Deadlines 2

 So now what? A few ideas on education and deadlines.

In the early 1900s, French publisher Jean-Marc Côté published a series of postcards titled “En l’An 2000”, showing a range of wild inventions humanity will be endowed with in a hundred years: from the obligatory flying cars to what seem to resemble Roombas, Zoom and synthesizers. One postcard in particular is striking: a classroom where a teacher feeds books into a hand-cranked machine, being turned into lectures for the students. It’s a rather top-down approach; the system seems to work, at least in the eyes of the educator.

 

That future didn’t arrive 22 years ago, but some gists seem to be floating around. Frankly, it would be lovely to just throw a book at someone and have it memorized instantly. Sadly, us humans are complicated units, so we’ll have to look for other ways to deal with education.

In a previous article, I responded to Mathijs van Kouwen’s plea for a ban on deadlines between 11PM and AM. While I agreed with his general principles, it had to be added that deadline culture can stifle some, could blur a work-life distinction and create a bummed-out student.

There were some reactions, so some nuance should be provided. Just pointing out what doesn’t work is easy, but coming up with something better? That’s a challenge. This article posits three ideas for education that might ease this problem of deadlines and other educational gripes for the better.

1: Means and ends

First off, the underlying problem here seems to come down to a confusion of means and ends: what serves what? More concretely: are the systems put in place for education mostly serving themselves, or the educators using them for their students?

Take grading, something also touched upon by Bob van Vliet. While it usually seems to work out fine, it has shown itself to be lacking in nuance - how can someone really be .2 grade-point better than someone else at an essay? - as well as demotivating those that need motivation and vice versa. The same goes for deadlines: weekly box-ticking does not always equal learning.

So, what to do? Don’t put all hope in the system and leave some room for human-to-human interaction. It is worth noting that having hundreds of different systems for different students is impossible, so there will always remain a certain system of generalization. Just know when it has gone too far. 

2: Taking the weight off

We Dutch don’t really like to celebrate things lavishly. Our birthday parties can look more like a plastic chair therapy session than a jubilant fest and we’re among the quickest in Europe to finish our meals each day. So it should come as no surprise that this ‘act normal, that’s crazy enough’ mentality is ingrained into educational events as well: when you’ve finished a course, there’s no time left to ponder. Move on, dear.

And yet, finishing a large deadline can leave many unresolved feelings; clicking a button is something you do umphteen times per day already, so why would that one ‘submit’-button be more special? 

There are some professors who are doing things differently, with a post-deadline lecture congratulating the students on their achievements, looking how far they’ve come. It can sound a bit silly, but it really does allow for good closure and reflection of where the student is at. After all, as John Dewey once said: “we don’t learn from experience, we learn from reflecting on that experience”.

So here’s the thing: humanizing systems of education makes them less daunting. Of course, trinkets should not be the focus of educational activities, but a little gown would make it all the more worthwhile.

3: Learning, unlearning.

Amar Bose (yes, that Bose) was somewhat of a legend at MIT. His tests were a thing on their own, with all of them being open book, though with questions that could nowhere be found in the curriculum and had to be solved anew. Moreover, there was no set deadline for the tests: as long as you wouldn’t leave the class, you could work on the test for as long as you’d like. Finally, about an hour into each test, TAs would rather abruptly bring out ice cream to hand out to the students, because, well, why wouldn’t you do that?

However unorthodox it might seem, his classes yielded good results: many students of his went on to become prominent audio engineers, with the field as a whole being revolutionized by Bose. So why did it work?

Bose seemed to focus on discipline without caveats: it doesn’t matter how you do something, as long as you just do it. In a sense, Bose looked to gamify the course to a certain extent: students can do whatever they want, but would soon discover their own methods of dealing with tests, which could often overlap with the conventional, but not always.

In a way, education could shift from the craftsman-apprentice model to something more like a provider-creator model. In this model, the student is someone who creates and/or interprets something provided by the teacher in the form of a case, a theory, or something similar. The result of this is more freeform, challenging the student to come up with something of their own, yet still incorporating the existing matter at hand.

Now, before there can be innovation, there has to be some education about what actually is supposed to be innovated: learn first, unlearn afterwards, otherwise a totally chaotic learning environment will arise. 

It is therefore wise to only try this in a master or doctoral environment, not in the bachelor. 

