmed rules so that it appears intelligent but is in effect a simulation of a human-like thought process. With recent innovations such as that of Nvidia’s microchip in April 2016, a shift is now being seen towards what we might understand as ‘deep learning’, where a system can, in effect, train and adapt itself.
The interest for designers is that AI is therefore starting to apply itself to more creative tasks, such as writing books, making art, web design, or self-generating design solutions, due to its increased proficiency in recognising speech and images. Significant ‘AI winters’, or periods where funding has been hard to source for the industry, have occurred over the last twenty years, but commentators such as philosopher Nick Bostron now suggest we are on the cusp of an explosion in AI, and this will not only shape but drive the design industry in the next century. AI therefore has the potential to influence the architectural design process at a series of different construction stages, from site research to the realisation and operation of the building.
01. site and social research “By already knowing everything about us, our hobbies, likes, dislikes, activities, friends, our yearly income, etc., AI software can calculate population growth, prioritize projects, categorize streets according to usage and so on, and thus predict a virtual future and automatically draft urban plans that best represent and suit everyone.” Rron Beqiri on Future Architecture Platform.
Gathering information about a project and its constraints is often a first stage of an architectural design process, traditionally involving travelling to a site, perhaps measuring, sketching and taking photographs. In the online and connected world, there is already a swarm-like abundance of data for the architect to tap into, already linked and referenced against other sources allowing the designer to, in effect, simulate the surrounding site without ever having to engage with it physically. This ‘information fabric’ has been referred to as the ‘internet of things’. BIM tools currently on the market already tap into these data constellations, allowing an architect to evaluate site conditions with minute precision. Software such as EcoDesigner Star or open-source plugins for Google SketchUp allow architects to immediately calculate necessary building and environmental analyses without ever having to leave their office. This phenomenon is already enabling many practices to take on large projects abroad that might have been logistically unachievable just a decade ago.
The information gathered by our devices and stored in the Cloud amounts to much more than the material conditions of the world around us. Globally, we are amassing ever expanding records of human behaviour and interactions in real-time. Personal, ‘soft’ data might, in the most optimistic sense, work towards the ‘socially focussed design’ that has been widely publicised in recent years by its ability to integrate the needs of users. This approach, if only in the first stages of the design process, would impact the twentieth century ideals of mass production and standardisation in design. Could the internet of things create a socially adaptable and responsive architecture? One could speculate that, for example, when the population of children in a city crosses a maximum threshold in relation to the number of schools, a notification might be sent to the district council that it is time to commission a new school. AI could therefore, in effect, write the brief for and commission architects by generating new projects where they are most needed.
02. design decision-making Now that we have located live-updating intelligence for our site, it is time to harness AI to develop a design proposal. Rather than a program, this technology is better understood as an interconnected, self-designing system that has the ability to upgrade itself. It is possible to harness a huge amount of computing power and experience by working with these tools, even as an individual — as Autodesk president Pete Baxter told the Guardian: “now a one-man designer, a graduate designer, can get access to the same amount of computing power as these big multinational companies”. The architect must input project parameters, in effect an edited ‘design brief’, and the computer system will then suggest a range of solutions which fulfil this criteria. This innovation has the potential to revolutionise how architecture is not only imagined but how it is fundamentally expressed for designers who choose to adopt these new methods.
I spoke with Michael Bergin, a researcher at Project Dreamcatcher at Autodesk’s Research Lab, to get a better understanding of how AI systems are influencing the development of design software for architects. While their work was initially aimed at the automotive and industrial design industries, Dreamcatcher now is beginning to filter into architecture projects. It was used recently to develop The Living’s generative design for Autodesk’s new office in Toronto and MX3D’s steel bridge in Amsterdam. The basic concept is that CAD models of the surrounding site and other data, such as client databases and environmental information, are fed into the processor. Moments later, the system outputs a series of optimised 3D design solutions ready to render. These processes effectively rely on cloud computing to create a multitude of options based on self-learning algorithmic parameters. Lattice-like and fluid forms are often the aesthetic result, perhaps unsurprisingly, as the software imitates structural rules found in nature.
