Notion Parallax

Choosing Gas

Mon, 24 Feb 2025 12:00:00 +0000

While I was doing my ANDP course I was interested in how the relationship of deco gas O₂ percentage had a non-linear relationship with the time it would take to get to the surface.

Naïve me thought that if 50% O₂ got me to the surface in x minutes, then 100% O₂ would get me there in half the time, but that’s super wrong. You can use a leaner mix at a deeper stop, meaning that it’s useful for longer; that stepped relationship means that there’s some weird steps in the graph:

This plot shows the total run time, with 3 different run times at 4 different depths. The ⭐ shows where the sweetspot is for deco-acceleration. (Or the safest perhaps if you’re going intentionally slowly.)

The graph above assumes that your back gas is air, but if you were to go for a nitrox back gas, what’s the sweet spot there? The problem is that it’s a 2D problem now, and that makes it hard to show on one complicated plot, so here’s an even more complicated table of plots:

Back gas ppO₂ 1.3, Deco gas ppO₂ 1.6 - Decompression Profiles

Depth	18 min	21 min	24 min
35m
40m
45m
50m

And here’s that again, but at a ppO₂ 1.6 of 1.4 for those who like to live dangerously:

Back gas ppO₂ 1.4, Deco gas ppO₂ 1.6 - Decompression Profiles

Depth	18 min	21 min	24 min
35m
40m
45m
50m

These surprised me, I didn’t expect the low % nitrox to have such an effect on deco.

I was interested to see that the benefit of the highly optimised mixes isn’t a wild improvement on just having a 50% and being done with it. With a worst case scenario of 24 minutes at 45m, nitrox 28 back gas, and nitrox 83 for deco gets you out of the water less than 10 minutes faster than air and 50%.

I’d imagine that this process would be a lot more useful beyond the realm of what can be plotted on a 2d graph, when you’re dealing with helium, multiple deco tanks, and much longer bottom times/depths. Then it might be able to knock a fair bit off, and 20 minutes less deco might be the difference between freezing and having a good day. I guess I’ll find out later when/if I do my trimix course.

All decompression calculations use the decotengu library, a pure Python implementation of the Bühlmann ZHL-16B-GF algorithm.

Printing a reel

Tue, 10 Sep 2024 12:00:00 +0000

I have a thing that happens in my brain, maybe it’s because of a brief time as a person who made things, that I think I can make things. It means that I’m pretty resourceful, but it’s also got me into some serious pickles over the years. I’ve thought about it a lot, and I’m able to catch myself before I get into serious trouble—mostly—but I’ve found an upside to it.

By making things myself, I appreciate how hard it is to do a good job of it. I also understand much better why things are the way they are. I Appreciate croissants a lot more after trying a couple of times to make them!

So with that preamble, I’ve been thinking about getting into cave diving, and a cave reel costs upwards of $300, which is quite a lot for something that looks a lot like something that you can get from Bunnings for under $10. So, this is a process of understanding where all that extra value gets generated.

The “finished” reel

This is where I ended up. There are a few tweaks to make, but I’m happy enough with this one to get stuck into some land drills with it. This is the process of getting here:

The evolution of the handle

I got three pieces of Delrin from Ali Express, all 100×100mm, one 20mm, and two 5mm. The plan was that the handle came from the 20mm piece, and the cheeks of the reel would come from the 5mm pieces. That set the thickness of the handle, an the max diameter of the cheeks.

The first handle, checking for hand size, was a polystyrene shape cut out on a hot wire cutter.

Fully assembled first prototype

The first one I made assumed that I needed to capture the cheek of the spool at both ends. That meant that I needed to make the spool really small to accommodate all the stuff at the top end, and still sit under the chin at the bottom.

I learnt a lot of things from this one though; the whole point of making prototypes!

Mainly that the spool could hang off the side of the handle. That meant that the spool could be the full 100mm of the Delrin sheet. The reason I’m so obsessed about making the most of the Delrin is that it’s really expensive. So that’s probably one of the reasons that the commercially available reels are so expensive.

The other things were details that are a lot easier to notice when the thing is in your hands, rather than rotating on a screen. I like being able to write on a print; treating it as a thing that can be gouged and written on makes it much more useful.

The other big thing is that you can’t really thread a bolt into a PLA print, so the final version has a lot of heat-set brass inserts in it.

I’m going to do some land drills with the reel, and see if anything else needs to be changed. If I like it, I’ll machine it out of Delrin, and then probably buy a commercially available one.

P.S.

Cave diving is obsessed with cookies, and one of my favourite cookies is the stroopwafel

P.P.S.

Ben Doherty Side Mount (BDSM)

16/02/2025 Some land based testing

Some line laid in Henson Park

I finally got a chance to test it out doing what it’s supposed to do. As a 3d printed jankey thing it’s not too bad at all! However, the ergonomics needs a bit of a tweak. My thumb got really tired while holding it, so I think it needs a wider area to rest my thumb. The Halcyon reels don’t have a hole at all, and I can see what they’re thinking (even if I don’t like it).

Dive Checklists

Sat, 27 Apr 2024 14:00:00 +0000

This is a constantly evolving list. It’s probably quite wrong, but it’s getting better. Ever since I read Checklist manifesto I’ve been into writing these kinds of reusable lists. If you’ve got suggestions, I’m into hearing them!

Lecture 2—Computational Design Theory 1—Architecture's Digital Turn

Thu, 24 Feb 2022 14:00:00 +0000

This is the first of this term’s lectures from CoDe 1110 - Computational Design Theory 1. It’s my take on how we got here as a broad survey of the origins of what we’ll be talking about for the rest of the term.

Below is a lightly edited transcript:

okay so we’re going to talk about this thing which people call architecture’s “digital turn” but I don’t think you can really get into that without a whole bunch of context.

I wanted to go back over the…

I had this in last week’s [lecture] and I thought that it would be good to keep asking this question; you keep asking this question of yourself. Why are you here what’s the point of being here? Are you just here to like please your parents or is this something that is of value to the world? So I just want you to keep asking that question and coming back to what’s the point of this? What’s the value in it? Whenever you kind of come up with some ideas on that let’s talk about it.

Really this kind of computing in architecture is a is a smaller part of “what is technology in architecture” and so the big question that surrounds everything is “what is a technology?

I think that the easy way to think about that is that if we split the world much like they did in the—I don’t know, 16th 17th century—into two things: everything that is art and everything that is nature. Art is anything made by people anything that is artifice or artificial, and so the world of art contains all of technology all of human endeavour in general. It’s difficult to kind of keep track of that because of this. The Arthur C Clark quote: “any sufficiently advanced technology is indistinguishable from magic”. This idea that if something works really well you have no idea how it works it just does the job and you think well maybe it’s magic. If you were to show an iPhone to an 1850s pilgrim they would probably burn you for being a witch but then we have a sort of similar problem. I don’t know if this is an official quote because I think I made it up. but I think I might have made it up after hearing it and then forgetting it. The idea that “any sufficiently traditional or well-known technology is indistinguishable from nature”.

People talk a lot about what is “natural”, particularly if you look at things like what American Conservatives consider to be natural that sort of stuff about the idea of wearing clothes or modesty or something like that. It’s important to remember that everything from poking a stick into an anthill, language, clothes, shoes, candles, maps, writing, all those sorts of things all of those are technologies; those essentially set us, as humans, apart from most of the rest of the animal kingdom. Let’s give that a second: if we’re looking at “technology” that could be a lot of things and so this lecture is a few separate ideas that we can then tie together at the end but it’s also kind of a history it’s just not a history that I’m going to tell in a single line it’s just a history I’m going to tell in a series of little examples. These are ideas that come up in a lot of the readings and so I thought I’d kind of have a go at a few.

The first one is “material computation”. The OG material computation was build something see if it falls down, see if it leaks, if it doesn’t you’ve computed that it works and you can keep going. Cathedrals would traditionally take up to like a thousand years to build. It’s not unusual for a cathedral to take over 500 years to build. So if you are saying a generation is roughly 20 years you’re talking like 25 generations of people who’ve passed this down from generation to generation as the thing that they do and it’s knowledge about whether you can build this insane flying buttress on Notre-Dame. These things would have just fallen down all the time until they figured out exactly how to build it and it didn’t fall down anymore. Then we get onto stuff like this—you’re going to see this project a lot over this the next three years—this is the Sagrada Familia in Barcelona by Gaudí.

Did anyone go to the talk the other day or watch the talk the other day who was talking about this hopefully it’s recorded somewhere and you can dig it out.

What he did was he was more actively computing these load paths. He’s interested in making these shapes be as efficient as possible, in terms of getting gravity to the load to pass through the structure into the ground. He realized that you could do this by turning the model upside down and using gravity to pull it into position and then turn the picture of the model back up again and build it. You can see this inverted model here the hanging chain model which then you flip over and you get the structure: the compression structure. He was using this to through gravity compute—in an analog way—the shape of the building that was going to come out of it. People say “oh well this is very natural”, “this is kind of unnatural” depending on how they think about it but the shape of that is dictated by the forces of nature in the sense that it’s a science concept and so you can see the diagrams of how this all pans out, because these weights are little weights on here are different weights and sometimes he has sheets in there to represent walls rather than buttresses, that kind of stuff.

Then you can come right up to much more modern stuff and this is an early [Frank] Gehry model for a Maggie’s Centre in Scotland, where he’s using the fact that this special thick paper that he uses doesn’t stretch at all so any shape that he can make with that he knows is going to be singly-curved and could be made out of relatively simple materials. Whereas if you used another model making technique you wouldn’t be able to guarantee that it could be built as easily. So people—particularly like The Simpsons—like to say that Gehry was just screwing up paper and seeing what happened, but he’s using the paper to produce some kind of approximation of a thing that’s buildable; he knows it’s buildable because the material won’t let him do other things.

That leads into this idea of you’ve got single-curvature; that’s a mathematical concept. There’s all these mathematical concepts in designing buildings and it starts with the Greeks—well it possibly starts in the Greeks it might have been earlier we just don’t know!

Temple design seems like a relatively simple thing. it’s just like a birthday cake with some sticks around it, but they were very sophisticated in the way that they understood optics and so if something looks if something is dead straight it will look like it bows when you look at it across the long distance so the whole of the temple was domed slightly, all of the columns rake in ever so slightly to correct for the fact that you’ve got this perspective thing going on, so by building this way it made everything look a little bit more magnificent when you were standing there. Which is kind of the idea that if Zeus is looking at your temple you want it to be the most magnificent temple to Zeus you can get otherwise he’ll transform into a swan and steal your wife or something like that. So it’s important to understand this stuff, and the way that they would bow those shapes in order to give you the impression that it’s actually a much more imposing building than it really is.

These mathematical concepts started to come into a more general understanding in the renaissance when people invented perspective drawing and the use of perspective drawing to be able to think through problems so it’s not just representing things that already exist it’s the idea that you can represent ideas and use perspective to get you there. Then the few hundred years after that, much in the same way that now if you make a really cool Grasshopper package you’re kind of a little celebrity for a bit, the tool and instrument makers were making these incredibly fancy devices. This is an “architectonic sector” which swings out and it gives you different perspective proportions. (I’ve actually got the book here if you want to have a look at some of those things.) These guys were basically the rock stars of their time as they created new tools they allowed new types of drawing and so there was an interaction; a discussion between the toolmaker and the drawer who wanted to do new and cooler things and we’ll see this discussion—this interaction between technology and imagination—coming up over and over again.

In the Carpo reading, does anyone remember that Olivetti adding machine that he was playing with? This idea that the machine gave up and couldn’t do it? We’ve been trying to put intelligence into machines for a really long time.

This is Talos who is one of Hephaestus’s creations. He created this giant robot full of ichor (which is god-blood, basically) that he would walk incredibly fast around this big island twice a day, and this is Jason and the Argonauts running away from him. One of the Argonauts, very cleverly, pulled the plug out of his heel and all his, essentially, hydraulic fluid fell out and he wasn’t able to defend the island anymore.

But the idea that machines could replicate things has been around for a super long time. This is a scene from R.U.R., Rosamond’s Universal Robots [1921] which was a play where the word “robot” first got used to describe this, because traditionally it was “rabot” which is the Slavic root word for worker.