Closing notes

Hopefully, this conversation will develop further into something more solid, with a continuous drive towards innovation in education. And again, our current method of education isn’t all too bad. It could just use a little more future.

Deadlines

First published in TU Delta: https://www.delta.tudelft.nl/article/letter-get-rid-deadlines-2#

I agree with many of the points that Mathijs van Kouwen raises in his letter, Get rid of those crazy deadlines, though there are some issues regarding his proposal. I would suggest that wherever possible, a standard midnight deadline is set. That’s then it. People can go to bed and get a healthy seven or eight hours of sleep. With a midday deadline, it is too tempting for people to be up all night, as Van Kouwen himself says, or to end up in a disruptive rhythm for other reasons.

But there is a more fundamental issue underlying the problems around deadlines and that is not so much the times, but the number and the gravity of the deadlines. It seems as though there is greater emphasis being placed on production and this is leading to a continuous maelstrom of unnecessary pressure, represented by the never-ending number of deadlines set.

The danger of this perspective is that students learn to know what is expected of them, but have little space for creative innovation and reflection. The division between studying or working and life outside becomes obscured. Shockingly, the architecture profession puts this on a pedestal. Architecture firms state not having a ‘nine to five mentality’ as a requirement on their internship vacancies. They want to produce as much as they can, at the cost of quality.

Just stop it! There is nothing wrong with hard work, but this culture will ultimately create a miserable human being that will produce miserable work.

The creative process needs space to breathe and sometimes be given a free rein whereby deadlines should be a tool and not a goal. My conclusion is that TU Delft should set clear deadlines at midnight, or at 20:00 if there is no other choice, so that people know where they stand. Students should also be given the freedom for reflection and training without continually using a grading system.

Elgaland-Vargaland and the Phenomenology of Space.

Originally intended as a paper for a course at the faculty of Urban Studies at Leiden University

Introduction

What makes a place a place? This paper will discuss several interpretations of what ‘place’  is, and analyze these definitions through the lens of the art project of Elgaland-Vargaland. Along the way, concepts such as multiculturalism, thirdspace and heterotopia will be assessed and discussed.

Definition

First, to make things clear: there is a distinction between ‘place’ and ‘space’, with space being a location without a specific meaning, in contrast with place (Tuan, 1977). This is a relatively minor difference, but can lead to confusion.  Therefore, in this paper, the term place will be used.

There have been several scholars who identified ‘place’ or ‘space’ in three or four terms, which roughly seem to outline the same concepts. 

In 1976, geographer Edgar Relph identified the following three components of ‘place’ as being:

1. The setting/location of the place, the position and ‘flesh and bones’ 

2. Activities, situations and events in the place

3. Meanings associated with the place, both individual and group-like.

Some of these components could be interpreted as being parts of the same concept, such as Lefebvre (1974) would combine P(2) and P(3) into one concept, the espace vécu, lived space. However, the reason to split up this is based on the fact that P(2) is objective, whereas P(3) is mostly subjective. In this paper, these different components of place are indicated with P(X), with X being a number. 

It is useful to add a fourth component to this definition, being:

4. Conceptuality of a place.

P(4) deals also with the ‘state’ or conceptuality of a place: architectural drawings themselves would not be called a place, though they do describe a place that is not yet built. But if the drawings are there, then there is a notion of the place already, and the other components of place can have valuable information being ascribed purely from the drawing. 

One might be tempted to say P(4) is just part of P(3), but this can be refuted with the example of religious places, such as heaven, hell and limbo: their state of being is defined by P(4) (Maier, 2013).  These places have characteristics which can very well be described along the lines of P(2) and P(3). It also can’t be said that the very notion of heaven itself does not exist, just like the notion of a demolished building still exists. And it’s this notion that differentiates it from P(3).

Table 1: P-components in a table

	‘What it is’	Abstracted
Things being there	P(1)	P(4)
Things happening there	P(2)	P(3)

P(4) resembles Edward Soja’s theory of secondspace somewhat, in that it mostly deals with conceptuality (Soja, 1989). Soja’s theorem falls flat when it comes to accurately describing Los Angeles, as he uses too many dualities for it to be really relevant at times (Mitchell, 2002).

