Jay Springett: You can find me online. I’m at @thejaymo. Professionally you can find me at The Ruderal. In my pro­fes­sion­al life, I work as a BizOps-type start­up scal­ing con­sul­tant.

So, Madeline Ashby is a sci-fi writer and a futur­ist. And at the end of last year on her blog she wrote that her one piece of advice for 2018 is that we should talk loud­ly, fre­quent­ly, and in detail about the futures that we want. And that kind of real­ly will set the tone for the rest of talk. And I want you to kind of keep that in mind, that we should be speak­ing about the futures—with every­body that you come across—the kind of futures that we want, because it’s impor­tant.

So I may be best known— I, for my sins, coined the term stack­tivism” ear­li­er this decade, and have been inter­est­ed in infra­struc­ture and pol­i­tics, and what it means. And kind of the thing that I per­haps am most known for tum­bling out of this project is the term, Who owns the means of not dying?” And that was kind of one of my prin­ci­pal con­cerns that falls out of infra­struc­ture pol­i­tics and how we think about tech­nol­o­gy.

I’m also one of the admins on solarpunks​.net which, if you don’t know about solarpunk, it is an emer­gent sci-fi genre which looks to imag­ine a bright green, non-dystopian future for every­body.

Right now, I’m work­ing on a research project called Land As Platform which is kind of look­ing at the cri­tiques that are cur­rent­ly being applied towards plat­forms like Google and Facebook as plat­forms, and tak­ing the log­ic of the cri­tique of plat­forms and apply­ing it to land. What is the log­ic of a plat­form, as opposed to what we think about plat­forms being as like a multi-sided mar­ket, which is what we kind of cur­rent­ly under­stand plat­forms in 2018 to be. But if you say the word land as plat­form,” I think you can kind of con­jure an idea about what it is that I’m seek­ing to write about. And this is prob­a­bly the first out­ing of Land As Platform kind of as a few frac­tured thoughts in this talk.

So I first of all want to talk about short-term think­ing. Who works in tech? How many of you have two-week sprints? How many of you work on qual­i­ty goals? Couple of you. Everyone has year­ly goals at their com­pa­nies, right?

Well, when we think about short-term think­ing, how short-term is short-term? Because if you plant a tree, like an oak tree, it takes 100 to 120 years for an oak tree to be ful­ly grown. So any­thing between the point in which you plant the tree to when the tree is ful­ly grown is short-term think­ing, when we speak about land. Because we have to pass through that peri­od. And talk­ing about a hundred-year time scales for plan­ning is not some­thing that our cul­ture is very good at. But we need to do that.

So, giv­en that it takes 100 to 120 years for an oak tree to reach full height, what does it mean when most of the atolls in the world will be unin­hab­it­able by the mid cen­tu­ry? So we have fifty years until the waves take the islands. So we already have plan­ning for 100 years, but we have cli­mate dis­as­ters with­in fifty. So just fram­ing the kind of con­cepts and the amount of time that these things take is impor­tant to get a han­dle on that.

Speaking in longer terms, in terms of deep time, this is what 8,000 years of agri­cul­ture will do to a land­scape. Does any­one know where the Loess Plateau is? Anyone know? So this is in China. This is where the ter­ra­cot­ta war­riors were found, and it’s where the Han Dynasty began. So if you farm a land­scape for 8,000 years it ends up look­ing like this.

An inter­est­ing fact, I’m sure you all know about Petra in the Middle East. Petra did not deser­ti­fy because the cli­mate changed, it deser­ti­fied because they cut down all the trees and changed the cli­mate. So what do we do about this? Because these are man-made envi­ron­ments.

A wide, largely barren hillside, with many cup-shaped basins dug into it in rows for catching water runoff

So this is an exam­ple of what’s going on. This is a pic­ture from last year. And as you can see they’re plant­i­ng these basins on the hill­sides. So when it rains, the water tum­bles down the hills and filled up the basins and is cap­tured and then slow­ly sinks in once rain stops. And there a tree plant­ed in each of these basins.

Contrasting 2003 and 2010 photos of an area in the Loess Plateau, showing it almost completely barren vs covered with greenery.

So it might not look very impres­sive, but giv­en the right amount of plan­ning and time, this is what you can do to a land­scape. This is the biggest land­scape regen­er­a­tion project ever attempt­ed by human­i­ty, and it’s still very much short-term even if it does look regreened, because trees take 100 years to grow. It looks bet­ter, though. And I’m kind of down for that as a plan.

