(This transcription has been edited) 

Presenters: Alessandro Bava (AB), Philippe Morel (PM), Marco Vannucci (MV), Roberto Bottazzi (RB), Provides Ng (PN).  

Venue: Zoom

Date: 08th December, 2021

AB:  

What I’m interested in, in this discussion – and we saw it in all the presentations – is not exclusively work that has been done with a computer per se or using proficiency in coding, but also how this can influence the practice of designing and making spaces. Going back to architecture; making spaces, constructing the human habitat. 

I think there are a number of strands we could pick up on, so I’m going to leave space for the speakers too, [but] I have a few questions and connections that I want to make. 

I think the video was amazing to end with, Philippe [Philippe Morel], because it also gave us a big platform to understand culturally how all these different things are laid out, because we really dwell in different timeframes – or timelines, one should say, it’s more fashionable today! 

I think there are these amazing overlaps and connections that allow us to expand on this, and I really want to stress our support for our guests. For the people listening, there is not so much work being done in the direction of understanding this cultural impact – I mean, Philippe mentioned quite a few moments and exhibitions that are in fact legendary, precisely because there are so few of them. 

So, there have been a few moments where of course the role of technology and computation has been understood in terms of its cultural implications. The other day, I was at another panel, another symposium, where we discussed algorithms and their impact on culture at large, and there was so much – in my view, being someone who does not consider themselves to be the most literate on the subject – I find that there is a lot of illiteracy that leads to a lot of paranoia, which actually doesn’t work. And this is something that I was surprised to find in Manfred Mohr, in the 60s, the idea that we need to push for literacy, because actually it is a tool that extends our ability, I think, especially for the purposes of architecture.  

Federico, speaking about the work of his studio today, really clarified that in a very direct and visible way; how we can use applications of computation within groups today, on the design side and the management side, and how these two things can be harmonised through technology. It’s an amazing development, and one that you know Manfred Mohr would be happy about, let’s say, as far as literacy on the subject goes. So, I’m very happy that today we are collectively contributing to this, adding to this history. 

I keep saying lately that we need new hermeneutic tools; tools for understanding computational design and computational tools and how they can be integratedinto established methodologies. How do we integrate new tools into existing methodologies? For example, in the work I did, I was really interested in seeing Moretti’s exhibition at the Triennale where he actually proposed a few buildings. Analysing that exhibition alone, we can see how certain parametric tools were used for specific typologies of buildings. Moretti could have applied this to anything, but he chose to apply it to a certain large-scale urban infrastructure, such as a sports arena, or a cinema – things that we understand as “large objects”. Large single objects that can respond to one main parameter. And actually, towards the end of your presentation, Marco, you said we “could not compute” – we need to understand the scale of algorithms and how far they can go, where they can be applied to architecture in a meaningful way and where perhaps not at all!.  

MV: 

I think, yes, in retrospect, Moretti focused on typologies that, if we fast-forward 50 years, are typically parametric now, they are more or less mono-functional. Nowadays, a stadium is no longer mono-functional, but it is actually designed [so that spectators are all] looking at the pitch, and therefore we developed it into the most parametric typology. I’m not sure how aware he was of that actually, also because I think at the time the stadium itself was a rather new typology, in a way. Sport, and the “massification” of sport, and so on.  

The other thing I want to say, regarding the discussion – and I’ll just throw it in there perhaps – is that we take it for granted, that for many, many years, computational design, especially from the early 90s, has never really confronted the past. As if it was developed in a vacuum, let’s say, as if it just came out of nowhere. Of course, this is understandable, because architects were all very excited; they wanted to kind of experiment and bring this new technology to fruition to start building. The economy at the time was better than today, so there were things that were converging, let’s say, but what I find particularly important is that at some point, eventually, it is actually, really necessary to go back and see that there is a legacy there. There is a tradition; which is a very normal, traditional architecture, as we know it, and it’s not just a bunch of punks that play with computers. In terms of the cultural relevance of the discussion. 

And then, of course, we can say that we have always been parametric, or that architecture itself is a discipline that is about the idea of establishing algorithmic procedure to get something built. 

AB: 

I think the knowledge that we should perhaps understand, and I think Manfred Mohr’s work really helps us with that, is that it’s perhaps just the idea of encoding certain processes that have always been part of architecture. Coding them, and then potentially automating them or doing something else with them, is what machines allow us to do, but that doesn’t necessarily change how we think about it; it’s not the end.  

I want to stress the fact of what you say about the importance of history, or how we are trying to reconnect – or rebuild bridges, if you like. For some parts of the discourse on digital computation, perhaps it’s as if history started in the Bell laboratories, or something like that? It started in the US with the beginning of mass computers and stuff like that. But I think, Roberto, of course, has done a lot of work on building bridges,  and making us understand that the bridges go a lot further back in time, in fact.  