A heterotopia can also be explained more easily with this model: as these places are reserved for deviations of the norms of P(2): that what is expected of the place is explicitly different from the normal spaces surrounding it (Foucault, 1967). 

Table 2: Examples of places with their descriptions

Place	P(1)	P(2)	P(3)	P(4)
Limbo	Somewhere between heaven and hell	Not much	Mostly boring	Ethereal
Albert Speer’s ‘Germania’	Berlin	Nazi rallies, fascist daily life	Awful	Unbuilt, experienced through models
My current room	Somewhere in Delft	Typing this essay	Kind of warm, it’s ok	Built
A unified Ireland	Ireland and Northern- Ireland	One Irish political system	Both catholic and protestant, etc.	Physical, though not as one place.
Heterotopia	(...)	Different from the norm	Personal interpretation	Built
Soja’s Los Angeles	Southern California, but also ‘everywhere’, like the Aleph	The essence of California	(...)	‘Both real and unreal’

If any of the components change, then a place is different. Though, can you really say that a place with changed values is fundamentally a different place? The line can be drawn at several points, with a weak hypothesis only deeming P(1) and P(4) as fundamental. The strong hypothesis includes P(2) and P(3) as fundamental. The order of importance can be seen as P(1) → P(4) → P(2) → P(3).

Definition of Elgaland-Vargaland

Figure 1: Flag of Elgaland-Vargaland in Svinesund, the border crossing between Norway and Sweden.

Source: http://cabinetmagazine.org/issues/18/blackson7.php [Visited: 16/11/2020]

A good example of how to play and experiment with the notion of place is Elgaland-Vargaland (abbr.: KREV). Founded in 1992 by Swedish artists Carl Michael von Hausswolff and Leif Elggren, the ‘country’ encompasses all places of ‘no man’s land’: borders, international waters, the unclaimed territories of Antarctica, et cetera: all Elgaland-Vargaland (Middleton, 2015) (Newman, 2007). Next to that, Elgaland-Vargaland encompasses mental ‘states’ as well. The state of limbo? That’s a subregion of Elgaland-Vargaland too. So are the other religious territories. Dreamland? Yup. Even the digital world isn’t safe from the colonialism of KREV.

It’s incredible how paradoxical the nation can be: it is both the largest and smallest on earth, has diplomatic entities in place, yet appears to be completely unrepresented on the world stage. It has a flag, stamps, a national anthem, passports, even its own embassies. Yet no-one officially lives in the place, though citizenship can be obtained outside the country by sending a letter to the embassy in Stockholm. 

Interaction between the two concepts

Now how does Elgaland-Vargaland play into these components of place mentioned earlier? It does quite a good job in dissecting all of these, with several components. 

Notable is also that Elgaland-Vargaland claims all virtual, dream and religious space, thereby heavily playing into the concept of P(4). Because, while virtual spaces have been ‘conquered’ at times (be it hacking, or government restrictions on access of certain sites), it would seem silly to conquer the other spaces. However, what about propaganda and things like a Thought Police? In a sense, this can be seen as colonization of the state of mind.

Furthermore, P(1) is flexible in Elgaland-Vargaland, as borders tend to change, but also aren’t always considered solid, in the case of heavily disputed territories for example, where there can be very real borders. So, is this KREV? In theory, yes, but in reality, it seems unlikely and frankly, a bit silly.

Multicultural state of mind

No one lives in KREV’s territories, yet it does have several embassies and consulates of its citizens, which could be interpreted as an exclave of the country by some, and to that extent as soil. However, the legality of this is a bit vague, because several people have lived in embassies under the approval of the country behind them, not their official soil, such as Julian Assange in the Ecuadorian Embassy in London (Addley, 2019). In that sense, it can be seen as foreign soil, which also expands KREV’s claim to territoriality.

The constitution of KREV explicitly states the promotion of tourism and multiculturalism within Elgaland-Vargaland. (article 30 and 31). Of course, it’s easy to ‘visit’ a mental state, the only thing holding you back is yourself. But how about the border territories KREV claimed?

At one point in 2002, several ‘citizens’ of KREV attempted to cross the border by ferry from Finland to Estonia and, although successful in getting on the boat in Finland, were shortly detained in Estonia, because of their ‘fake’ passports (Middleton, 2015). So, in practice, KREV’s policies don’t really work out yet.