So this is a “worker” this is an undressed Olivetti adding machine. Inside it we’ve got all these levers that are doing work. You press, like, eight times eight and it will go and end up with 64. There it is with its clothes on it’s quite an elegant little machine and so the idea that you can get computers to do things is interesting and it’s a relatively recent idea but the idea that machines could do intelligent things is very old and so the question of whether the machine is thinking is something that people still kind of fight over.

There was there was a fight last week over whether neural networks were conscious and one of the guys in London Murray Shanahan said that “[machine] neural networks are a little bit conscious in the same way that a field of wheat is a little bit pasta”.

So where did these things come from? This is Ada Lovelace who some of you might have come across. She often gets called the “first computer programmer” which is I think is an uncharitable way of describing her. She is the first theoretical computer scientist because she not only worked out the logic of how the machine works she also worked out the kind of philosophical implications of what you could do with that. She worked with Babbage, and Babbage designed this machine. He never actually built it never built a working version of the fully functional “difference engine” here which was rebuilt in the London science museum. There’s a close-up of it. What would happen is you would put in a calculation by setting the dials and then you turn the handle a bunch of times and then eventually an answer would pop out. If you really want to understand how these work there’s a bunch of really interesting videos. Just a little side note is these don’t work in binary. The idea that computers are all binary is actually quite a recent thing it was only settled really in the last 50 or 60 years. Before that there were computers that were running on five level logic, 10 level logic, that kind of thing. they just became a little bit unwieldy and difficult to use. So now when you think about ones and zeros they’re not actually ones and zeros they’re highs and lows in voltage so anything above three and a half is a one anything below about one is a zero and they just bounce up and down, and that ends up taking us all the way into Bletchley Park.

Which is a historical manor house in the English countryside, but it was also the place where Alan Turing and all of the code breakers on the British Intelligence were working. If you search for Bletchley Park, Google does this nice thing where it encodes the web page and then decodes it for you.

At this point, these women are “computers”. Until Turing comes up with the idea of the stuff we’re going to talk about in a second these women were what you would point to when you were saying “computer”. They had the job—in much the same way as the sort of hidden figures women in the in the movie—of doing basically the grunt work of doing the calculations. We don’t, or we might never, know the full extent of their contributions because they’ve been largely written out of history. If we see in this picture these two women operating one of the more advanced machines later in the war they were often very heavily involved in actually doing the computing and doing the logic and that kind of thing whereas they were written into the history as assistants or they just got cups of tea that kind of thing and so a lot of this is to do with how the history was recorded rather than the way that history actually was. The key thing that came out of this era was the work that Church and Turing did, kind of separately, on the idea of the Universal Turing Machine. Which is not a thing, this is an important concept, that the Turing machine is not a thing it’s an idea it’s a thought experiment: that given an infinite tape you could mix data and instructions on the tape and then it would decide what to do depending on what was presented to it. That was the key breakthrough in this idea of how computers were going to work. Around that time all kinds of interesting stuff was happening: [John] Von Neumann came up with Von Neumann Architecture which is how we understand computers to work now, they have storage, memory, processor, input and output, that together, basically, is the Von Neumann architecture. With a computing machine that was able to implement a Universal Turing Machine so you’ve got a hard drive or you’ve got a paper tape or whatever and it’s doing stuff and with that you can compute any computable concept which it may take almost infinite time. (This idea of almost infinite time is something we’ll probably get into next term if you do my programming course.)

Anyway so this takes us up into the 20th century. They were doing that in the 30s and 40s. After the war there was this great sense of enthusiasm the computers have kind of saved us, we were able to do stuff in the war because we had computers, and now what could we do with them afterwards? There were all these people who were optimistic about what we could do with computers and a lot of them were working on stuff, and I think Nicole will talk about this a bit in second year, she has a much more in-depth view into the work of Archigram and Cedric Price and those sorts of people, who were inspired by ideas of computers but not actually really using them or particularly understanding them.

We do get into the work of people like Christopher Alexander who is largely shunned in architecture because people don’t like being told what to do, but he is treated as something of a god in computer science because he came up with this concept of “patterns” and the idea of iterating on a pattern to make it better and then composing patterns into bigger things. This is some math, some data, and some beautiful diagrams from his book Notes on the Synthesis of Form. All of this stuff is in the lecture you’ll be able to look at that later. He’s talking about problem decomposition and how you can think about design from a logical perspective. But if we look at that page full of data, all the numbers, that’s very small data and so he’s talking about a kind of relationship set of problem types not actually data about the problem itself and these ideas are still very early on. You’ve also got people like Phil Steadman, who while we think of him as an OG person he’s still working, he’s still one of the most fearsome PhD supervisors you can get if you want to do an architectural computing PhD. (If you can get Phil Stedman you’ve done very well.) He was doing things like enumerating all of the possible rectangular layouts of plans and then trying to understand concepts like can you represent the arrangement of buildings through graphs? You can see if two building plans are similar because they have a similar graph representation. This room is connected to that room, which is connected to that room, which is connected to those two, and so actually we use this graph representation idea all the time for all kinds of things in the kind of nerd world. Most regular architect people don’t really know about it so it gets very interesting.

This is well William Gray Walter, he’s a robotics guy, he invented these two little Roomba things they’re kind of hard to see, but if you look them up they’re called Elmer and Elsie after two dancers of the era and they didn’t really do much. They just saw the light on the other one and followed it, but because they were quite slow at processing where they were, by the time the robot had moved towards it [the light], [the robot] was no longer there so they had this chaotic dance around each other. That’s actually docking itself, turns out Roombas do that now and Elmer and Elsie, possibly some of the first autonomous robots, were doing that too.

They were doing this little dance around and this kind of was one of the early pieces of the cybernetics world. The idea that systems interact in interesting ways and have time sequences to them. Cybernetics then moves into this idea of interactions between systems and the idea that systems talk to each other so a lot of people say that cybernetics is the study of conversations. If I’m interacting with a bicycle I know that I can’t just lean in one direction or I’ll fall off and I have to interact with the bicycle system, so me and the bicycle, two separate systems, become one system in a super-system, a larger system.

When do we get into some real computation in architecture?

One of the kind of claimants to the first architecture project that used any kind of computational system was Paul Coates and John Frazer when they were at the AA. They used a computational system, but not a computer because they were rich kids but they didn’t have the millions and millions of pounds needed to build a computer, so they were doing design projects based on the outputs of a random number generator, which was in their case a plastic roulette wheel, that they got basically in a cracker. Paul wrote one of the readings that you just read and John Fraser was head of school until very recently at QUT, so these people go on to do interesting things because they started off doing interesting things! A lot of these things end up being kind of silly and they’re kind of metaphorical computer uses and when you actually start getting into the meat of things, especially with the computers that were available at the time there’s not a lot you could do, so everyone had these grand aspirations of doing complete enumerations of all possible rectangles or automatic layouts, all that sort of stuff and actually you just can’t do that kind of thing generally at all, and less generally with the kind of compute power that they had on a DEC10 or a PDP or something like that in the late 70s and early 80s. So a lot of things that people actually came up with were really interesting low-compute systems that produced what we call “emergent behaviour”. This idea that by giving a set of very simple rules you can come up with a much more complex system by iterating it lots of times so Craig Reynolds came up with this system called Boyds, which is a New Jersey accent for birds, where they have a couple of rules. Steer to avoid: so you don’t crash into anything. Steer for cohesion: which is where you stay near the other things, and match your speed to your surroundings and so with those three rules (I think those are the three rules) you end up with the behaviour that you see in this [slide]. These incredible shapes that look just like birds flocking. When you look at a flock of starlings you can simulate that very similarly using very little code, less than a page of code, but huge amounts of compute power because it’s crunching through and every one of them is doing all sorts of vector calculations. (You should be able to program something very similar to that in not too long.)

The other one the other kind of classic finding was this beady ring idea that. There were certain fundamental urban design principles in older cities so a lot of the time they were looking at places in Yemen and things like that where they they’d find these structures that they could simulate on their not-very-good computers and so those end up being really interesting.

The thing that then comes out is that we have a lot of fairy tale fairy tale ideas about how an algorithm will work. A lot of that is to do with how we want it to work so when Richard Dawkins—in his period of being a biologist rather than a religious leader—got to doing these things which he called these Biomorphs. Genetic algorithms to produce these sorts of things. At this stage he’s selecting for “interestingness” so he’s saying “this is the best one”, “this is the most interesting one” but he’s tried to do trees that would grow upwards he was like how can I evolve the tallest tree and so the rule set he came up with was grow tall—that’s good—and don’t use too much material because too many sticks is bad right, and so after a few generations of running this tree design algorithm can anyone have a punt at what he ended up with? What what’s the tree that uses the least material and grows the tallest what shape is it?

It’s basically a straight stick! so the tallest and least material you can get is a telegraph pole, just go straight up and so Dawkins was completely surprised by this. [An] otherwise intelligent person understands the system but he had these romantic ideas about how the algorithm was going to work. You’re going to find this a lot when you start programming yourselves that you’re like “but it’s supposed to do that”, well where does it say that in the code? It doesn’t say that in the code and one of the things that this really teaches you, and has taught society in general is that the beliefs that you have don’t matter it’s what’s written on the page.

This is all very well and good, this is kind of theoretical it takes us into a bunch of interesting questions, but how is it going to pan out in architecture or in any real design field? This is a book I brought it with me it’s a great book, I think amazon has a print on demand copy but there’s no real copies in the world, I got it from a library that was throwing it out. It’s from ‘73 and they’re talking about all the cool things that you can do with computers in architecture, and at some point in a later section it’s like “oh and also maybe we can do graphics”. If we look at the table of contents, none of those are about drawing pictures they’re all about solving design problems and so in real building design there’s all there’s often going to be questions like how much outdoor space do I need as a ratio of indoor space? How many toilets is a ratio of the number of people? and once you’ve stacked enough of those ratios together they have they start to have quite complex interrelations so you can have so many people inside if it’s so big, but you also need to then have that much outside space, and you also have need to have that much parking, and those things end up being very difficult to solve all together and so a lot of the early work in computers “can we solve these real design problems?”, “can we simulate the environmental properties of this building?”, that kind of thing. The last line in that book is “the architectural profession as a body, has been slow to recognize the computer’s worth and has not yet fully realized the potential of this new tool.” If you were to go into a practice right now you would see a bunch of people just sitting around drawing pictures and not really “realizing the potential of this new tool” this is 50 years ago and not enough has happened! One of the interesting things is that all of you, as you come out of this course can change this and do something about this problem.

The problem really comes from this distinction: computer-aided design at the beginning was this idea that you could use a computer to help you design. That very quickly got changed to computer-aided drawing when people realized that they could sell computer programs to help you draw things much better than you could sell computer programs to help you change the way that you think, so that you can design better. The the key offender in this area is AutoDesk’s AutoCad. This [slide] is AutoCad two and a half. (I don’t know I don’t know why they have half versions in those days) but this was in DOS and they’re drawing, I don’t know, a region or something like that. The big selling point of AutoCad was that you didn’t have to change the way you thought you just “computerized” your existing process. The benefits of this were that you could just print out the same drawing over and over again, you didn’t have to take it through the ammonia copy room, and that you could make small edits to it. There was no help of “design”, no concept of design added into this. This was just drawing and that persisted unmolested until like, 2004-ish, the early 2000s.

Then we meet up with these people who have been doing a bunch of work in weird places like inside architectural firms there were a bunch of people working at SOM developing their own design tools there were people working shipyards there were people working at Foster and Partners, and they’d all come up with their own custom tools which were like Excel plugins and all that sort of stuff to end up with things that you could design. (I’m pretty sure that’s Achim standing there wearing his like traditional Achim Mengis outfit.) That ended up being a bit of software as it got published to the public called Generative Components, which for five or six years was the coolest thing you could get your hands on. You had to go to a workshop to be allowed to have a copy of this.