The Dreamcatcher software has been designed to optimise parametric design and link into and extend existing software designed by Autodesk, such as Revit and Dynamo. Interestingly, Dreamcatcher can make use of a wide and increasing spectrum of design input data — such as formulas, engineering requirements, CAD geometry, and sensor information — and the research team is now experimenting with Dreamcatcher’s ability to recognise sketches and text as input data. Bergin suggests he imagines the future of design tools as “systems that accept any type of input that a designer can produce [to enable] a collaboration with the computer to iteratively target a high-performing design that meets all the varied needs of the design team”. This would mean future architects would be less in the business of drawing and more into specifying requirements of the problem, making them more in sync with their machine counterparts in a project. Bergin suggests architects who adopt AI tools would have the ability to “synthesize a broad set of high level requirements from the design stakeholders, including clients and engineers, and produce design documentation as output”, in line with Engelbart’s vision of AI augmenting the skills of designers.
AI is also being used directly in software such as Space Syntax’s ‘depthmapX’, designed at The Bartlett in London, to analyse the spatial network of a city with an aim to understand and utilize social interactions and in the design process. Another tool, Unity 3D, is built from software developed for game engines to enable designers to analyse their plans, such as the shortest distances to fire exits. This information would then allow the architect to re-arrange or generate spaces in plan, or even to organize entire future buildings. Examples of architects who are adopting these methods includeZaha Hadid with the Beijing Tower project (designed ante-mortem) and MAD Architects in China, among others.
03. client and user engagement As so much of the technology built into AI has been developed from the gaming industry, its ability to produce forms of ‘augmented reality’ have interesting potential to change the perception and engagement with architecture designs for both the architects and non-architects involved in a project. Through the use of additional hardware, augmented reality has the ability to capture and enhance real-word experience. It would enable people to engage with a design prior to construction, for example to select the most appealing proposal from their experiences within its simulation. It is possible that many architecture projects will also remain in this unbuilt zone, in a parallel digital reality, which the majority of future world citizens will simultaneously inhabit.
Augmented reality would therefore allow a client to move through and sense different design proposals before they are built. Lights, sounds, even the smells of a building can be simulated, which could reorder the emphasis architects currently give to specific elements of their design. Such a change in representational method has the potential to shift what is possible within the field of architecture, as CAD drafting did at the beginning of this century. Additionally, the feedback generated by augmented reality can feed directly back into the design, allowing models to directly interact and adapt to future users. Smart design tools such as Materiable by Tangible Media are beginning to experiment with how AI can begin to engage with and learn from human behaviour.
04. Realising designs and rise of the robot craftsmen AI systems are already being integrated into the construction industry — innovative practices such as Computational Architecture are working with ‘robotic craftsmen’ to explore AI in construction technology and fabrication. Michael Hansmeyer and Benjamin Dillenburger, founders of Computational Architecture, are investigating the new aesthetic language these developments are starting to generate. “Architecture stands at an inflection point,” he suggests on their website, “the confluence of advances in both computation and fabrication technologies lets us create an architecture of hitherto unimaginable forms, with an unseen level of detail, producing entirely new spatial sensations.”
3D printing technology developed from AI software has the potential to offer twenty-first century architects a significantly different aesthetic language, perhaps catalysing a resurgence of detail and ornamentation, now rare due to the decline in traditional crafts. Hansmeyer and Dillenburger’s Grotto Prototype for the Super Material exhibition, London, was a complex architectural grotto 3D-printed from sandstone. The form of the sand grains were arranged by a series of algorithms custom designed by the practice. The technique allowed forms to be developed which were significantly different to that of traditional stonemasonry. The aim of the project was to show that it is now possible to print building-scale rooms from sandstone and that 3D printing can also be used for heritage applications, such as repairs to statues.
Robotics are also becoming more common on construction job sites, mostly dealing with human resources and logistics. According to AEM, their applications will soon expand to bricklaying, concrete dispensing, welding and demolition. Another example of their future use could include working with BIM to identify missing elements in the snagging process and update the AI in real-time. Large scale projects, for example government-lead infrastructure initiatives, might be the first to apply this technology, followed by mid-scale projects in the private sector, such as cultural buildings. The challenges of the construction site will bring AI robotics out of the indoor, sanitised environment of the lab into a less scripted reality. Robert Saunders, a researcher into AI and fabrication at the University of Sydney, told New Atlas that “robots are great at repetitive tasks and working with materials that react reliably…what we’re interested in doing is trying to develop robots that are capable of learning how to work with materials that work in non-linear ways… like working with hot wax or expanding foam or, more practically, with low-grade building materials like low-grade timber.” Saunders foresees robot stonemasons and other ‘craftsbots’ working in yet unforeseen ways, such as developing the architect’s ‘skeleton plans’, in effect, spontaneously generating a building on-site from a sketch.