But these aren’t the only projects. There are big­ger ones. There’s the Nile River Basin, the NBI project, which is going to be restor­ing all of the water­sheds that feed the Nile, improv­ing water qual­i­ty, fre­quen­cy of flow, reduc­ing deser­ti­fi­ca­tion upland, and also mak­ing sure that Egypt gets its con­tin­u­al flows. As part of this project they will be remov­ing dams from the Nile. It is already in progress, the stuff that they can do, but there’s a lot of plan­ning that still needs to be done in terms of how the project gets rolled out.

Satellite map of Africa with the countries participating in the Green Wall Initiative outlined, and showing their point of focus on a line across the continent dividing green and desert areas.

So that seems like a big project, but there are even big­ger projects than this. The Great Green Wall of Africa project, which is the sin­gle biggest plan right now. It is a length of about sev­en and a half thou­sand kilo­me­ters. And the area in ques­tion that they are hop­ing to regreen to pre­vent the Sahara from deser­ti­fy­ing fur­ther is 11 mil­lion hectares of land that is being planned and regreened.

As part of both of these projects, Ethiopia as part of the Eden Project has already regreened one-sixth of its land­mass. So, from the left to the right. And these projects are hap­pen­ing now, and I think it’s real­ly impor­tant that those of us that don’t know any­thing about this do. Because this is very much what the future’s gonna look like. These are not nat­ur­al spaces, these are now anthro­pogenic spaces. Humans have designed these spaces.

But in order to design these spaces we need to plan it. And I’m gonna give you a very brief overview of a thing called key­line design today, which works very much in Europe where it has rolling hills and not so many moun­tains.

So this is a map. You can see the fall run­ning from the high­est to low­est. And to find a key­point, it is the loca­tion where a pri­ma­ry val­ley emerges from the side of the hill and begins to flat­ten out. So if you can imag­ine rocks falling down a hill, at the point in which rocks first start to stop falling down a hill and land, that is a key­point. And if you want to find a key point, if will you hold out your hands like this and press your fin­ger up between your fin­ger and the mid­dle fin­ger, you’ll see a lit­tle dent in your skin. That is the key­point, it’s like a pond, essen­tial­ly. It’s the high­est point in the land­scape where you can hold water. Does every­one get that?

So we can iden­ti­fy a key­point in the land. And then the con­tour line becomes the key­line in the land­scape, which it’s high­est point in the land that can hold water. And once we’ve found a key­point, we can then abstract the idea of val­leys and ridges and actu­al­ly define where it is the val­ley walls start and where does the ridge end. Which if you were stand­ing in the land­scape is quite hard to iden­ti­fy, like where are the walls of the valley…where it shifts from being a ridge to a dale, let’s say.

So, we can iden­ti­fy these two dif­fer­ent types of lev­el in a landscape—ridges and dales. And then we can extrap­o­late out into a much larg­er map. So you can see here that there’s a pri­ma­ry val­ley and then there’s a sec­ondary val­ley, and you have the red line which is the key­line that runs through the land­scape.

What you can then do is then you start to draw par­al­lel lines on the land­scape, both ver­ti­cal­ly up the hill and down the hill from your key­point. And then there’s var­i­ous things that you can do. It basi­cal­ly gives you a log­ic for lay­ing out the land. You can plant trees on these lines. Or you can use a thing called a key­line plow, which is basi­cal­ly a t‑shaped plow that goes into the soil and explodes the sub­sur­face. So when it rains the water runs into the ground and is soaked into the soil.

And what that does is means when it rains… You can see the direc­tions of these arrows ice and it means that the water will run from the cen­ter of a val­ley out to the ridges. It’s not run­ning uphill, but it is run­ning out to the ridges. And water that lands on the ridges will flow into the val­leys. Which means that you get a full cov­er­age of water into a land­scape and it’s far more effi­cient than just let­ting the rain­wa­ter run down the val­ley and cause ero­sion.

And then we extrap­o­late fur­ther, and you end up with, you know, at a high lev­el a key­line plan for the land­scape. Keyline also allows you to dic­tate where you can put roads in order to best pre­vent ero­sion and water move­ment through the land­scape. But essen­tial­ly, if you were look­ing at maps, this is a key­lined plan for the land­scape.

But you can zoom in. And this is an actu­al key­line plan for a farm. So if you were to zoom in on Google Maps, obvi­ous­ly it’s like a frac­tal land­scape because you will find small­er key­points with­in land­scapes. So you can see here this land­scape has got des­ig­na­tions where they’re going to be grow­ing trees; it’s the yel­low. You’ve got the key­line rip lines, which is the blue where the water’s going to go. And you can also see they’ve got places where ponds will nat­u­ral­ly form from rain­wa­ter. And these are known as pock­et ponds rather than large ponds. So if you’ve got a cou­ple of acres you can lay out your land­scape to best opti­mize water flow.