Furthermore, the Constitution explicitly states that it seeks to unify every country on Earth to a single state, that of KREV. What this means, is that there will no longer be any real territorial claims to place, rendering the political notion of P(2) quite useless, and discrediting P(1) a bit. Because, what’s a country when it has no borders and political system, other than a cultural entity? After KREV (somehow) has taken over all of the planet’s soil, every citizen will have a territory of its own, yet this claim will mostly be useless.

All this is remarkable for one thing: multiculturalism. Because, remember, the notion of culture isn’t particularly bound to place, such as in the case of the Romani (Pehkohnen, 2018). While it could be argued that the Romani do not have a definite ‘place’, the descriptions of P(2), P(3) and P(4) are still very valid, and P(1) can be described, just being very complex. If KREV were to succeed in their pledge of unification, P(3) would be the last to change, because this place-component of meaning is deeply personal. One might even say that to achieve true multiculturalism, everyone should be able to express their notion of P(3), while acknowledging the other components of place. However, before this will become a reality, years and years will have passed.

Conclusion

Place is a funny thing. In this paper, the concept of place has been analyzed in four components, based on those by Edward Relph: 

P(1), indicating a setting/(physical)location, P(2), indicating activities, P(3) indicating meanings and P(4) indicating conceptuality. The art project of Elgaland-Vargaland was analyzed and deemed very interesting in demonstrating these components and their implications, in multiculturalism for example.

References

Addley, E. (2019) “The seven-year itch: Assange's awkward stay in the embassy.” The Guardian. From: https://www.theguardian.com/media/2019/apr/11/how-ecuador-lost-patience-with-houseguest-julian-assange [Visited: 16/11/2020]

Elggren, L. & Von Hausswolff, C.M. (1992) Elgaland-Vargaland: A Short History. From: https://elgaland-vargaland.org/a-short-history/ [Visited: 16/11/2020]

Foucault, M. (1967) “Of Other Spaces, Heterotopias.” (trans: some guy, 1984) Architecture, Mouvement, Continuité. 5: p46-49. From: https://foucault.info/documents/heterotopia/foucault.heteroTopia.en/ [Visited: 05/11/2020]

Lefebvre, H. (1974) The Production of Space.

Maier, H.O. (2013) “Soja's Thirdspace, Foucault's Heterotopia and de Certeau's Practice: Time-Space and Social Geography in Emergent Christianity” Historical Research. 38-3 

Middleton, N. (2015) An Atlas of Countries That Don’t Exist: A Compendium of Fifty Unrecognized and Largely Unnoticed States. London: Pan Macmillan.

Mitchell, T. (2002) The Psychasthenia of Deep Space. From: https://discovery.ucl.ac.uk/id/eprint/4325/1/4325.pdf [Visited: 16/11/2020]

Newman, M. (2007). “Slash Fiction.” Art Monthly, 306: p30-32

Pehkonen, S. (2018). “Impromptu facts and moral panic: the Roma people and local communities.” In M. Ojala-Fulwood (editor), Migration and Multi-ethnic Communities p. 223–244. Berlin: De Gruyter. From: https://doi.org/10.1515/9783110528879-010 [Visited: 16/11/2020]

Relph, E.C. (1976) Place and Placelessness Toronto: University of Toronto Press

Soja, E.W. (1989) Postmodern Geographies. New York: Verso Books

Tuan, Y. (1977) Space and Place: the perspective of experience. Minneapolis: University of Minnesota Press.

Get lost

Originally published in BNieuws in October 2020. You can find this article there too.

Cities are full of surprises, mostly pleasant, sometimes unpleasant or even boring. All these elements combined form a complex whole, which is hard to grasp for the human mind. Relying on your phone to get around in this complex whole, however, leaves you with a shallow image of a city. I think that it is nowhere comparable to the experience of inhabitants, which bothers me. Therefore, I would like to introduce you to the concept of “getting lost”.

In this age of GPS navigation, the act of getting lost has itself been lost. Think for a moment about the last time you genuinely ended up somewhere without knowing where you were. There are many forms of being lost and the perception of what it means undoubtedly has changed over the years. The availability of an all-knowing device in your pocket, the amount of information around you and the extensive network of public transportation, makes being lost less serious. Bringing being lost back to the old days is quite complicated in a world where information is all around you. So, how does one knowingly get lost?