RB: 

I keep thinking about what Philippe said a second ago, and why computational logic keeps going metaphysical, and I think it’s a side note, but I can’t stop myself, I have to say it! 

There are two ways to look at it, one is that you’re totally right Philippe, [Ramon] Llull is the point of reference in this conversation, and again, if we’re talking about bridges that were burned in history there’s definitely only a vague understanding of the importance of Llullism. How could it be that a person who invents concentric wheels, who wants to basically convince Muslims that their religion is inferior, has a lasting effect throughout Europe for over 300 years? I mean, it’s not even explainable as a joke! I would say this is perhaps interesting – because it is a computation project, there is no doubt about that – it’s very interesting because computation sits at a moment in history where other notations emerge for non-visual, or non-mimetic ways of articulation, articulating reality and knowledge. That was interesting for Philippe – but his is just the last presentation we saw and I tend to have a short term memory! 

It was also interesting, for instance, for Manfred Mohr, this constant tension between the visual and the conceptual – and I think that is one of the interesting premises of computation, historically, over a very long period of time. A system to articulate something that lies between the intelligible and the sensible. Something that cannot quite be sense, and yet needs to be very clear to the mind. This tension, the fact that computational logic always tends to be in that realm, is probably something that has to do with that. 

Obviously, you could also look at it a different way, you could say, well, computational logic is a simple mathematical process that could be grasped a lot earlier in history than other, more advanced, mathematical models; or you could also relate it to the fact that, for some reason, the Christian tradition forgot the first commandment, because we should not really be able to draw God. But we decided to ignore it, for reasons that are not entirely clear to me, and the kabbalistic tradition did not ignore it, the kabbalistic tradition is a notational system for symbolic articulation of the world without generated images. So, I think all I want to say is that the short comment that Philippe made in passing could be quite powerful. 

AB:  

I love that this took a theological dimension! I think it’s really crucial; this constant question on this idea of the visual and the conceptual, even in the work of Manfred Mohr – when you talked about this period when his work was purely code and, in fact, in the exhibition, there was a printing machine just printing whatever was coming out of the program. Then later on, in the 80s, with the development of the visual interfaces, his work became different – and in fact you connected it to the work of Peter Eisenman.  

So, it’s really a key question for me that today, of course, software is popularised, there is even visual computation, visual algorithms… this is possible through software such as Grasshopper. There are aids to an understanding of a visual means through code, let’s say, and I’m interested in this, because for a long time we have been discussing computation and architecture purely in terms of data – how do we get data, how do we structure data? But today, we’re in a different environment, where software is more developed and more accessible, and people don’t necessarily think about “what’s in the black box”; but nevertheless, what comes out for me, when I look at it again, I can only understand as computational. Even more so when it’s informed by the language and culture of the digital – by the culture of digital tools.  

I’m really curious to hear your position on this, whether you see where we are going in a sense? Is visual computation comparable to a purely algebraic or coded computation? Can we compare the two, can the two coexist? Philippe, I would love to hear your answer, but this question is extended to everyone. I think it touches everyone, pretty much.  

PM: 

I mean, first, just a very quick note on this metaphysical issue associated with combinatory rates. My feeling is that at that moment in time – you know, in the 13^th Century, or 12^th Century – it was a bit extraordinary to be able to demonstrate that only a few numbers or parameters could lead to so many possibilities. So, I think there are some magic tricks for the people who know nothing about mathematics, there’s some magic associated with combinatorics – at least at that time in history. Of course, today we look at that as something which is pretty simple; we are not surprised anymore by anything to do with combinatorics and we are probably more impressed by some other domains of mathematics that are more conceptual but, I would say even in the 20^th century it was impressive, there was some magic to it. My feeling is that if it’s a bit associated with metaphysics, it’s also because there is some intrinsic magic in this combinatorial explosion at some point. It’s a very sketchy hypothesis! 

Regarding the question by Alessandro; no, I believe that visual programming is not like more standard programming where we use code and symbols. It creates the same effect, but I would say probably the intellectual operations are not exactly the same – also the feeling we have is not exactly the same because, in one case we do things – it’s a much more visual operation. When you do visual programming it’s a bit like putting some order in a PowerPoint presentation, you shift some slides until it’s made, but when you do programming by writing code I think it’s a slightly more analytical approach, or it’s more textural, more text based. 

AB:  

I agree. Then my question is to the end of making architecture – as of course I understand what you are saying, the two things are very different – but to the end of making architecture, toward the end of what is useful for architecture? Because if I look, for example, at someone like Federico, they use computational tools, but the input is very much like a curve that is drawn, and they use this data to then do different kinds of processes. That one curve can start influencing other curves that are drawn and things like that, but there is an input that is drawn. Whereas in a lot of computation, for the description of the visual design, there is always this question – even in the academic work at the Bartlett – of where does the data come from, and it’s almost like a theological question; it has to come from some God-given numerical formula. So I’m interested in this question, which, I think, is quite a central question, methodologically. 

