How many ways are there to generate a design proposal for a building? Some universities cut to the chase, and tell their students to walk down a certain street or around a part of town and “find an architectural project”. For what it’s worth, this is Identification, Analysis and Synthesis all in one. The rest of the semester is then spent developing, modelling, illustrating and communicating that project. After my last week’s post on the Synthesis part of this thing we call The Design Process, I’m beginning to see the sense in that.

Research

I’d been noticing for years that many final year students would spend a semester on research prior to spending another semester developing their final project. Everyone calls it research but it’s really just data gathering and program setting. Usual deliverables are a report identifying the problem, case studies or “precedents” as some like to call them, relevant data, a proposed program, perhaps a bubble diagram showing relationships, and perhaps a massing model to provide a base for further development. If alternative sites aren’t compared and analyzed and one eventually decided upon, some real site is usually chosen as a demonstration site. All this information is collected and presented at the end of semester and the problem, if not the solution is expected to be in there somewhere.

Some students will have already decided what they wanted to do will have contrived their case studies, data collection and research to validate it. They’re not that much different from those students who were told to walk down the street and find a project. In some ways, they’re the lucky ones because that approach better approximates the real world and not just the research-driven practices and their readymade approach, if not a readymade solution, waiting for the right site and client. It’s not that architects don’t occasionally advise on site selection but they generally don’t get to choose where and what to build. Some architects may be enthusiastic about certain building types and eventually gain a reputation for it, but they probably won’t have control over what the project, the program, or budget. There are also students who diligently research without already knowing what they want to do with it. If one believes that projects derive from research (and if we believe that research leads to a better understanding of the problem) then better design ideas should result from it. At the same time, we have students who have done the appropriate studies and then proceed to waste the first half of the second semester coming up with a “concept” that can be developed into a project. I conclude that research doesn’t “inform” design as much or as often as we think it does.

Program

It was once believed functional requirements could shape a project. It was thought that a room didn’t need to be any larger than the sum of what it was to contain, and that rooms could be connected in representations known as bubble diagrams and arranged into plans to be later tidied up into masses. This all still happens except that, prior to the application of facades, it’s now called development gain massing.

Site considerations

Site considerations are a moveable feast. One selects what one thinks is worth considering be it a view out or a view in, the direction of the wind, the neighbours, what’s already there … And of course, there’s always this which I never miss an opportunity to quote.

Genius Loci

This idea that a site has some inherent spirit that needs to be gratified with a building crops up every now and then. [See above.] It can be understood as the equivalent of the architect saying “what I think should go there.” Sometimes it’s convincing. Sometimes it’s not.

As a basis for generating buildings, it’d be more convincing if genius loci is something that all sites have, although some may be easier to identify and work with than others.

Data

Data is what we used to call information and information is what we used to call knowledge. Generating a design proposal from data still involves the same three filters of Identification, Analysis and Synthesis working (or not working) in exactly the same way they have in the past. The only difference is that people are responsible for their knowledge but data is often presented and accepted as given truth. It can come from anywhere. The main function of linking the words data and design seems to be to get us to distrust our instincts and believe that data is objective and irrefutable.

Two summers ago I went to a conference where the notion of Society 5.0 was floated. Apparently, Primitive society was Society 1.0, Agricultural society was Society 2.0, Industrial society was Society 3.0, Digital society was Society 4.0 and an Ultra-smart society with a cyber-physical integrated space was said to be Society 5.0.

Some scholars believe the invention of agriculture was the beginning of social inequality. They have a case because, for the first time in the history of mankind, people could stay in one place and produce not only sufficient for their own needs, but a surplus that could be taxed. This surplus could either be used as currency to pay for works for the good of society, or retained as a surplus for the sake of having more than others. This next is a summary of their argument.

Hunter/gatherers tend to be egalitarian, with each family or clan in control of themselves, cultivating personal relationships with a variety of spirits/gods to keep everything healthy. Farming led to monocultures with fewer and more powerful gods, a priestly class to bring rain and protect the crops, and eventually god-kings with the divine right to rule, and control irrigation, passed down from above. This is the pattern of the Pharaohs of Egypt and the Great Sun of the Natchez, the leaders of the Inca, Maya and Aztec, and the Louis’ of France. Thus, if agriculture was encouraged, it was as a means of control and not liberation.

In this sense, we’re either in The Fourth Industrial Revolution, or Industrial Revolution 4.0, or Exploitation 1.4. Whatever it’s called, our immediate future looks like it’s going to have 1) automated driving whether we like it or not 2) manufacturing and robotics, 3) infrastructure management 4) biotechnologies and materials, 4) 3D printed anything whether it’s any good or not, and 5) “smart life” a.k.a. data mining. At the conference, the speaker stressed that “The key to international competitiveness is the development of systems by major companies with real data and AI start-up companies.”  I wasn’t the only person in the audience to gasp but the mood onstage was that data is where it’s at, and is going to be.

Data may not be treated as “goods” in international treaties but as long as it can be bought and sold, or stolen or mined and exploited, it’s definitely a thing of value. But what is that value and is anyone even bothering to find out? If all this data is so valuable, then it’d be nice to be compensated for generating it. It’s the principle that underlies work – I sell my labour and someone else sells the product of that labour.

In the past, farm workers needed a place to live if they were going to work and housing was part of the deal. Even the early industrialists saw the sense in providing workers with housing (even though its giving and taking could be used to ensure compliance). Nobody builds worker housing anymore, probably because workers are no longer what powers economies. At this stage of the pandemic, I’m not even hearing much about co-living and co-working spaces. It seems both have quietly died now nobody is as mobile as they used to be nor as keen to mingle socially or professionally beyond their household. We’ve had a version of a digital city forced upon us for almost two years now and we’re not as excited about the idea as we once were told we would be. Google’s smart city for Toronto has been put on hold for a while but will circle back and land again, probably in California if not in Texas.

The assumption is that everything that makes up a city is 1) capable of being understood, 2) can be converted into known software and hardware and 3) that said software and hardware will be all we need to satisfy all our wants and needs. If any of these assumptions is wrong, then what we get won’t necessarily be what we need. Data is assumed to be neutral but if it can be used to identify a problem, analyze it, and generate a solution then it’s the same old process but now stripped of any notions of authorship or idea. At least when we were in thrall to Art we still had the agency to question whether it was good art or not. And even with The Idea, we still had the right to question if that idea were a good one, or even if it were, an appropriate one. An architecture that refuses to be evaluated on anything but its own terms is never going to be for the public good.

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What’s Already There

Architcture Misfits #26: Asnago Vender

Architecture Myths #17: Genius Loci