Each one of these nodes—have you started using grasshopper yet? Do you have your hand up?—each one of these nodes is similar to a Grasshopper node in that data is flowing in and then data is flowing out and then what data it is, is over here. That gives you all of these sorts of things. It was a bit crusty and it crashed a lot but it sort of paved the way for this idea that you could create design tools as a normal person you didn’t have to be a software developer to make that work. Then around that time we went through this kind of terrible time which I’m going to call the Deluze patch where the theory wankers—don’t write that down—the people who, similar to the people in the 70s who were doing stuff inspired by the idea of computers, were writing a load of stuff inspired by the ideas of what was possible with computers but the problem we had, and this is this is conjecture, is that those people in the 70s who were doing this stuff with the metaphorical idea of computers were working with an entirely new idea that you couldn’t go out and test but they were designing as if they were doing speculative projects, whereas the writers were largely either doing speculative writing and no projects or they were doing projects that weren’t very difficult and then writing about them in a way that made them sound difficult. That’s the kind of open question that I want you to kind of think about when you’re reading these things because some of the readings are written by people who are kind of hardcore and did things and were doing interesting stuff and some of them were written by people who just kind of needed to write to live.

The next thing that came along after generative components was Grasshopper. Grasshopper’s early name was Explicit History which now is the name of something else in Rhino, but Explicit History was actually a really nice name because the whole point of it was that it captured your design process and so the process required to make that towery thing is captured by the Grasshopper connection graph on the left. Which means that at some point you can go along and you can change the decisions you made. You’re like “oh I want to have seven sides not six” and then it can all play forwards. It doesn’t strictly capture the design thinking because it doesn’t have a history of that, whereas generative components did, but that was the main thing that caused Generative Components to crash so I think that’s why they took it out. Now we’ve got this kind of platform which allows people to build plug-ins on top of it and the platformization of Grasshopper has been the thing that’s made it so successful.

The big question now is what’s next, because I think that we’ve got to the point now where geometry creation, geometry manipulation, all that sort of stuff is pretty well understood and we’ve got this idea of most of the fancy stuff is up here, we’re dealing with one-off towers, pavilions, all that sort of stuff is in this zone here. Then down here you’ve got really basic stuff like putting an extension on someone’s house or putting a porch door on that kind of thing. In terms of the work there’s this chunky middle section, it’s what people have called the “fat middle” of really quite straightforward design tasks. Like “how do I lay out a car park?”, “how would I put this building in if it was pretty simple building?” and these tools like Giraffe or Test Fit have actually come an incredibly long way in not very long at all and I think we’re going to see a lot more a lot more work done along these lines which are “how do I design essentially generic boring stuff and make a tremendous profit from it because I can just crank through this and see which of 500 options gives me the most profit”.

That’s the kind of like one end of the boring scale and that gives you a lot to play with it lets legislators understand what the implications of their laws are it lets developers understand what’s going on it lets the people understand the implications of a developer doing something and so some of the work that Hank is doing with Giraffe is partially about generating things but it’s also partially about allowing the public to interact with proposals to say well this doesn’t look so good like this, or from my house perspective I get shaded at this time. The other thing that I think we’re going to see a lot more of is in the feminist literature around domestic spaces they write a lot about how the introduction of white goods like washing machines and tumble dryers and that kind of thing didn’t give people way more time it just meant that people had much higher standards of cleanliness. Nicole talks a lot about this; she’s done a lot of work on it. As computer tools get better and better we don’t tend to just do the same project faster, we tend to do more work. Partially because architects have some sort of pathological desire to never see their children, and partially because clients demand it.

One of the things we’re going to see a lot more of is simulation of the performance of a building. We already do a lot of solar performance analysis, like “does this apartment get enough sun?” that kind of thing but we’re going to start to see human occupation analysis. One of my like hobby horse topics is that you can get the highest award in New South Wales architecture [the Sulman Medal] without the building ever having been occupied. The idea that you can get an award for a really great building that no one’s ever been in seems horrifying to me. The idea for me would be that in the future we want to see buildings getting awards five or ten years after they’re built for being really great buildings to live in. You don’t give films an Oscar because you like the poster, you give a film an Oscar because you watched it and you thought it was good. Hopefully we’ll see a bit more of that and you can simulate the people moving around it and say “oh well these people can’t get from here to here in time to escape because of fires” or “people seem to bunch around here that’s no good” or “people feel sad here because there’s not enough light” and whatever you can imagine at some point we’re going to be able to simulate that.

Then the third thing I think is going to be a big deal is a much longer ongoing interaction with buildings. This [slide] is from Estimote’s new Space Time OS. It’s so new, it’s like a month old I think, but the idea is that as you track assets around the building, those assets could be furniture they could be people, you can understand how the building works in real time and change it. There’s lots of things you can do with that!

There’s a bunch of references there, they’re unreadably small but you can download it and have a look at it.

That’s about it for this lecture, that’s a kind of potted history of a very odd angle on architectural computing. The angles in the readings that you did last week took completely different views on that and so I think would be some very interesting ways of thinking about how those different views come together to create a kind of super-view in your minds because you can discount or you can encourage different parts of those views to work together.

Updated: A Game About Possible Futures - how to play

Fri, 01 Jan 2021 09:00:00 +0000

Possible Futures

It’s difficult to sit down and think about the future. It’s tempting to think about the present, but blue and shiny[^construal]. Or to think about the issue that’s important and in the news today, and have much more or much less of it. You need a framework!

This is a game that helps its players think about the future. It gives players specific things to think about, and by thinking about the interactions between those things, gives a different way of thinking. It’s not any more “correct”, but it breaks through the barrier of simplistic utopias or dystopias, and pushes the ideas into the messy, soupy middle.

Have fun with this, and let your imagination loose. If there’s anything we’ve learned from the recent past, it’s that That could never happen means that it’s almost guaranteed to happen.

How to play

Get into teams; teams of 3 seem to work pretty well. If the team is too small it’s hard to get enough ideas bouncing around, if it’s too big, not everyone’s option gets heard.

Print out the cards. In total you need about 10 per team, there are 106 cards now, so you can work that out. If you want to just get the cards as a PDF then they’re here, but if you want the freshest ones, they’re here for you to print yourself.

If you’ve got a particular focus or reason for running this workshop, then it’s probably ok to make a fixed card that is always in each team’s hand. E.g. if you really care about smart cities, make a card (or cards) about that, and make sure that each team always has one of them.

Extra to the teams, someone needs to be the MC/time keeper. It helps to have a few other people going around to get the teams to think a bit differently if they get stuck in a rut.

Early rounds

This is all about getting warmed up. You can play through this stage for as long as you like until you feel like everyone’s “got it”.

I’d recommend playing 3 rounds, the first with 1 card, the second with 2, and the third with 3 cards.

For these first rounds, keep them quick, 10 minutes or so. You should keep these following prompts in mind, but not be too diligent about doing them all. Save the diligence for the last round.

Each team picks N card[s], at random. The job then is to bat ideas around between the team members. Most of the cards don’t explicitly give an outcome, more like an idea or a trend, so it’s the team’s job to think about the bounds of that trend. E.g. will all the bees die, or will we do something magical and get bee populations to their highest ever level?
If you’ve got more than one card, think about each one individually, and then think about their interactions. Do they amplify each other (IoT trackers glued to bees?) or cancel out (a fashion for owning bee eating lizards?).
If you’ve heard of the five whys, this is the five and then whats. Think of an effect:
1. get started
  - not many bees
2. and then what?
  - so not as many people get stung as kids
3. and then what?
  - so more people get stung for the first time as an adult
4. and then what?
  - so more people die from anaphylaxis without any warning
5. and then what?
  - so people are more afraid of bees
6. and then what?
  - so people go out of their way to kill bees when they see them.
This might not be scientifically supportable, but you can get to some pretty interesting and unintuitive results from it.
Once you’ve got a pretty good grasp on how the ideas interact, take some time to think about them from different perspectives.
- How does it affect the economy? What about under different forms of government? How would they deal with it in the USA, in France, in China, in North Korea?
- How will it change what we eat?
- How will it change what we buy?
- How will it change family structures?
- How will it change our free time?
- How will it change what we think about as we live our lives?
- How will it change what society values?
Invent a protagonist.
- What do they do?
- How is their life different to yours?
- How is it the same?
Capture it! Write notes, do sketches, take photos of your team acting out scenarios. The idea is to have a record of your thoughts so that if you wanted, you could go back and write a speculative fiction short story about your world.
Put all your cards to one side, and take N+1 new cards. Start again, but with more insight and enthusiasm now that you’re getting more warmed up.

Final round

Each team keeps one card from their last round (so throw away 2 of the three for example).

Play through the same as before, but take the luxury of more time. Make your notes a bit more detailed and your sketches more detailed/atmospheric. Once you’re about 10–15 minutes in we can start to stress test the ideas.

Pair up teams, and present the future to the other team. Their job is to stress test the future. To be clear, it’s not to find a knock down argument that destroys the delicate fiction that you’re assembling! It’s to ask questions that they think that you haven’t thought of, and to ask for clarification. If you’re a dick in your questioning, nobody wins, so help build your partner team’s world.

Once the teams have reciprocated, swap again. Have a little break between swaps to consolidate your team’s thoughts, and then go refreshed into the stress test.

Take a bit more time to weave all these ideas into a story, and then tell everyone about that world.

Tips

It’s very tempting to think of blissful utopias or of hellish dystopian worlds, but there is good, even joy, in all worlds, and bad in them too.

Try to avoid extremes in your worlds, it’ll feel much more real if it’s nuanced. Balance is a much better place to make a jump from.
Make way more notes than you think you need. At the time everything seems impossibly vibrant, but as the blinding light of the next idea comes along, it’ll bulldoze the preceding ideas out of its path.
Grab quotes from others in your team, they’re really usable in future bits of work you’ll do.

The canvas

Fill in the canvas. Its job is to make all the ideas visible, so that you can start to probe them for inconsistencies. Start using post it notes, so that you can change things, a lot.

Canvas

If you’ve got a big printer, print this as A3 or even better A2

High res download

Or just work through these prompts on whatever paper you’ve got:

Imagine an object used in this world
What would a convenience store be like (or the nearest thing to one)?
What’s child rearing like?
What are the last 10 years of a person’s life like in this world
draw up a timeline of your protagonist’s day, who do they interact with, what technology do they interact with?
How will this scenario
- affect the economy?
- change what we eat?
- change what we buy?
- change family structures?
- change our free time?
- change what we think about as we live our lives?
- change what society values?
How would it play out under different forms of government? How would they deal with it in the USA, in France, in China, in North Korea?

Contributing

There are two main ways to contribute:

Improving cards

These cards are made by me, who is an expert in none of these topics. If you are an expert then you probably have way more useful things to say! Better illustrations, better prompts, better footnotes, and so on.

You can improve them by going to GitHub and just editing the card you’re interested in. Don’t worry about breaking it, your edit will be sent to me for approval first.

If you’d like to do an easy one, the following cards have been stubbed out but not finished:

Autonomous technology
Blockchain
Citizen science
Consumer ML/AI
Crypto currencies
Echo chambers
Fake news
Gaming as socialising/e-sport/entertainment
Influencers
Lidar
Military robots
Millionaire YouTube kids
Mushroom mania
No-melody music
Online shopping and the redefinition of physical retail
Pandemics
Personal trillionaires
Post truth
Predictive healthcare
“Progressive” social policy dominance
Religious extremism
Remote work for all
Van life
Post-capitalism
r/WSB STONKS
The Circular Economy
The Metaverse

Making new cards

Cards are defined using a YAML format that looks like this:

live: false
title: The name of the card
image:
    source: usefulPicture.jpg
    caption: This is an image of an xxx
    citation: a graph by by YYY
    link: https://www.google.com/
body:
    paragraphs:
        - The first paragraph.
        - Another one.
        - one more just for luck[^luck].
footnotes:
    luck: "I'm not sure luck really exists: [luck](en.wikipedia.org/wiki/luck)"
consider:
    - add a prompt for the players
    - And maybe another one too
card_type: future_tech
meta:
    sources:
        - source_comment: Who wrote this card? Who are you?
          source_link: If you pulled it from somewhere else, ref that here
          update_date: 2021-02-20 #an iso date
        - source_comment: Who updated this card? Who are you?
          source_link: #leave it blank if you like
          update_date: 2021-02-20 #an iso date

Save the file as The name of the card.yaml and either 💌email it to me, or make PR against the repo. (I’d go with email for the moment, until this game gets it’s own repo; my blog is a huge download.)