05. integrating ai systems This innovation involves either integrating developing artificial technologies with existing infrastructure or designing architecture around AI systems. There is a lot of excitement in this field, influenced in part by Mark Zuckerberg’s personal project to develop networked AI systems within his home, which he announced in his New year’s Facebook post in 2016. His wish is to develop simple AI systems to run his home and help with his day-to-day work. This technology would have the ability to recognise the voices of members of the household and respond to their requests. Designers are taking on the challenge of designing home-integrated systems, such as the Ori System of responsive furniture, or gadgets such as Eliq for energy monitoring. Other innovations, such as driverless cars that run on an integrated system of self-learning AI, have the potential to shape how our cities are laid out and planned — in the most basic sense, limiting our need for more roads and parking areas.
Behnaz Farahi is a young architect who is employing her research into AI and adaptive surfaces to develop interactive designs, such as in her Aurora and Breathing Wall projects. She creates immersive and engaging indoor environments which adapt to and learn from their occupants. Her approach is one of many — different practices with different goals will adapt AI at different stages of their process, creating a multitude of architectural languages.
Researchers and designers working in the field of AI are attempting to understand the potential of computational intelligence to improve or even upgrade parts of the design process with an aim to create a more functional and user-optimised built environment. It has always been the architect’s task to make decisions based on complex, interwoven and sometimes contradictory sets of information. As AI gradually improves in making useful judgements in real-world situations, it is not hard to imagine these processes overlapping and engaging with each other. While these developments have the potential to raise questions in terms of ownership, agency and, of course, privacy in data gathering and use, the upsurge in self-learning technologies is already altering the power and scope of architects in design and construction. As architect and design theorist Christopher Alexander said back in 1964,“We must face the fact that we are on the brink of times when man may be able to magnify his intellectual and inventive capacity, just as in the nineteenth century he used machines to magnify his physical capacity.”
In our interview, Bergin gave some insights into how he sees this technology impacting designers in the next twenty years. “The architectural language of projects in the future may be more expressive of the design team’s intent”, he stated. “Generative design tools will allow teams to evaluate every possible alternative strategy to preserve design intent, instead of compromising on a sub-optimal solution because of limitations in time and/or resources.” Bergin believes AI and machine learning will be able to support a “dynamic and expanding community of practice for design knowledge”. He can also foresee implications of this in the democratisation of design work, suggesting “the expertise embodied by a professional of 30 years may be more readily utilized by a more junior architect”. Overall, he believes “architectural practice over the next 20 years will likely become far more inclusive with respect to client and occupant needs and orders of magnitude more efficient when considering environmental impact, energy use, material selection and client satisfaction”.
On the other hand, Pete Baxter suggests architects have little to fear from artificial intelligence: “Yes, you can automate. But what does a design look like that’s fully automated and fully rationalised by a computer program? Probably not the most exciting piece of architecture you’ve ever seen.” At the time of writing, many AI algorithms are still relatively uniform and relatively ignorant of context, and it is proving difficult to automate decision-making that would at first glance seem simple for a human. A number of research labs, such theMIT Media Lab, are working to solve this. However, architectural language and diagramming have been part of programming complex systems and software from the start, and they have had significant influence on one another. To think architecturally is to imagine and construct new worlds, integrate systems and organise information, which lends itself to the front line of technical development. As far back as the 1960s, architects were experimenting with computer interfaces to aid their design work, and their thinking has inspired much of the technology we now engage with each day.
for an interesting read on the design jobs of the future, see http://www.fastcodesign.com/3054433/design-moves/the-most-important-design-jobs-of-the-future
this article is from a monthly feature column for the online platform Archinect which explores architectural developments within wider cultural and political discussions. Read the original article here: https://archinect.com/features/article/149995618/the-architecture-of-artificial-intelligence