This is the first key­lined land­scape, from 1965. PA Yeomans is Australian—or was an Australian farmer who invent­ed key­line. And you can see here that there’s all the dams on the land­scape hold­ing water and allow­ing for flood irri­ga­tion and stuff like that.

But what does it actu­al­ly mean to talk about a land­scape that has been designed in this way? This is New Forest Farm in the States. And this is what a key­lined land­scape looks like. I think it looks pret­ty cool com­pared to square indus­tri­al farm­ing fields that we’re kind of used to. So this is a key­lined land­scape, and it’s kind of what the future is going to look like, I think.

So on the inverse, in the very short term, what is tech­nol­o­gy bring­ing, and what does say the next ten, fif­teen years look like in terms of tech­nol­o­gy? Well, they’re in the audi­ence today, but there’s terra0 who are based here at Trust. And they are a blockchain start­up that attempts to kind of wres­tle with the ques­tion, can an aug­ment­ed for­est own and uti­lize itself? And behind here is the grow wall for their test stuff that they’ll be doing. Maybe they can speak about that a bit lat­er.

But in order to think about a for­est that is gonna uti­lize itself, it needs a lot of deep sens­ing data in order to inform its deci­sions about… Or, we need deep sens­ing data in order to inform the deci­sions that we need to take about the land­scape. At the moment you’ve got stuff like this which is a soil mois­ture sen­sor from OpenHardware. It’s two AA bat­ter­ies. Very cheap if you buy them in bulk. But they still require bat­ter­ies. And there’s also car­bon sen­sors, soil pH testers, mois­ture testers, all var­i­ous things that you would expect com­ing out of the open hard­ware move­ment. But they’re all indi­vid­ual sen­sors that require bat­ter­ies at the moment.

A small rod-shaped sensor about the size of a pocket flashlight sticking horizontally out of a wooden post.

There’s also things like this, which is the Ebird mon­i­tor, which can be placed around the land­scape and plot­ted on a map. These things can record over a mil­lion hours of sound. Then they run it through machine learn­ing and can iden­ti­fy bio­di­ver­si­ty of birds in the land­scape, because machine learn­ing lis­tens to the bird­song and extrap­o­lates how many birds there are in a cer­tain region, etc. Again, they have to be pow­ered, which is a bit of a prob­lem. So we need to start think­ing about how do we bring all of these var­i­ous sens­ing devices togeth­er, and what does it look like when we do.

Cory Doctorow: Make me a computer that doesn't run every program, just a program that does this specialized task, like streaming audio, or routing packets, or playing Xbox games, and make sure it doesn't run programs that I haven't authorized that might undermine our profits.

So we’ve kind of reached a point in 2018 where we’ve reached the end of general-purpose com­put­ing. If you’re not famil­iar with the term, then Cory Doctorow wrote a fan­tas­tic essay in 2012 about the end of general-purpose com­put­ing, and you can read the dan­ger up top. Basically it’s the idea that you can’t run code on a device unless it’s either signed, or you have per­mis­sion to do so.

Some of the prac­ti­cal impli­ca­tions of this is like, self-driving cars can only run code that is signed because you would­n’t want peo­ple you know, installing mod­ules onto self-driving cars and delib­er­ate­ly dri­ving into peo­ple rather than avoid­ing them, for exam­ple.

The sec­ond part of the end of general-purpose com­put­ing is a thing called ASICs. Does any­one know what an ASIC chip is in the audi­ence, hands up? Alright, not that many. I’ll seek to explain. So an ASIC chip is a chip that is only designed to do one thing. So it does­n’t run code in the same way as you would assume code to be run, where you can just run all sorts of com­pu­ta­tion and code. An ASIC chip will only run what it’s phys­i­cal­ly designed to run. And in 2013, this is the Butterfly Labs bitcoin-mining rig. It was one of the first kind of dri­ves for­ward in the open source ASIC space. Because all that these chips did was mine Bitcoin. They could­n’t do any­thing else. They’re mod­i­fied GPU chips.

But what it’s meant in this kind of push­ing for­ward of chip design is that we now have things like this, which is Google’s TensorFlow. These units only run neur­al nets. So if you’re doing machine learn­ing, they don’t run any oth­er code except the code required to train neur­al net­works.

Advantages of this is that the code only runs on the chips. It also means you get a mas­sive pow­er sav­ing, because it can only do what you’re ask­ing the chip to do and it does­n’t have all of the over­heads of try­ing to do com­pu­ta­tions in a gen­er­al way. It’s very spe­cif­ic and tar­get­ed.

Photo of an iPhone logic board, with various chips identified.