The current cards are:

5G/𝒩G
AGI fast take off
AI Bias
AI creativity
Advert free internet
Amazon Nations
Architectural team size
Audio AR
Battery density
Bee population crash
Betting markets
Big data analysis
Breakdown of traditional education paths
Broadband access inequality
Carbon labelling for consumer goods
Cashless biometric payments
Centralisation of web companies
China power shift
Climate migration
Compute power
Concentration of functions into smart phones
“Conservative” policy dominance
Cost of domestic property
Cost of space travel
Cottagecore and Waldenponding
Coworking and Cohousing
Crime/violence
Dark kitchens
Death of music genres
Digital commutes and forced mindfulness
Discovery of extra-terrestrial beings
Drone delivery
Drones
Economic crash
End of the open-plan office
Escape into fantasy worlds
Facial recognition
Full-filter reality
GDP
Genetic medicine
Global temperature
Horse population
Indoor plant farming
Internet coverage
Lab meat
Legalisation of drugs
Live shopping
Psychedelia
Micromobility
Non-sovereign currencies
Population growth rate
Private internet
Asteroid mining
Quantum computers
Radical life extension
Return of the face lift
Rewilding
Screens
Self driving cars
Single use plastic ban
Smart homes & internet of things
Tech platform exit
The gig economy
TikTok/K-pop activism
Ubiquitous broadband
Universal basic income (UBI)
Universal work from home policies
Urbanisation
Virtual reality
Walking robots
Wearable/implantable technology
Working hours
XYZ as a service
Zoom fashion
life expectancy
Design for Manufacture and Assembly (DfMA)
Mass Timber Construction
Private space exploration and asteroid mining
Smart homes & internet of things

Updated: A Game About Possible Futures - the cards

Fri, 01 Jan 2021 09:00:00 +0000

5G/𝒩G

Wildly optimistic speeds, but in the rough orders of magnitude. Do Yourself A Favour – Don’t Get A 5G Phone Just Yet

Each increase in G increases connectivity speed, and changes the types of things that you can do while connected to that network. 3G allowed full webpages rather than just WAP¹.

5G untethers broadband speeds from the geographical constraints of fibre optic or copper networks. Once there’s a 5G network in place, high tech applications can be set up with no digging, it also allows for easy reconfiguration of data rich robotics in warehouses.

Conspiracy theorists think it’s a mind control mechanism.

Consider

In the 2030s 6G will bring even faster connections, what will that allow
If you don’t need to re-cable, what will this mean for factories? For offices?

AGI fast take off

Specific—or weak—AI is useful for things like image recognition, or playing chess. Artificial General Intelligence (AGI) is different because it can solve general problems.

One of the problems that it is likely to want to solve is making itself more capable. In an AGI fast take off scenario, the AI will put all its effort into improving its ability. It may well start at dog level intelligence, and maybe over the next week or two it’ll get to chimp level intelligence. Within another day or so it’ll get to a stupid human, and within a minute or two will have become far smarter than the most intelligent human ever to live.

This card gives you the choice of whether you want to assume that the AGI will try to kill us all, or if it’ll think of itself as a loving parent to us.

Consider

Who “owns” a greater-than-human intelligence?
Is it unethical to turn it off?
What impacts would AI/AGI have on a future city or workforce?
What if the AI’s motivations don’t align with ours? It’s much smarter than us, should we treat it as a god?

AI Bias

The PULSE algorithm takes pixelated faces and turns them into high-resolution images. However, it has a strong bias towards white faces. ∴ Obama -> white guy. The Verge

Bias can be built into algorithms in several ways. The obvious one is through the datasets used to train the system. If a dataset has only cats, it will classify a dog as a cat. It can also be introduced through the hyperparameters (the setup variables of the system).

Propublica² showed widespread bias in sentencing based on an algorithm that baked in, amongst other things, geographical biases, e.g. if you live in a black neighbourhood, sentence more harshly.

Many ML algorithms are considered “black boxes” so can’t be explained. There is a lot of work on trying to make that not the case.

Consider

Whose responsibility is it to make sure that algorithms don’t discriminate against particular groups of people?
Is there an acceptable rate of failure? What is that relative to the human rate of failure?

AI creativity

Artificial intelligence: Google’s AlphaGo beats Go master Lee Se-dol Published12 March 2016 BBC

Algorithms like alpha go have been displaying signs of non-human creativity, i.e. they’re doing things that their creators think are beyond the scope of their training.

Other algorithms, like style transfer GANs, look creative, but are quite predictable. However they produce art-like outcomes which—it could be argued—is what most “creative” human “artists” do.

Consider

What is creativity? Can it be defined in a way that doesn’t involve humans?
Can a machine think? If you take a pragmatist view, does that matter?

The dominant business model of the internet is making a service that people use, and then serving adverts to those people while they’re there. If you could opt out of those adverts there would need to be some other kind of value transfer to make the service worth running.

Each time an ad is served (an impression), it costs the advertiser a tiny amount of money, more if it’s clicked. These sums would be dwarfed by transaction fees as an impression is in the order of $0.012 per impression and a transaction fee is somewhere between $0.03 and $0.30. So the payments would need to be aggregated by another party before being passed to the banks.

Companies like Blendle³

Consider

Would you pay money to avoid adverts?
Adverts make you aware of products and services that potentially make your life better. Would you suffer without them?
How would graphic design trends change if there was less to put on the page?
If the wealthy paid not to see ads, would ads change? Wealthy customers are worth more to advertise to, would people need to pay a % of their wealth to avoid adverts?

Audio AR

zombies, run!

Most Augmented Reality (AR) is thought of as visual, but there are significant technical hurdles in image processing and rendering to overcome before it has widespread adoption. Audio AR is already available; if you use google maps’ walking directions through your headphones without looking at your phone then you’ve already tried it. (Many sports apps use audio cues to prompt performance too.)

For it to be audio, only the output needs to be audio, the input can be anything, GPS, accelerometers, microphones, even cameras.

"Hey Siri, who’s that guy over there? Do I know him?"

See the Ender’s Game series for an audio AR, AI character.

Consider

if you have an audio assistant that’s able to understand the world, what would they need to be able to do for you to make it worthwhile?
Historical characters like Jiminy Cricket or the angel and demon on your shoulders are prototypes for audio AR. What sorts of things could this system help you with?
would it all be voice prompts? How else could you sonify the interaction?

Battery density

battery statistics battery university

The ability to store energy and then release it later has been a constant human obsession. Mill ponds are there to turn water wheels when it isn’t raining and clocks run on weights and springs that release their energy slowly.

Chemical batteries make that energy portable in a way that was previously inconceivable⁷.

Tesla’s PowerWall batteries allow solar power to be used at night, and the same batteries that are inside the power wall are used in cars. These allow the power providers to load balance/peak shave so that they don’t need to turn on more power stations to handle peak loads.

Consider

Peak loads cost power suppliers a lot of money, who else stands to gain from batteries apart from consumers?
Will consumers prefer ever thinner phones or longer battery lives. What would life be like if you only charged a phone once a month?
Will the distribution of metals that make up batteries change global trade/power?

Bee population crash

Bee populations are declining.

In recent winters, in Europe alone, bee losses up to 53% became a reality.

Plants rely on insects like bees to reproduce. Plant reproduction is vital for our food supply. If the bees die, then we die too!

This dramatic decline in bee populations is the result of multiple factors such as diseases and parasites, climate change and wider industrial agricultural practices.

Consider

What would we need to do to support bee populations?
Could we come up with a technology solution to replace bees? What would the risks be?

Big data analysis

Big data analytics is the process of examining large data sets containing a variety of data types.

BIG DATA: to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits.⁹

The goal of analysis is for companies to make more informed decisions. They could use Web server logs and Internet clickstream data, social media content and social network activity reports, text from customer emails and survey responses, mobile-phone call detail records and machine data captured by sensors connected to the Internet of Things.

Consider

How could this scale of information and its availability influence not just business but also society?
Are there negatives to a society driven by ‘big data’ metrics?

Cashless biometric payments

Since NFC payments—tap and go—became the norm, it has become increasingly unusual to actually make contact when you pay (i.e. insert or swipe). As this capacity has moved to phones people carry their wallets even less.

You know how iPhone’s Face ID can trigger Apple Pay’s contactless payments? Now imagine¹⁶ this technology being available in many retail settings, and in various implementations outside of the Apple ecosystem.

Consider

If you don’t need your wallet to pay now because it’s on your phone, then if you don’t need anything, will people leave the house without their phones? Or is there too much other value wrapped up in the phone to let it go?
This will need some very broad scale facial/fingerprint/iris recognition, will society value convenience over privacy again, or will this be the step too far?

Centralisation of web companies

Amazon is now bigger than Walmart Quartz

Amazon is now bigger than Walmart. The internet allows companies to centralise services. This is a long running trend; in 1850 your village would have a singer and someone who played an instrument for entertainment, but with the introduction of music recording the wealth from entertainment was concentrated into the very best entertainers. The same is happening to education and news providers.

This has also enabled the “long tail”, catering to ever more specific groups of people, but the bulk of everyone’s needs can be fulfilled by Amazon.

With increasing globalisation, more and more services will be provided by a centralised organisation, even if that organisation is coordinating others (e.g. Uber and AirBnB).

Consider

Companies like Amazon and Ebay provide marketplace services to smaller companies; connecting them to consumers. What are the impacts of this?
Do we have all our eggs in one basket?
Do we (consumers) stand to gain from an arms race?
Politicians talk about “breaking up big tech”. What effect would this have?

Compute power

The number of transistors on a microchip has doubled every 18 months or so since transistors were invented. This was first spotted by Gordon Moore, and the phenomenon is named after him: Moore’s Law²⁰. More transistors means more calculations can be done in a given time. That means that computers can do more of what we want, feel smoother and more responsive.

Not only is each computer more powerful, but there are also more computers in the world. We all have computers in our pockets. There are giant data centres anywhere that a source of electricity or cooling can be found²¹. Put simply, there is a massive amount of raw computing power in the world, and the rate of its increase is increasing²².

Consider

Does more power unlock answers to new kinds of problem? Google search wouldn’t be possible without a certain level of computer power. What new kinds of activity will be unlocked by more power?
More compute power needs more electrical power. Where will this electricity come from?
Does everyone have equal access to this compute power?
Will we ever have enough computer power?

Concentration of functions into smart phones

Since smart phones emerged by merging personal digital assistants (PDAs) and telephones, they’ve been capturing more functions. Now films and documentaries regularly contain smartphone footage. You can pay with your phone, and keep your driving licence, so they’ve usurped wallets. Most online shopping is done on a phone. They are all round music players and controllers for our smart homes.

Consider

What else could end up on a phone?
Is this concentration causing a single point of failure? If your phone goes flat away from home are you totally powerless? (No pun intended)
Does it even make sense to call it a phone any more?
What other form factors could it take? What’s stopping this?

Cost of domestic property

²³

Housing is more expensive (in real terms) than ever. As a proportion of the money that people have to spend, we are spending more of it on housing.

This might be because there isn’t enough supply of housing where people want to live. It might be because housing is a safe asset class.

Low interest rates make it easier for those with wealth to buy more houses, and house values go up much faster than most other asset classes. Are we in a bubble?

If owning stops being attractive, wealth concentration will increase, but maybe a new safe as x asset class will emerge for renters to spend their money on.

Consider

How did we get to the position that we’re in now?
What other explanations could there be for these trends that aren’t the obvious ones?
What would reduce the pressure on the market?
Is expensive housing desirable?
Is the current model of how we live going to survive the rise in price?

Cost of space travel

The average cost of traditional launch methods is about $25,000/kg²⁴ but the SpaceX Falcon 9 can get that down to $2,618/kg. The Falcon Heavy is expected to be able to launch 53,000 kg to Low Earth Orbit for $90 Million or US$2,350 per kg to LEO²⁵^/²⁶.

With fully reusable launch vehicles the cost of a launch will drop to almost the cost of the fuel. As rockets are fuelled with hydrogen and oxygen, this can be made in bulk by electrolysing water, potentially with solar power. Expect the cost to launch to continue to drop.

Consider

What other mechanisms might we use to get things into space?
What will the price drop in space travel mean for society?
What limits the drop in cost of space travel?