There are several strategies, but this is the one that worked for me:

1. Find a vague indication of where you want to be heading, preferably by bike. The first game I played was cycling from Delft to a village a bit outside Delft. For a higher chance of getting lost, consider a residential, not touristic location. In the case of Delft, this could be Maasland, Bergschenhoek, Monster, etc.

2. Don’t look at maps! Not during your attempt, not beforehand, never. Additionally, avoid looking at signs. This will be quite hard, but you must try. They just give too much information away. However, bring your phone with you anyways, just in case things actually get out of hand.

You’ve succeeded when you come to a point where you don’t know how to get back and have the slightest clue of your location. You will find out that the more you play this game, the more difficult it becomes to get lost. Once you get familiar around a particular place, the chance of getting lost drops drastically. In that case, you will have to go to even more alien places. The world is your oyster at that point.

The first time I tried to get lost, I aimed for Berkel en Rodenrijs, but in that area is not very challenging to keep track of where you are. So I kept going and ended up in Rotterdam, which seemed not very challenging either at first. I tried again, until the point that I was almost lost. Almost, since I noticed a somewhat familiar railway bridge in the distance. The train station in Rotterdam-Noord. Damnit. It took another 30 minutes, but eventually, I succeeded: I was completely lost! It happened somewhere around the Insulindeplein in Rotterdam, after taking a ‘wrong’ turn. It is a weird feeling, one of distress and joy combined, but boy, I sure was glad.

What to take from this? I think that we are so used to moving around in a city with a purpose, that we’ve lost the skill of looking. Being lost forces you to look around with all your senses and therefore opens up a whole new world. It makes you vulnerable but connects you to your environment at the same time. So next time you are in a new place or city, you have a choice; do you take the standard way of moving around, or do you challenge yourself with an adventure into the unknown? 

Houses of Machines - AI in Design

Originally published in BNieuws in October 2019. You can find this article there too.

Recent developments in artificial intelligence have posed a challenge to the world of architecture and design. Contrary to previous computer methods, which could only have a deductible output based on a formal input, artificial intelligence replicates the creative process. This has posed a threat to architects: what role will AI have for the architectural profession? It is necessary to find the right approach to handle AI for architects, urban planners and landscape architects, as the development of techniques for architectural, urban and landscape analysis have been rapidly developing, with a possible future out-performance of architects by these techniques.

Say a system is desired that creates images of domes. It does not know what a dome is, so a discriminator is set up which tries to determine if the picture given to it is a dome or not using a value from 0 to 1, with 0 meaning: ‘This is not a dome’ and 1 meaning: ‘This is definitely a dome’. To do this properly, a large dataset containing images of domes is used, labelled with their according values. To create images, a generator is set up, which generates an image from a large number of parameters. The created image is sent to the discriminator, which renders the initial image of pure noise to be nothing like a dome: the discriminator gives a 0 to the image, with scores being assigned to the parameters of the generator as well. So the generator adjusts its parameters to create a more dome-like image, repeating this process over and over, until the parameters are tweaked just so that the discriminator is convinced the generator produces images of domes. This method is called a generative adversarial network (GAN) and is one of the most common methods for content generation using AI today. A variation on the GAN-method is to use the ‘style’ of pre-existing images as an input for the generator. To use the dome example: say, a baroque dome will be ‘played’ in a gothic style. The discriminator will decipher the ‘gothicness’ of gothic images provided and tweak the generated images of baroque domes so that it looks both like a baroque and a gothic dome.

‍Design Methodology

Design methodology is the study of the methods of design, with an emphasis on architecture. The term ‘design methods’ is quite a broad term: it can describe everything from the process of design in the mind, to the ways of planning, doing business and dealing with contractors. Every building or structure has been built using one or more design methods. Even animals maintain design methods: a birds nest is built on the principle of gathering materials nearby, continuously changing the design according to the needs at the moment of construction.

Within the history of the design discipline, we can speak of craftmanship. A person becomes a craftsman not by reading up on how to become one, but by trial and error, learning from previous work, which itself has been the product of years, if not centuries of trial and error. If one asks a craftsman how their craft was made, they most often cannot tell you how they made their choices of design, other than by instinct. The craftsmanship approach used to be the most common way of designing in architecture during the Classic up to the Gothic period. During Gothic ages, most buildings were built without a masterplan. The art of ad hoc stone masonry, combined with the art of geometry prevailed the design. And even though the underlying ideology for Gothic building was fairly well-documented, the evolution of the style has been completely due to craftsmen, not published literature.