PM:  

I would say, probably, we are entering an era in which the data is becoming more important than the algorithms. I don’t know if it’s true scientifically speaking, by the way, but at least the mindset is maybe in favour of a deeper influence of the data, over the influence of the algorithms, maybe – but again it’s definitely not a scientific statement. Probably because it’s much easier to associate the data to everything which is happening in society at large. 

For example, we know the data of Facebook, because we see them every day. Although we don’t see all of the data, we see how it works; but we don’t know the algorithms they are using. So, even if I believe that algorithmic science is more developed and more advanced than ever – it’s absolutely crazy the complexity of algorithmic science today – most people don’t have a grasp on that. So this is why, maybe, we can say that on an everyday basis the data seems more important in today’s society. 

AB:  

I agree with that. Perhaps it’s also because certain algorithmic blocks are more available. I can bring the example of my students last year: they would take existing machine-learning procedures, then completely change the data set to an architectural data set, for example on architectural typologies, and then they would tweak the machine learning “black box” to adjust the output to what they needed it to do. So, in a way, this is a different approach. I mean, scientifically it is not a purist approach to computation, but ultimately, at least what I’m interested in is, how can we use it, even if it’s about using blocks and bits, how can we then tweak them to be useful for us as designers? That is my point to you. 

Are there any more comments, or questions from the audience? We had a pretty amazing rate of people not dropping out.  

PN: 

Actually, when you were asking the question about visual computation versus algebraic code computation, I wasn’t exactly sure why it was asked us a question. Maybe it’s because it’s 1 am, but when you were asking, it actually reminded me of John Nash, the guy who got the Nobel Prize for game theory. When he was 25, before he developed mental illness, he was actually famous for the “embedding theorem”, looking at high dimensional objects and whether you can actually embed them in any Euclidean space. We usually visualize this sort of embedding like a donut, with a lot of waves flowing through the donut, but actually when they interviewed John Nash everything in his brain was numbers; he was never really a visual person.– He completely hated the movie A Beautiful Mind [a biopic of John Nash] because he didn’t see things [in the way it portrayed], like his schizophrenia was a miracle – I mean that’s crazy to a very banal brain like mine. 

I don’t really see the visual and the algebraic as either/or – and also, if you look at Chinese mathematics, as Philip also showed, the entire book of change, the I Ching with the hexagrams, was not visual. They literally document everything with Chinese characters – and it’s crazy when you have to read through that, because China is an agricultural nation, so we measure everything pragmatically. The mathematics is metaphysical, but we’re measuring the depth of the soil, how much rain we need, in the book of I Ching, and they would write down “12345” in those complex characters and people would still manage to do the geometrical calculation in their mind, which is crazy. 

When talking about Facebook data, there is always this privacy/ethical question that I agree is becoming theological and inescapable – but maybe it’s just because of the mindset that we feel like we’re always dependent on a centralised platform. We’re actually making a sort of trade, where we surrender the data because they’re doing a social service for us. A computational service that would be hard to do as an individual. So maybe the mindset is, as opposed to passively surrendering data, is there a way to actively contribute data so that we get over the data privacy problem? 

AB: 

I was thinking about how, for example, architecture data is scarce. When we did this research on technologies, it was really hard to find this data. Where do you go? You need to go into the old registries of each city to find the undigitised maps, and try to redraw them and things like that, so we also live in that reality.  

Also when you mentioned the abstraction versus visual idea, I was reminded of my dad, who in his career was a computer programmer, and how he always says that he sees the numbers and not the visual things, so for me this is slightly triggering on some levels!  

Anyway, any more comments or questions? 

PN: 

It’s actually like CAPTCHA, right, what they really do is that they don’t hire an intern to label a data set, but instead they create an economy by distributing the labeling tasks to users, match-making two problems – problems in training machine vision and in validating humans – [to create a solution].  

AB: 

Yeah, we’re waiting for a start-up to deal with the architectural algorithm!  

Provides Ng 

(Laughs) [Get people to label] doors and windows for BIM? 

AB: 

Exactly. That perhaps is a good implementation.  

All right, I’m thinking that I will close this amazing session here today, just because, again, we were meant to finish at five! 

I’m really grateful to all of you for your contributions, and again, today was a kind of amazing and stellar way to present the journal that will come out next year. So thank you so much for this discussion. It’s really precious, for me a lot of ideas were really fruitful in amplifying the conversation on computational design. As we have seen, augmenting the literacy and the discourse and the different threads on it, and even the historical grounding of this discourse, is fundamental.  

So, thank you so much.