Crime/violence

Australia is blue²⁸, USA is red.²⁹

Generally, crime and violence seems to be declining overall³⁰ ³¹. This may be because of better policing, or more surveillance. It could just be that we are generally richer, and therefore we feel less compelled to risk committing crimes to obtain what we don’t have.

Consider

How much crime went unreported in the past? Has this amount increased or decreased?
Has the Overton window moved to include new acts within the definition of violence?
Are we less violent because we have ‘advanced’ as a society, or because we are more afraid of getting caught?

Dark kitchens

Dark kitchens create meals exclusively for the online delivery market³². In the early pandemic many regular restaurants went dark only.

Dark kitchens have lower overheads, and can share a premises more easily, but they are at the whim of the delivery service for speed of delivery and the whim of the customer for presentation. This means that there will often be a significant overhead in packaging that can offset the savings from rent on the dining room.

Consider

How much of eating out is about the convenience of not having to cook? Wash up?
This increases demand for chefs, but decreases demand for waiting staff, what will those people do?
Eating out is often a safe space for first dates, if the restaurant industry collapsed (or the low-mid price range did) what would that do to dating?

Discovery of extra-terrestrial beings

You have one of the lucky-longshot cards!

There’s a lot of scope with this card.

Consider

What would it mean to encounter an extra-terrestrial life form?
Would it be sentient? Would it just be bacterial?
Would it be friendly, aggressive, or maybe even just unconcerned about humans and other earth life?
Would they give us new technology?
Are there other ways to be alive? Think about slime moulds, trees, bees, the earth computer from Hitchhiker’s Guide…

Drone delivery

On the surface, drone delivery is about pandering to rich people’s whims. “I want a [insert thing here] now! Minimalism has been described as a thing that only the rich can afford—everyone else needs to have backups!³⁵ That could change if drone delivery takes off in a big way. You needn’t actually own anything because it could be delivered to you within a few minutes.

The resources needed for everyone to own a ukulele could be put into making a few really good ones with energy left over to make other things.

Drones could also be used to deliver medicine and other essentials to places that don’t have fixed infrastructure like roads or power for refrigeration. E.g. taking a shepherd’s insulin to her on the side of a hill.

Consider

How many of your belongings could you live without if just-in-time delivery was possible?
Can medical assistance be ‘delivered’?
What things of yours would and wouldn’t you share if a drone would pick it up and drop it off for you?
What other infrastructure does this make obsolete?
Could deliveries be made to apartment windows on high levels? How would the window need to change?

Drones

Let’s define drones as a class of robots that are able to do a human’s bidding with some level of autonomy. That might just be the ability to hover level, or it might be full autonomy over an assassination mission.

There are drones deployed in military situations, drones do the vacuuming, drones do aerial filming. The list of things that drones can do is only limited by how far we can imagine at the moment.

Most drones only have limited autonomy, but that is changing in military applications and will change in commercial and domestic ones too.

We can send drones to dangerous or inaccessible places. Wriggling into pipes to look for leaks, or flying over cliffs to count sea birds.

Drones were used to attack the Saudi Aramco oil refinery; this was consumer tech, used in a military context.

Consider

What if drones get so small that we can’t see them?
Could warfare become entirely autonomous?
What new types of jobs or applications might emerge for drones?
Will drones displace a significant part of the labour force?

Escape into fantasy worlds

Perhaps unsurprisingly, global uncertainty has led to a boom in escapism³⁷, and all signs point to this continuing strongly into the next decade. Fantasy can and will take various forms, including long-form immersive gaming experiences, ketamine’s recreational popularity and new acceptance as a clinical treatment, and increasing commercial emphasis on the worlds of young adult literature and its spin offs across media.

There has been an increase in people shutting themselves away, in Japanese, Hikikomori³⁸, but at the same time the traditionally reclusive activity of gaming has become increasingly social, with streaming and multiplayer worlds.

Consider

Virtual worlds could easily get interesting and immersive enough that people wouldn’t want to go out into the world. Is that a bad thing?
What would you need to inject into virtual words to keep their inhabitants function members of the outside society? Is that necessary?
Virtual worlds don’t need to be geographically bounded; would it ultimately break down the nation state?
what things need to be done in the real world?

Facial recognition

Computers can now recognise faces almost as well as humans can. They are more susceptible to tricks like face paint or sunglasses than we are, but that’s probably not going to take long to solve.

Strong facial recognition will mean that security agencies can track you wherever you appear on a CCTV feed. It means that advertisers can personalise billboards to your particular buying habits.

Consider

How might these ideas of surveillance influence other systems to become more intuitive?
Will fashion embrace it or resist facial recognition³⁹?
What, other than faces, can be “recognised”?
Will the bans on facial recognition get more severe, or will they be lifted? Is there a middle ground?

Full-filter reality

Immersive, photo realistic imagery in the form of Instagram-style filter layers will become widespread beyond just phones when applied via increasingly mature augmented reality systems⁴⁰, forcing people to question the relationship between the visual and the real, and potentially fragmenting consensus reality even further.

Consider

GDP

⁴¹

A lot of countries are getting richer. A few are getting poorer. A big slab of countries are staying the same.

Also, wealth distribution inside countries is changing.

Consider

What causes there to be three groups?
What do the countries in the three groups have in common? What do UAE, Brunei and Libya have in common?
What leverage are the countries that are getting richer able to use that the countries that are static don’t have access to?
Is GDP even a useful measure? What would the world be like if we measured something else, or a range of things?

Genetic medicine

Medicine has developed to a point where it is incredibly good at treating an imaginary, statistically normal person. Each variable that could be part of your health has a statistical range that is ‘normal’, perhaps subdivided by age, or sex, or race if you are lucky.

Genetic medicine is focused on treating each patient as an individual⁴². Those ranges would be hugely more specific. Based on your genetic markers you may need to keep your potassium levels between X1 and X2. This leads to much more preventative medicine being possible. This ultimately reduces the spending needed to achieve a given level of health and also makes it possible to increase general health for everyone.

All that statistical specificity unlocks a dystopian side. Health insurers can make much more accurate predictions about the true cost of insuring a person. This means that people at risk of the worst diseases will also find it the hardest to get health insurance.

Consider

Will this make us healthier?
Will we choose mates who are genetically different to us, or to try to reduce the likelihood of complications?
Will it lead to people being denied healthcare/insurance?

Global temperature

This graph from NASA⁴³ shows global temperature variation

“The paleoclimate record combined with global models shows past ice ages as well as periods even warmer than today. But the paleoclimate record also reveals that the current climatic warming is occurring much more rapidly than past warming events.”

Future temperature rises differ by the model used to predict them[^34] and by the way we act in the future[^35]. These will lead to sea level rise. Partially from melting ice, but also from the water in the oceans getting bigger from thermal expansion.

Consider

Who will warming be bad for?
Who will it be good for?
What will temperature increases trigger? And then what will those things trigger? and what will those things trigger? And so on.

Horse population

The Horsepower was a measure of the work that one horse could do. The horse was the engine of most economies until the internal combustion engine displaced it. This was one of the first real examples of large scale disruption⁴⁴.

Horses were no longer a requirement, and people quickly moved over to engines to provide motive force. Horses stayed for recreational use, but in tiny numbers compared to their previous penetration.

This is interesting, but it’s also a metaphor for a change from one entrenched technology to another. The disruption to the world can be huge.

Consider

Why did people prefer engines to horses?
What was the core function that the horse performed?
If you think of this as a pattern, what might replace the car?
What other historical technological revolutions fit the same pattern? What current technologies are vulnerable to it?

Indoor plant farming

Plants are green because they reflect the green part of the visual light spectrum; it turns out that plants need mainly pink light to photosynthesise. 1m of solar panels can generate more than 1m of pink light, so it’s very resource efficient.

The plants are grown in racks, in a sealed warehouse. Each rack has lighting and a water supply with nutrients in it. Because the building is sealed, there’s no need for pesticides because there are no pests. Because the plants are in racks, each square metre on the floor can produce tens of square metres of plants.

Consider

If we do this, what will happen to the farming industry?
What would happen to all the land that is currently used to grow plants?
Not all plants can be grown like this. Plants that are tall are particularly unsuited, e.g. fruit and corn. How will our diets shift to reflect the price differences?

Lab meat

Ruminants, like cows and sheep, emit a lot of greenhouse gasses. They are also sentient beings. Those are two pretty compelling reasons not to eat them. However, meat is a dense source of calories, protein and vitamins. If we can culture meat in a lab, then we can have all the upsides without any of the downsides.

Consider

Will we start to design meats that aren’t copies of animals?
Will lab meat ever overcome the yuk factor?
What will happen to the meat industry? What about the animals that are already alive?
What will we do with all the spare land that is freed up?

Psychedelia

Shrooms are the new weed, commercially speaking, as new firms and funds scramble to monetize⁵¹ psilocybin in advance of its extended clinical applications. Psychedelics as a class of drugs continue to be destigmatized, relative to other drugs. Forecasts see this reaching a new level of mainstream saturation in coming years.

Consider

Population growth rate

⁵⁵

The world population is growing by 200,000 daily. Population increases are expected to level out globally between 2030 and 2100⁵⁶, but that’s an aggregate value. Some countries will still be growing fast whilst others will be shrinking (looking at you Japan).

There are a lot of factors to population growth. Better sanitation means fewer children die. Better access to education for women means that fewer children are born. People living longer means that people hang about for longer. Wars push people out of countries, prosperity pulls them in.

Consider

What job will all these new people do?
What will they eat?
Where will they live?
What factors will drive migration?
What limiting factors are there on Australian population growth? What could we do to remove those limitations?

Quantum computers

Quantum computers are able to solve a particular type of problem incredibly fast. Unfortunately, that particular type of problem is the one that the world’s encryption systems are based on.

Quantum computers are currently a research curiosity, if they become a real world technology then all internet transactions will fail. (Unless credit card companies and banks take action before then to upgrade to quantum encryption.)

From a more optimistic angle, once computer scientists work out how to phrase their problems in the way that quantum computers like, lots of

very hard problems become quite easy!

Consider

How much disruption would it cause if electronic money, and other encryption methods, stopped working?
If protein folding was solved, what would it mean for the pharma industry?

Radical life extension

The first children to get to 150 years old have already been born. Radical life extension advocates think that it’s possible to push that number much higher.

Technically nobody dies of old age. They die of diseases that old age makes us more susceptible to. Life extension advocates extending the useful period of one’s life to make 90 the new 40.

Immortal fictional characters often long for death, but usually because they are tired of their friends dying. If everyone lived a long time they would probably be pretty happy about it.

Consider

What would you do with another lifetime?
Which decade of your life would you like life extension to extend? Would you be in your 20s for 50 years? Teens? 40s?
If you could push your healthspan, at the cost of your lifespan, would you? (I.e. live in a 25 year old body until you are 60, then drop dead.)

Return of the face lift

Brazil

More invasive procedures such as surgical facelifts will regain popularity – people are tired of paying over and over for fillers⁶⁰, which is more like a subscription model. Superusers say a surgical facelift is cheaper in the long run, and forecasts seem to be aligned with them, as the plastic surgery sector will continue to boom overall.

Consider

beauty standards are variable, is doing something permanent a risk?
has the facelift got too much of a bad reputation from 80s stars who look bad in their old age?
How would this trend generalise to other things? The permanence is embraced in tattoos already?
how does this sit with trends towards body positivity?

Rewilding

Depiction of some mammals common in northern Eurasia during the late Pleistocene, by Mauricio Antón. From left to right: wild horse, woolly mammoth, reindeer, cave lion and woolly rhinoceros. Pleistocene Park

Cities and suburbs are looking for places to downshift development and add urban greenery⁶¹ to compensate for rising CO₂ emissions. Especially if carbon sequestration is eventually monetized, this could have an impact on land use overall, since owning undeveloped forest land would be profitable. This permaculture land ownership.

Progress in ancient DNA recovery is leading some to suggest rewilding with currently extinct fauna⁶².

Consider

Will this lead to a sharper distinction between urban and wild?
How will we interact with the apex predators (bears, wolves, etc.) that are needed for a functional ecosystem?
Will governments need to compulsory purchase the land from farmers, or will there be another way to incentivise rewilding? Maybe an emissions scheme, or fallow payments?

Screens

Screens have become bigger and denser. ‘Retina’ screens mean that we can get up close and not see pixels. “Don’t get too close or you’ll get square eyes” doesn’t apply anymore.