‍Artificial intelligence and design methodology

While the development of ‘design methods’ appears to occur independently from that of artificial intelligence, there are essential similarities between the two, which provide a deeper understanding to the application of both fields in architecture. Notice how the generative adversarial network system eerily resembles the craftsmanship approach to design. The trial and error phase is analogous to the discriminator and the act of crafting without knowing how the craft resembles the generator. A large difference between the two subjects is the matter of time: where the mastering of a craft takes centuries, this network takes weeks to do a similar job.

‍Critique of Artificial Intelligence in Architecture

Some say that artificial intelligence offers a cornucopia of creativity, rendering architects virtually useless, flooding civilization with endless ‘good’ architecture. However, this is far from reality. AI systems, certainly at this point in time, come with great limitations, not only in computing power, but in general logic as well.

Suppose a fully functioning AI system is desired, that produces CAD-drawings given a list of requirements. How would this system work? First of all; using natural language processing, the list of requirements has to be deconstructed into bite-sized, AI-friendly pieces to be interpreted properly.

Now that is known what to build, how should it be built? Propose the system chooses a style at random, ignoring context. It is assumed this style is a classic style of architecture, constructed around the rules of classicism. The system has analysed the distinct placement of elements and their size, ornaments are constructed using StyleGAN, mechanical stability of the proposed structure can be easily calculated using statics software, et cetera.

However, this is far from perfect: beginning with the problem of language. While natural language input processing by AI is improving over time, it remains a weak link in the chain. Exact input being statements as ‘the maximum load on this beam is 500 kN’ and fuzzy input ‘make this room look nice’. The question arises to what extent exact input in architecture occurs. Whilst mechanical requirements are generally clearly defined, statements that appear to be exact, such as ‘the maximum surface area of this room is 50m2’ are not always as exact as they seem in architectural processes. The deviation of these semi-exact statements and their consequences of error differ from client to client. And even more so in architecture than in art: not only does every culture have their own interpretation of art, combined with the different ways of building and demands, there cannot be a consensus of universally good architecture.

‍The 'meaning' of architecture in relation to artificial intelligence

This raises the question: Is it possible to add this meaning to a system? Meaning can be highly interpretative, however, discrete meaning exists in architecture, for example: using chemical analysis, it is highly certain that the dome of St. Peter’s Basilica is made of concrete. So while an AI system might accurately know that Michelangelo painted the dome of St. Peter’s Basilica using its knowledge of all domes, for it to know that the sixteen figures represent the sixteen first popes, a whole other system is needed. For an AI to understand the dome at the level of an expert, an incredible amount of useful data would be required.

And what about the generation of such a dome? Using the GAN method, an image that appears to be such a dome at first glance is generated. The details of the dome are generated based on existing images, merging the existing details to a smudge without meaning. For the system to add meaning, it needs to know the context which is wanted from the user.

Is the process of designing a process that can be reduced to a logical system, or is it truly a black box? The two groups in this debate are that of the designer-scientists and that of the designer-artists. According to the argument of the designer-scientist, there exists a discrete, logically deductible system that can produce an architectural design from a list of requirements, with every step of the way being entirely understandable in its behaviour. The designer-artist adheres to the theory of the black box. According to this argument, while some steps of the design process can be clearly defined, creativity and design at their cores consist of expressions of  the philosophical concept of the sublime: an indescribable sense of quality.

While artificial intelligence could within its logic easily adhere to the designer-scientist (despite relying heavily on the black-box theorem), for it to accurately replicate the sublime, these indescribable experiences need to be described first, which is fundamentally impossible. Of course, there remains the possibility that the sublime consists of made-up constructs, envisioned by a mystique surrounding the - to a designer-scientist potentially describable - quality of the object.

To conclude, artificial intelligence has potential in the analysis of architecture and to serve as a source of inspiration. But is far too limited to create a functional building design at this point in time. Because of the difficulties in the notion of meaning and quality of architecture, one can doubt the feasibility of an AI-architect becoming a reality in the near future.