One of the oth­er places that you’ll find ASIC chips every­where is inside mobile phones. And it’s very unclear where iOS on your mobile phone ends and the hard­ware begins. So for exam­ple, all of your MP3s, MPEGs, JPEGs, are all decod­ed in hard­ware on tiny chips on the moth­er­board, not in soft­ware. So, those tiny chips only decode video, for exam­ple. And this is what is also dri­ving the ASIC space, is the minia­tur­iza­tion of mobile phones.

Dr. Charles Reid: LoNo (short for low-power no-power) Computing is the idea of building a computer that is extremely low power. It is the attempt, inspired by nature, to build efficient computers.

In the ear­ly days of solarpunk, there was a talk giv­en on low- or no-power com­put­ing. So as you can see here there’s like, a soil clock. I’m sure you used to make pota­to clocks as a kid, where you could pow­er a pota­to. Well you can also do the same thing with soil. You can run devices from soil.

So what do deep sens­ing devices look like when they’re that low-power that you don’t need to have a bat­tery is a ques­tion. Can we get there? Maybe. But we need to have a think about if we’re gonna be deploy­ing all of these sen­sor devices on a land­scape, what does it kind of look like? How often you have to go change a bat­tery? If you’ve got like thir­ty hectares of land, there’s no way that you want to go walk or get on a quad bike to go to the oth­er end of your land if you’re a farmer to change the bat­tery in a sens­ing device. Because that’s like— Especially if it’s like once every six months. That’s mad­ness. People are too busy on farms to be chang­ing bat­ter­ies in devices.

So when we try and put these things togeth­er, the idea of land as plat­form and deep sens­ing, what does it look like? So I heard a bit of… One of the most ridicu­lous things I’ve ever heard I heard the oth­er day, a blockchain con­fer­ence, where some­one said that the inven­tion of the blockchain is our gen­er­a­tion’s pyra­mids. But I would like to con­tend that the tri­umph of our civ­i­liza­tion, with ASIC chips and so on and so forth, is that we will teach minute bits of moun­tain into think­ing with cap­tured light­ning. Because they will be think­ing machines at that point. Not in the way that we per­ceive think­ing in terms of AI, but it will lit­er­al­ly be a slab of mate­ri­als that only do one thing and they think. And they give us sens­ing data.

Various Palette Gear modules: a button, a slider, and a dial, all small rectangular blocks with contacts visible around their sides where you'd connect them.

But what do these devices look like? Well, I don’t know if you make music but there’s like Palette Gear is prob­a­bly like the nicest design objects out there. These are MIDI con­trollers that you can just click togeth­er and build a board of all of your dif­fer­ent­ly MIDI con­trollers.

So I’m imag­in­ing that sen­sor plat­forms, or deep sens­ing plat­forms, will be one plat­form that goes in the grounds and then you can just con­nect mod­ules on depend­ing on what sen­sors you want. And obvi­ous­ly when you put a sen­sor on you’re going to have a deep­er pow­er load on the par­tic­u­lar sen­sor.

Sattelite map of a wildlife area, with various map points indicated and variously colored lines connecting them.

Bioacoustic Wildlife Monitoring, Green Valleys Watershed Association

So, the Ebird instal­la­tions kind of look like this. You can’t real­ly see the map but you can kind of see how it works. So at the moment it’s all pow­ered by base sta­tions. And each one needs to be pow­ered and there’s wifi net­works that then ship all the data back­wards and for­wards. And because they know where they are in the land­scape they can also tri­an­gu­late where the birds are on the land­scape.

So one of the appli­ca­tions this, and why I’m here speak­ing at Peer-to-Peer Web is mesh net­works. What does it look like when we start to think about con­nect­ing, or plan­ning for, sen­sor data with mesh net­works that allow for much smoother com­mu­ni­ca­tion routes in terms of its infor­ma­tion? What hap­pens when mesh net­works start think­ing in terms of land as plat­form?

And this is where I feel like I went off the deep end a lit­tle bit when I was mak­ing this slide, because it kind of looks like art rather than a dia­gram. But, the idea here would be mesh net­work pro­to­cols have to have an under­stand­ing of how we’re going to be lay­ing out the land. Because if that’s where I live, there’s no way I want to go all the way up there to change a bat­tery in a router. So how do these mesh net­works work in the land­scape? How often do they ping each oth­er, how often do they pass infor­ma­tion through the mesh? How often do you even need infor­ma­tion from cer­tain sen­sors? Is it once a week, is it once a month? All of these things can be baked into the pow­er con­sid­er­a­tions of how mesh net­works work.

And yeah, so that’s the final slide. And that’s land as kind of the…the land as plat­form. Thanks.

Further Reference

Peer-to-Peer Web Berlin event page

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