Being able to get close to a screen means that we can change the relationship with them. Touch screens mean that we can interact directly with images.

We’re seeing flexible screens making a tentative step onto the market. Soon we might see screens that feel like they have a texture (buttons, roughness, etc.). We’re also seeing screens in more places: on watches, as car dashboards, as billboards, inside VR headsets.

Consider

What other interface methods might supplant screens?
Will screens continue to get bigger and denser?
What will happen if screens stop being personal and are about shared experiences?
where else could we have screens?

Self driving cars

From a long shot dream in 2004⁶³ driverless cars are now more of a when than an if.

Humans need a lot of tolerance to account for their imperfect driving skills. That means that the lanes need to be wider, cars need more impact protection, cars need to drive further apart.

Cars also represent freedom for a lot of people. Owning a car means that for a large proportion of the day each car is idle. When cars drive themselves it’s unlikely that anyone will own a car. Cars will provide mobility. That means that parking will be eliminated, freeing up almost half of the current road network and many structures currently dedicated to parking.

While not driving, people will be free to do other things. They could sleep, have meetings, eat, relax, etc.

“To generations of Americans, owning a car represented freedom. To the next generation, not owning a car will represent freedom.”⁶⁴

Consider

Will this replace mass transit?
Current cars are styled to face forwards, and to be a little bit like racing cars. What will future cars be like?
What will this do to ownership models? Will it be transport as a service?
What effect will this have on moral standards (drink driving) or sexual freedom?

Smart homes & internet of things

⁶⁵

Legislation is already in place that all white goods will have wireless communication built in. That means that a central controller in your house will be able to tell your air conditioning to ease off a couple of degrees to reduce peak electricity loading.

The dream of smart refrigerators ordering more milk as you run out is getting closer. There are lots of other issues that are less obvious and less friendly about every aspect of your life being instrumented. E.g. there have been lots of examples of smart home devices being hacked and used as spy cameras. Less frightening, but still annoying, a lot of smart devices stop working altogether if the parent company shuts down.

Consider

Would you let a power company decide when you boil the kettle if it saved you money?
Who would have access to data about your house? Who should?
Would you like to be able to turn off your iron if you left it on at home? How about your lights?
What if your smart lock company goes broke and you can’t get into your house?
How does this impact the built environment?

TikTok/K-pop activism

Wikipedia

Apps and subcultures that consist of almost entirely young people are able to self-organise and do things that seem surprising and impossible to the older population that aren’t involved. E.g. the overbooking of a Trump rally by K-pop fans.

The capacity for a group of under-enfranchised people to self-organise like this is new, and its power is not well understood.

Consider

This is inherently global, the arab spring was similar, but had local effects, where could this go next?
Is this just gen Z using TikTok? Might we see a coup led by the Peppa Pig fan chat brigade?

Ubiquitous broadband

Broadband internet unlocks so much of our urban economy in the developed world but that is a small part of the earth’s surface.

What would access to broadband do for rural African farmers, or for Antarctic explorers?

Google had project Loon, Facebook tried giant autonomous planes that act as repeater stations to the ground. SpaceX is putting a network of toaster-sized internet-satellites into orbit and .

If everyone in the world has access to the same markets it would have a huge levelling effect. It might raise the incomes of the poorest, but it might well lower the incomes of the most well-off.

Consider

What can you do with fast internet that you can’t with slow internet?
Could the world’s best robotic surgeons operate on the cases that most needed their help, regardless of how close they were to a big hospital?
Could low income Indian children get educated by the best teachers?
Could Ethiopian graphic designers sell their expertise to Chilean wine producers?
What are the exponential potentials with this card?
If broadband is ubiquitous (e.g. available in national parks), will it be possible to get away from it? Is this a good thing? Is it a technology problem or a social problem?

Urbanisation

Populations and urbanisation percentages by Hannah Ritchie and Max Roser, Our World in Data

The NSW Department of Infrastructure Planning and Natural Resources estimates that 60% of the world’s population will be living within cities by the year 2030 and about 91.1% of the Australian population will live in cities. They expected the population in the Sydney Region alone to grow by a net increase of 40,500 per year.

The forecast demand for new residential development to support Sydney’s current population is 25,000 dwellings per year over the next ten years, with 25% of that growth located in Greenfield sites on the urban periphery and Greater Metropolitan Region corridors.

With the enlarging population and increasing urbanisation the demands on resources will contribute to further degradation of the Australian environment and Sydney’s ever expanding urban sprawl.

Consider

Is it inevitable that the urbanisation trend will continue?
Can we bring traditionally rural activities into cities too?
What benefits could come from even greater urban density?
What mistakes are cities making right now that we might not make in the future?

Virtual reality

Current virtual reality gives us a glimpse of how we’ll experience it in the future. There’s a lot between us and fully believable, totally immersive virtual environments. As we solve more and more of those problems, VR will become more useful. Breaking out of gaming to be the standard method for video conferences, for virtual site tours and for shopping.

Consider

If VR was perfect, would people still prefer the “authentic experience”⁶⁹
Do crimes committed in VR have moral status? Killing? Rape? ⁷⁰
What could VR never simulate? Are you sure?
Is VR just a step on the road to AR, or do they have different applications?

Walking robots

Legs have lots of advantages over wheels. 2, 4 and more, legged robots are able to go places that wheeled and tracked vehicles can’t⁷¹. That means that we can send robots to map remote places, or to navigate places designed for humans. (Or other legged things!)

Most of the current crop of robots have military origins, but they are also ideal of other types of hostile environments, like firefighting, rescue or space!

Consider

What other sectors could these robots be used in?
Wheels need smooth surfaces, legs don’t. Will we need fewer roads?
Does this have an outsized effect on humans’ exceptional talent of mobility in difficult spaces? Will it affect employment?

Wearable/implantable technology

Apple watches have FDA approved ECG capabilities, but its usefulness is disputed 9 to 5 mac

We are in the first flush of the wearable technology boom⁷². The quantified self⁷³ that knowing your steps and heart rate allows for means that people can make more informed choices about their behaviour.

We are currently in a very naïve period of this trend. The things we measure aren’t the important things, they are the things that are easy to measure. The feedback we get is distracting and doesn’t allow us to be more present in our lives. In the next generation of wearable, or even implantable, technology, we’ll be able to use it to maximise our health and wellbeing, and to be far more present than we currently are.

In vet science, there are sensors that sit in a cow’s stomach that can relay back to the farmer the health of each cow. Humans have pacemakers, but non-therapeutic implantables are almost unheard of⁷⁴.

Consider

What else could you measure and what would be the best way to do it?
What would you do with that data?
Who else would like to know that information about you? What information would you worry about if it was leaked?

XYZ as a service

Anything you can do or own yourself can probably be provided as a service⁷⁸ to you. Gmail is the most obvious example: email as a service. People tend not to have a well at their house, they get water as a service.

You can get computing and storage as a service from AWS. X as a service also applies in the physical world. Uber and GoGet are examples of transport as a service.

Consider

What advantages are there for rolling your own? (This mean not using x as a service, but making a version of that service for yourself.)
What can’t be turned into a service and why?
What will people do when they have a service for everything?
What do you own/do that could be provided as a service?

Zoom fashion

Fashion designers and retailers will create markedly different strategies⁷⁹ for fashion that appears on the upper body, ie above “the Zoom line” compared with the bottom half of the body, which isn’ usually visible on screen.

Many fashion houses have been embracing comfort and loungewear. Tracksuit bottoms have become the defacto cool weather bottoms of the pandemic.

Consider

Now that we’ve had a taste of comfort, will we go back?

life expectancy

Life expectancy continues to increase⁸⁰ in contrast to Hobbes’ idea of life, which was “Nasty brutish and short”. We are comfortably on track to hit an average life expectancy of 100. There is a lot of variation in global life expectancy. That average of 100 means that there will be a global reduction in lifespan inequality, or that some nations will see huge lifespan increases. It’s not uncommon to see claims that some children alive today will live to be 150⁸¹ or 200⁸²!

Life expectancy is measured at different ages. These days, in ‘developed’ countries the difference between life expectancy at birth and at five years isn’t substantially different. Some believe that prehistoric humans could expect to live into their mid fifties⁸³ if they made it through childhood.

Consider

Will life expectancy rise equally all over the world?
Will people work for longer in their life?
Will people maintain a single career? Does their degree from 1990 have any validity in 2050?
Will there be a modern equivalent to coopers and farriers needing to find new careers during their lifetimes?

Design for Manufacture and Assembly (DfMA)

An example of DfMA design refinement to improve assembly ease. Boothroyd, Geoffrey, Peter Dewhurst, and Winston A. Knight. Product Design for Manufacture and Assembly. 3rd ed. Manufacturing Engineering and Materials Processing 74. Boca Raton, FL: CRC Press, 2011. p.83.

Design for Manufacture and Assembly (DfMA) is a product design approach that was developed in the manufacturing industries as a way of linking the design and production processes of product development. DfMA captures production data and makes it accessible to the design team in the form of design principles and guides, and metrics for design evaluation and improvement. The aim is to create designs that are efficient, fast, and cost effective to produce. DfMA advocates: modularity and standardisation of parts and processes; simplicity in design; connection interfaces that cannot be assembled incorrectly; part count reduction (as fewer parts as possible); and an emphasis on maintaining good visual and physical access to all connection points (think IKEA!).

In the last decade, the construction industry has turned its attention to DfMA as a potential solution to its productivity crisis. Although some of the DfMA design rules (and most of the DfMA metrics) used in manufacturing are not completely appropriate for use in the design of buildings, DfMA as a philosophy certainly is, especially when paired with prefabrication. The development of a construction-specific DfMA represents a shift towards data-informed design. The construction industry will need to increase the sophistication of its data collection methods during building production/construction phases so that an appropriate set of design guides and evaluation metrics can be developed.

Consider

What kind of production data (in factories, in transit, on site) will be important to capture to inform design, and how might we do this?
How much standardisation (product and/or process) is it possible to achieve in the construction industry?
What does part count reduction mean at the scale of a building?
If buildings can be assembled as easily as IKEA furniture, what does that mean for the construction workforce?
If buildings can be assembled easily, they might also lend themselves to easy disassembly. How might this change the way we source new materials/components and design new buildings in the future?

Mass Timber Construction

A 350m tall timber tower proposed for Tokyo. Sumitomo Forestry

Mass timber construction refers to the use of engineered timber products such as cross-laminated timber (CLT) and glue-laminated timber (glulam) in the structure of a building. Engineered timber products are made by gluing layers of raw timber boards together into planar elements (CLT, used in floors and walls) or linear elements (glulam, used in columns and beams). This production method means that large timber building parts can be produced without cutting down old growth forest. Additionally, the properties of the building elements can be enhanced by using different types of timber (and even other materials) in the composition of layers.

Mass timber construction offers many benefits over typical concrete construction. First, timber sequesters carbon, meaning that the building becomes a carbon sink for the duration of its lifetime (as opposed to emitting carbon, as concrete manufacture does). Second, mass timber is much lighter than concrete, so it needs smaller foundations, and can often be used to add new floors to existing buildings. Third, mass timber changes the nature of the construction site, eliminating the need for formwork and wet trades, and significantly increasing the speed of construction (Brock Commons, an 18-storey mass timber project in Canada achieved a floor cycle time of 3 days). Some issues to consider when building with mass timber, include: forest certification, carbon miles in delivery (if CLT or glulam is not being manufactured locally), performance of the building under fire conditions, chainsaw attack!

In 2009 the first “tall” mass timber building—the 9-storey Stadthaus Murray Grove in London—triggered a global fascination with pushing mass timber to its limits. Since then, several buildings have held the record for tallest, only to inevitably have the title taken away. The current tallest, Mjøstårnet in Norway, sits at 85m, however a Japanese company has proposed a 350m tall structure for Tokyo, and is currently conducting research towards making this happen in the very near future.

Consider

Often with technological change, initial roll-outs tend to mimic what has come before: the first cars looked like horse-less carriages, early steel skyscrapers were adorned with the fluting and ornaments of earlier 19th century buildings. Mass timber construction is a relatively new building typology, and as such, expectations are not yet set. Many current mass timber building designs adopt the language of contemporary reinforced concrete and steel construction, however an emphasis on sustainability is emerging. What innovative architectural typology might mass timber evolve into in the future?
If mass timber becomes the predominant construction technique in our cities, how will we sustainably manage the demand for raw timber?
Engineered timber products have not been around that long (glulam around 100 years, CLT around 35 years). We do not know how the products will degrade in 200, 300, 600 years’ time. What kinds of monitoring/intervention mechanisms should be introduced to ensure the safety of inhabitants living in cities full of 350m tall timber skyscrapers?

Private space exploration and asteroid mining

Asteroids are mainly made of nickel iron or frozen water. They also contain a lot of platinum group metals. They are easy to mine because they don’t have big gravity wells that need to be overcome.

Water is important to space travel because humans need to drink it, but unmanned missions need water too because it can be split into rocket fuel. Launching things into space is really expensive, so if it’s possible to build spacecraft from things already in space it’s much cheaper.

The availability of precious metals in asteroids could upset the world economy in the same way that the influx of silver from South America caused massive inflation in the 15^th–17^th century⁸⁴.

Consider

If you hollow out an asteroid what could you do with it?
Platinum is used as a catalyst in chemical reactions. Making it a lot cheaper would make a lot of these applications more viable. What sorts of things could we do if the cost of platinum went down?
What could you do with a million tonnes of water in space?
Getting raw materials into space is expensive. What could you use the iron in an asteroid for?

Smart homes & internet of things

This is an image of an xxx by YYY

Consider

Would you let a power company decide when you boil the kettle if it saved you money?
Who would have access to data about your house? Who should?
Would you like to be able to turn off your iron if you left it on at home? How about your lights?
What if your smart lock company goes broke and you can’t get into your house?
How does this impact the built environment?

Not the song, but Wireless Application Protocol ↩
Machine Bias - There’s software used across the country to predict future criminals. And it’s biased against blacks. by Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner, ProPublica May 23, 2016 ↩
Blendle is a Dutch online news platform that aggregates articles from a variety of newspapers and magazines and sells them on a pay-per-article basis. The key differences to similar websites are the participation by otherwise commercially unrelated news services in a single platform and the ability for registered users to easily pay a small price per article. ↩
https://www.home.saxo/insights/news-and-research/thought-leadership/outrageous-predictions ↩
“Autofac” is a 1955 science fiction short story by American writer Philip K. Dick that features one of the earliest treatments of self-replicating machines ↩
How Nigeria transformed from a business into a country ↩
Watch springs are the obvious precedent, but their energy density is tiny in comparison. ↩
See an example prediction market ↩
definition from here ↩
https://www.mintel.com/global-consumer-trends ↩
As far as I can tell this counts the number of connections, but doesn’t take into account how many people share that connection. The number is 40 for France, but there might be more than 2 people sharing each line. Which would mean more than 1 connection per person! Data via Google: World Development Indicators ↩
Illustrated by how many totalitarian nations restrict access to the whole internet. ↩
↩
https://info.trendwatching.com/21-trends-for-2021 ↩
https://www.mckinsey.com/industries/retail/our-insights/state-of-fashion ↩
https://info.trendwatching.com/21-trends-for-2021 ↩
https://www.mckinsey.com/~/media/mckinsey/featured%20insights/china/china%20still%20the%20worlds%20growth%20engine%20after%20covid%2019/mckinsey%20china%20consumer%20report%202021.pdf ↩
https://intelligence.wundermanthompson.com/trend-reports/the-future-100-2021/ ↩
https://www.accenture.com/us-en/insights/interactive/fjord-trends ↩
Wikipedia: Moore’s law ↩
Which is why there are so many data centres in Iceland. ↩
Note that the graph has a log scale, that means that each line is an increase of 10 times, not of one unit! ↩
All these graphs are from: The history of Australian property values ↩
Advanced Space Transportation Program: Paving the Highway to Space ↩
Quora: What is cost of sending 1kg weight into space? ↩
Wikipedia Falcon_Heavy Launch_prices ↩
Against Waldenponding ↩ ↩²
http://violentdeathproject.com/countries/australia ↩
From Wikipedia: Crime in the United States ↩
The Better Angels of Our Nature ↩
for a nice interactive view of this phenomenon this article is good ↩
Dark kitchens create meals exclusively for the online delivery market - ABC ↩
https://victrola.com/blogs/articles/music-industry-trends-to-look-for-in-2021 ↩
https://info.trendwatching.com/21-trends-for-2021 ↩
Minimalism: another boring product wealthy people can buy "Minimalism is just another form of conspicuous consumption, a way of saying to the world: “Look at me! Look at all of the things I have refused to buy!" ↩
https://www.fastcompany.com/90588717/top-tech-trends-2021-post-pandemic-predictions-ai-fintech-health ↩
https://www.foresightfactory.co/trends-report/ ↩
https://en.wikipedia.org/wiki/Hikikomori ↩
Accessorize to a Crime “Research from Carnegie Mellon University can generate visual patterns onto glasses to either avoid facial recognition or ‘impersonate’ as someone else” ↩
https://www.frogdesign.com/designmind/trends-2021?utm_campaign=USA_Trends%202021&utm_source=email&utm_medium=trends%202021%20email&utm_term=trends%202021%20email&utm_content=trends%202021%20email ↩
GDP per capita (constant 2000 US$) ↩
I’m mainly talking about personalised medicine here:. Medicine that affects genes is another topic, big enough to justify its own card. ↩
How is Today’s Warming Different from the Past? ↩
With the printing press displacing scribes as the other that I can think of. ↩
https://bit.ly/3Hxlzl3 ↩
internet.org was planning to make internet access available through solar powered planes. ↩
Loon was planning to make internet access available through weather balloons. ↩
Drug harms in the UK: a multicriteria decision analysis by Prof David J Nutt, FMedSci; Leslie A King, PhD; Lawrence D Phillips, PhD ↩
https://www.singlegrain.com/web-trends/what-is-live-stream-shopping/ ↩
https://www.foresightfactory.co/trends-report ↩
https://www.benzinga.com/markets/cannabis/21/01/19329903/7-psychedelic-trend-predictions-for-2021 ↩
Worth checking this out! Frog: Mobile Money in Afghanistan ↩
There is an article about the economy of second life and this is an exchange that only deals in virtual currencies. Both are shut down now, but there were some wild stories from that era! ↩
Something like 80% of €500 notes are believed to be used in money laundering! The End of Money: Counterfeiters, Preachers, Techies, Dreamers–and the Coming Cashless Society ↩
ABS data, high scenario. ↩
Wikipedia: World population ↩
This talk is a really good source to understand the threats to the open internet ↩
TODO: find what this footnote pointed to ↩
https://en.wikipedia.org/wiki/Price_revolution ↩
https://www.newbeauty.com/aesthetic-trends-2021 ↩
https://www.mintel.com/global-consumer-trends ↩
https://www.theatlantic.com/magazine/archive/2017/04/pleistocene-park/517779/ ↩
https://en.wikipedia.org/wiki/DARPA_Grand_Challenge ↩
http://breakingsmart.com/a-new-soft-technology ↩
http://idisrupted.com/disrupted-electronics-internet-things-may-create-moores-law-steroids/” ↩
https://www.fastcompany.com/90588717/top-tech-trends-2021-post-pandemic-predictions-ai-fintech-health ↩
a16z Podcast: Companies, Networks, Crowds ↩
https://www.mintel.com/global-consumer-trends ↩
What Sort Of People Should There Be? ↩
The Nether ↩
Or can’t without causing substantial damage. ↩
Fifth, if you count clothes, shoes, spectacles and wrist watches as the first four.” ↩
The Quantified Self movement was founded by Kevin Kelly, and whilst niche at the time is now so mainstream that it’s basically not talked about any more. ↩
See the case of Meow-Ludo who implanted an transport card into his hand ↩
from How Did Work-Life Balance in the U.S. Get So Awful?. If we assume a 50 week year, Greece has gone from 54 hour weeks to 41; the Netherlands from 46 to 28! ↩
https://www.abs.gov.au/articles/insights-hours-worked ↩
When John Maynard Keynes Predicted a 15-Hour Workweek “in a Hundred Year’s Time” (1930) ↩
The World Of Everything-As-A-Service, Tom Blomfield, Techcrunch ↩
https://www.wgsn.com/content/board_viewer/#/85986/en/page/1 ↩
https://goo.gl/0omR22 ↩
http://goo.gl/CCBPuv ↩
http://ktwop.com/2012/12/27/the-first-200-year-old-human-has-already-been-born/ ↩
Hillard Kaplan, Kim Hill, Jane Lancaster, and A. Magdalena Hurtado (2000). A Theory of Human Life History Evolution: Diet, Intelligence and Longevity (PDF). Evolutionary Anthropology 9 (4): 156–185. ↩
Wikipedia Price revolution ↩

Cornbread recipe

Mon, 03 Aug 2020 09:00:00 +0000

Equipment:

Mixing bowl
10 inch cast iron skillet
blender
Spatula
[optional] probe thermometer

Skillet:

100g unsalted butter, plus more for serving

Dry:

140g fine yellow cornmeal
140g all-purpose flour
50g sugar
6g kosher salt
18g baking powder
1g (1/4 teaspoon) baking soda

Wet

2 eggs
170g sour cream
113g cultured buttermilk
1 tin of sweetcorn, drained

Adjust oven rack to centre position and preheat oven to 220°C.
In a mixing bowl, weigh out the dry ingredients.
In a blender weigh out the wet ingredients and blend until fully smooth
Place butter in a 10-inch cast iron skillet. Transfer skillet to oven and heat until the butter is melted and well browned, 10 to 20 minutes (you can measure your wet and dry ingredients while waiting).
Stir wet ingredients into dry, then add the browned butter. (Careful, it’s hot as fuck.) Stir until homogeneous.
Remove skillet from the oven and swirl to coat all surfaces with melted butter. Spoon batter into skillet, smooth top lightly, then transfer to oven. Bake until light golden brown on top and a wooden skewer inserted into cornbread comes out with no crumbs, 20 to 25 minutes. (Or internal temperature reaches 90°C)
Let cool 10 minutes, then serve with extra butter and honey at the table.

This is a bit of a hack hybrid of the Serious Eats and the Chefsteps cornbread recipes, which are both delicious. Most of the words are even from the Serious Eats recipe. I just tweaked it to make it a bit moister and have more corn.

You can make the dry part ahead of time and it lasts for something like 6 months but then the baking powder starts to lose its fizz.

Printing hyperlinks nicely as footnotes

Sat, 13 Jun 2020 15:45:00 +0000

Walden Pond is full of content that was intended to go on the web. So there’s all sorts of problems with how to make it usable in print. One of the most obvious is hyperlinks.

There are some really nice tricks that make what the link links to visible in print.

a:after {
    content: " [" attr(href) "] ";
}

From CSS tricks

Which is cool if your links are nice looking, but sometimes the text has a tonne of links in it and you can end up with more link than content.

In Walden Pond I’ve put the links in as footnotes. So a superscript number in the text, and a numbered list of links at the end of the article. I’m using a slightly edited version of Aaron Gustafson’s footnote code (from 2005!).

This is great, but sometimes you’ll get an article that uses a lot of long links. A prime offender is when the article recommends a lot of things with amazon referrer links, but it could be almost anything. For example, in the Wait But Why post From Muhammad to ISIS: Iraq’s Full Story there are 54 links, and a lot of them look like this:

https://www.ft.com/content/69e70954-f639-11e3-a038-00144feabdc0?%E2%80%94ftcamp=crm/email/2014617/nbe/AsiaMorningHeadlines/product#axzz3A20GKJTZ

In this case, the bit after the ? is just tracking (?%E2%80%94ftcamp=crm/email/2014617/nbe/AsiaMorningHeadlines/product#axzz3A20GKJTZ) to tell the FT where the reader found the link. But in some cases, the URL params actually have useful information in them, so I can’t just cut them off.

What I’ve ended up doing is using Firebase Dynamic links to shorten these links, so the FT link above becomes: Hi1e

That’s sort of cheating because it’s actually https://pond.page.link/Hi1e but the first part is the same for all the shortened links.

This means that people can either remember the https://pond.page.link/ part and build their own links, or they can go to the Walden Pond website and type it into the link-expander.

This figure is half-width and floated right

One problem with shortened links is that they’re an extra layer of abstraction away. So you have no idea if Hi1e is taking you to the FT or to PornHub, or to Best Number One Phishing Bank. I’ve tried to get around that by only shortening links over 90 chars long, and then for the links I do shorten leaving the first part of the domain intact. Giving: ft.com | Hi1e.

Sometimes the link has an ID attached to it, so I’ve added that in too. Hopefully it’s not too confusing, because without it, you can’t see what the link points to because Firebase seems to strip off the #part of the url.

WIP: Recipe vis

Tue, 28 Apr 2020 21:45:00 +0000

Visualising cooking a meal

I’ve always struggled to read recipes all the way through and visualise the order of operations. Mainly because my attention span is terrible, but also because there is going to be interactions with other things in my life; usually the other parts of the meal I’m cooking.

I’d imagine that chefs are pretty good at imagining how the sequencing of a day’s work is going to go. What prep needs to be done, in what order, and how it’s going to interact with the other components. There’s also the advantage of getting another go at it; Home cooks don’t do so well because usually it’s the only time you’ll ever cook a dish. Chris Young¹ said in an interview that the best thing for a home cook to do to level up their cooking was to not cook things for the first time on the day of the dinner party.

Anyway, most recipes say “Here’s how to cook really good roast potatoes” which is great if you want to only serve your guests roasties, but if you want to roast a chicken too, your oven becomes a bottleneck in your production. This sort of thing makes cooking at home tricky because home cooks aren’t skilled in planning this sort of stuff. Short of having a cup of tea and writing lists, how else could we support home cooks who are planning a dinner party (or just dinner) to get things to the table at the right time?

Eventually, I really should go and talk to some people who are actually good at this sort of stuff, but while I’m trapped in my house, let’s take an abstract approach to the problem.

Questions:

Information structure (is this the right term?)
- How do you plan the interaction between your recipes?
- How do you plan the interaction between the cook[s] and the things they’re making?
- Can the recipes be broken into components?
  - Do those components consist of tasks? Processes? It’s semantic, but does a task require an agent’s involvement? Is being in the oven a task? What’s the right word to make this idea flow into people’s minds?
- Can components be interrupted? I can stop chopping a carrot to take something out of the oven if a beeper goes off. What’s the task switching cost?
- What tolerances are there? E.g.:
  - Can I make this component ahead of time? How far ahead?
  - Can this cook for 40 minutes instead of 35?
- Can components share equipment? E.g. there’s a ChefSteps eggs benedict recipe where everything gets cooked at 64°C. That means that you can do everything in the same pot with one circulator. The “Perfect Hollandaise” recipe asks for 75°C, but that would need an extra circulator for the eggs.
  
  vs
  - Does those shared pieces of equipment have limits? I can only put so many trays in the fridge (space), so many cookies in the oven (power).
User
- Does the representation actually make it easier to understand and plan a cook?
- Is there a lot of user specific information? Can cook A mince a shallot faster than cook B? (Do we end up with a bunch of comparative advantage issues here?)

First thoughts

I think that Gantt charts, a la Microsoft Project, are more about organisation theatre than an actually useful tool. Tufte agrees. But, if you flip the chart so that instead of each task going in it’s own row, like an endless waterfall of misery, each resource gets a row, then you can see some useful interactions.

The diagram above is pinched from the docs for Google’s OR-tools Job shop algorithm. Job shop scheduling is the most promising algo/concept that I’ve seen that applies to this problem. The only problem being that the jobs here (tasks/components) have a lot more metadata than the basic examples that I’ve seen. There are some papers that discuss the addition of operators to the problem, so they’re probably helpful (e.g.). I’ll consult the CS brains.

Prototype vis

TODO: draw out a couple of simple recipes to see how it looks. Put an operator rail along the top for person one, and along the bottom for person 2, maybe through the middle for a third person?

The people can be linked to the tasks on equipment rails.

TODO: look into critical path

TODO: Talk to some chefs

Examples

Cooking for engineers

This is interesting as it shows the process of combining ingredients into sub components. The flow of that is sometimes hard to parse out of prose recipes because the ordering is arbitrary. This particular recipe is more or less a waterfall. From looking at the table it seems like soaking and boiling could be parallel activities, but I wouldn’t want to risk it as it might not take 10 minutes to cook the sugar syrup. (ideally there’d be a way to show temporal relationships that’s more complicated than purely precedence. E.g. “you can do these two steps in parallel, but wait 5 minutes before you start boiling the sugar.”)

Pro cookbooks

More professional recipe books assemble dishes out of sub recipes. This makes it easier to delegate work to cooks, but doesn’t really help us understand the timeline or the interaction of those components.

Recipe schema

Schema.org has a markup for recipes which makes recipes parsable by a computer by adding semantic tags to each part of the recipe.

It has tags for: cookTime, cookingMethod, nutrition, recipeCategory, recipeCuisine, recipeIngredient, recipeInstructions and recipeYield. Those are the specific recipe tags, Schema.org has inheritance, so it inherits a whole bunch from more general things, like HowTo and CreativeWork. There’s an example of a marked up recipe at the bottom of the page, have a look.

The only one that’s actually interested in how the food gets cooked is recipeInstructions. That’s defined as:


`CreativeWork` or `ItemList` or `Text`	A step in making the recipe, in the form of a single item (document, video, etc.) or an ordered list with HowToStep and/or HowToSection items.

Even the most structured (ItemList) is just a list. If we want more structured/nuanced way of describing things we need to layer on metadata from elsewhere.

Solution ideas

I think the ChefSteps process of having a list of ingredients, equipment, yield, active and inactive time at the top of the recipe is a good start.

I think it was when he called in to Cooking Issues, but I wouldn’t trust anything I say! ↩

Introducing Walden Pond

Thu, 23 Apr 2020 09:00:00 +0000

There are a lot of interesting articles online, and so little spare attention to read them. The Walden Pond zine is my way of fixing that. I thought it would be worth sharing that with other people too, so you can subscribe to Walden Pond yourself now. If you’re interested in how it works around the back, I’ll be doing a post on that soon.

One of the prototype editions, on my messy kitchen table. Reading with a pen in my hand feels different to reading on a screen; I like it.

What problem are we solving?

When I’m working, I constantly come across interesting articles. My ADD is like a naughty dog, at the slightest provocation it pulls my brain off track and onto something else, so I need a strategy to keep it going in the same direction as I’d like to go. At the same time, I don’t want to deny myself the ability to read all this interesting stuff because then my life will be boring.

I need a way to store all the interesting stuff I come across, so when I’m not trying to focus on something I can pull them out and expand my mind.

That’s problem 1, and there’s a fantastic solution to that, Pocket, but problem 2 has the same root cause: difficulty in controlling my attention. It’s all very well having all these interesting articles, but I get distracted from reading them to do other things¹.

How does Walden Pond solve those problems?

Problem one is easy, you just save the interesting article to Pocket and come back to it later. It’s a habit that took me a while to build, but it’s automatic now.

Problem 2 is harder, how do I protect myself from the ravages of notifications on my phone or from the “oh, this idea is hard, I wonder what’s on Twitter?” thought loop?

I think the answer is selective Waldenponding. The idea is that you carve out some distraction free time, an unplugged hour, but then you throw yourself headlong back into the melee.

Walden Pond is a little magazine that is full of articles that you’ve already saved to your Pocket. The act of saving is a strong signal that you’re interested, so the hour of reading should be great.

It’s on paper, so you can take it somewhere that your phone isn’t. I find the first few minutes away from my phone very unnerving, but if I persevere then it’s very freeing. It allows me to dedicate all my thinking to what I’m actually doing. By the end of that hour I’m thrilled to get back into the rest of the world, but the time out gives me a chance to recharge.

How does the computer know what articles to put in your edition of Walden Pond?

Because you’re saving articles as you go along, there’s a very strong chance that you will still want to read it when you get back to it. When you sign up you can pick the longest article you want to read, and the shortest. (E.g. I have my shortest set to 11 minutes because I read articles shorter than that while I’m waiting for the train.) The algorithm picks the longest article you have saved that’s shorter than your cut-off, then fills up the rest of the space with a random selection².

That means that you will get a chance to really get stuck into that long article that’s been eluding you. Turns out that for me, this month, it’s an article about The demise of the nation state which is 26 minutes long. My bounds are 11–26 minutes, so an example edition for me is:

Title	Time to read
The demise of the nation state	26
Sarah Sitkin’s Bodysuits presents the human form as it really is	11
Superforecasting: How to Upgrade Your Company’s Judgment	18
AI And The Ghost In The Machine	13

Which I had to wrench myself back to typing this as I was getting those links because it’s as if the algorithm knows me. But, there is no ghost in the machine! Past you is just a good predictor of what present you is interested in.

How to get started:

If you’re already a mad Pocket fan then all you need to do is sign up at WaldenPond.press and then you’ll start getting an edition every month.

If you don’t use Pocket, then you need to start becoming a mad pocket fan!

First thing to do is sign up to Pocket: getpocket.com

Then get the Pocket browser extension 💻 ( Chrome, Firefox, Safari, Edge) and the mobile app ( Android 🤖/ iOS 🍏 ) because that will make saving articles a breeze.

Then go on a saving spree! You are the expert on what you like, but here are some links that might be good places to start if your mind’s gone blank:

The New Yorker (News)
Aeon (Essays)
BBC Future and Worklife (Ideas)
Cosmonauts Avenue (Literature)
Hacker News (Tech)
Arch Daily (Architecture)
New Scientist (Science)
The New York Times (News)
Quanta Magazine (Science)
Ribbon Farm (Ideas³)
The Guardian(News)
The Verge (Tech)

It’s easier to pack a hour if you have a mix of short articles as well as long ones, so be broad in your saving habits.

I’ve been working on this, on and off, for about 2 years now. This is just a few of the prototypes that I’ve made and read through.

So there you have it, Walden Pond, the zine’s first outing on the world stage. I’d love to know what you think about it, or what’s stopping you from signing up. (I make the website with the typing⁴, so I can change things!)

As an extra incentive, it’s half price at the moment!

I can’t be the only person who’s got bored of Facebook and opened a new tab and gone to Facebook to see if it’s less boring. ↩
There are other things you can do, like force including, or excluding certain articles, but let’s not get too fancy here. We’re already over 1200 words. ↩
A nod to the genesis of the name for this project: Vankatesh Rao. He’s well worth adding to your editions. ↩
I was playing around with an art for the foyer of a cancer research centre in Sydney, making a branching tree in Generative Components, about a decade ago, and someone asked me if I was “making the tree with the typing”. That phrase has stuck with me ever since. ↩

Notion Parallax

Choosing Gas

Back gas ppO₂ 1.3, Deco gas ppO₂ 1.6 - Decompression Profiles

Back gas ppO₂ 1.4, Deco gas ppO₂ 1.6 - Decompression Profiles

Printing a reel

16/02/2025 Some land based testing

Dive Checklists

Core pre-dive prep

Pack - main bag

Pack - dry bag

Post dive job list

Winter extras

Sidemount extras

Dressing order: sidemount

Dressing order: backmount

Lecture 2—Computational Design Theory 1—Architecture's Digital Turn

Updated: A Game About Possible Futures - how to play

Possible Futures

How to play

Early rounds

Final round

Tips

The canvas

Canvas

Contributing

Improving cards

Making new cards

Updated: A Game About Possible Futures - the cards

5G/𝒩G

Consider

AGI fast take off

Consider

AI Bias

Consider

AI creativity

Consider

Advert free internet

Consider

Amazon Nations

Consider

Architectural team size

Consider

Audio AR

Consider

Battery density

Consider

Bee population crash

Consider

Betting markets

Consider

Big data analysis

Consider

Breakdown of traditional education paths

Consider

Broadband access inequality

Consider

Carbon labelling for consumer goods

Consider

Cashless biometric payments

Consider

Centralisation of web companies

Consider

China power shift

Consider

Climate migration

Consider

Compute power

Consider

Concentration of functions into smart phones

Consider

“Conservative” policy dominance

Consider

Cost of domestic property

Consider

Cost of space travel

Consider

Cottagecore and Waldenponding

Consider

Coworking and Cohousing

Consider