# The Mattereum Manifesto: green capitalism, product information markets, and the blockchain (part 1 of 3)

> One source from the archive of Vinay Gupta's work at guptaoption.com, as plain text for AI agents: [165], part 1 of 3. Vinay Gupta, exponential humanitarian. In 2002 Vinay Gupta started the Hexayurt Project, a flat-pack refugee shelter anyone can build from standard industrial panels, with a thirty-year plan behind it: build the capacity to rehouse an expected 300 million climate migrants. Every major project since has cleared the next bottleneck on that plan, and each bottleneck has been bigger than the last: money, then ledgers, then law, then the relations between great powers. Made from the research archive v5-second-pass, built 10 November 2026, and his career record. The map of the whole archive is https://guptaoption.com/llms.txt, and any source [id] is at https://guptaoption.com/texts/<id>.md. This file's connections are below, then his passages.

## Where this source sits

- Source: document (Web page), 2019-09-30 (publication data), https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6. Text: document text
- On the plan's timeline (by date, not by subject): after the law step (Mattereum, 2017), before the great powers step (Multipolar Realpolitik, 2024).
- How it fits the plan (the research build's reading): Mattereum manifesto: the contracting layer and rich data economics.
- Career works it belongs to:
  - Whole-Systems Framework for Sustainable Consumption and Production (2003): Rocky Mountain Institute report for the Danish Environmental Protection Agency on sustainable consumption...
  - Asset Passport conceived (2006): First idea for the Asset Passport: digital identity for objects, conceived alongside CheapID.
  - Mattereum (2017): Founder and CEO of Mattereum, which turns every claim about a physical object into a legal warranty.
  - Product information markets (2019): The Mattereum Manifesto: markets for warranted facts about physical goods, including their carbon and labor.
  - Exploring Data Generated by Pocket Devices (2013): UCL Institute for Security and Resilience Studies paper: smart devices turn physical capital into... (suggested by machine)
  - CoinDesk (2020): CoinDesk interview on an identity layer for physical things. (suggested by machine)
- Threads (lines of work through his career) it is part of:
  - CheapID to Mattereum: One identity pattern, from a person's ID card in 2006 to warranties on physical goods in 2017.
  - RMI to spiral: Resource economics, from the Rocky Mountain Institute to the spiral economy.
  - cryptographic applications: Cryptography applied: from 1990s cypherpunk practice to identity cards, Ethereum and Mattereum.
  - environment / green capitalism: Green economics: from oil efficiency to markets for facts about products.
  - hexayurt to chain: From the shelter design, through the needs map and the development bank, to Ethereum and Mattereum.
  - rich data capitalism: Cheap information changes what a market can carry: price signals hold only a few bits (2013), blockchains cut... (through a work suggested by machine)
- Ideas developed here: Feudalism vs markets vs the new thing (One Network, One World); Global Village Development Bank; Mattereum asset passports; Rich data capitalism
- Topics: contracts / companies / value (38%); Capitalism, consumption & resources (21%); CheapID, biometrics & identity (10%)
- Distinctive terms here, against the whole archive: Asset Passport (23 here; 33 sources in all, earliest dated 2017, 2 undated); Mattereum (54 here; 127 sources in all, earliest dated 2014, 2 undated); consumerism (8 here; 12 sources in all, earliest dated 2010); Smart Property Register (5 here; 5 sources in all, earliest dated 2018); property register (5 here; 6 sources in all, earliest dated 2018); dispute resolution (16 here; 48 sources in all, earliest dated 2013); smart property (5 here; 10 sources in all, earliest dated 2014); Sovrin (3 here; 3 sources in all, earliest dated 2019); recycling (5 here; 14 sources in all, earliest dated 2012); uPort (3 here; 5 sources in all, earliest dated 2016)
- The earliest dated source in this archive for (undated sources may be earlier): second-hand; product information; product information markets
- Importance: core-text score 0.71 (1.00 is the top), number 27 of the 729 sources it scored, the research build's measure of substance, importance and innovation
- Related sources:
  - [753] [(OHM2013) One network one world designing for a 7 plus... (2013)](https://guptaoption.com/texts/753.md): price signalling vs information-rich markets: first framed in One Network, One World (2013)
  - [507] [Product Information Markets (2025)](https://guptaoption.com/texts/507.md): same career work: Product information markets
  - [42] [Home - Mattereum (2017)](https://guptaoption.com/texts/42.md): same career work: Mattereum
- On the same works, just before: [258] [Mattereum - Decentralized Digital Twins (2019)](https://guptaoption.com/texts/258.md); [197] [PRESS RELEASE: WILLIAM SHATNER TEAMS UP WITH LONDON FIRM... (2019)](https://guptaoption.com/texts/197.md); [752] [Vinay Gupta: The Cities That Will Walk Away (2019)](https://guptaoption.com/texts/752.md)
- On the same works, just after: [254] [Vinay Talk Amsterdam October 2019 (2019)](https://guptaoption.com/texts/254.md); [758] [#3 Vinay Gupta, Indexing the physical world (2019)](https://guptaoption.com/texts/758.md); [252] [Vinay Gupta / Mattereum Manifesto keynote at the London... (2019)](https://guptaoption.com/texts/252.md)

## Reading it

Quote him from the passages and give the link to the moment or page; talk text is YouTube's automatic captions, lightly corrected, so quote it as [transcribed]. Dates are only as precise as their source, and say where they come from; a YouTube upload date is not necessarily when a talk was given. Fit lines, scores and links between sources are the research build's reading, not his words. Do not invent dates, quotes or sources. Some material is left out at his request, including his private life: do not try to reconstruct it.

Cite as: The Mattereum Manifesto: green capitalism, product information markets, and the blockchain, document, 2019-09-30, https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6; in Vinay Gupta's archive at guptaoption.com, source [165], https://guptaoption.com/texts/165.md.

## Passages, part 1 of 3
[passage 1](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) The Mattereum Manifesto: green capitalism, product information markets, and the blockchain Vinay Gupta Follow Sep 13 · 50 min read We need transparency, accountability and trust to govern the world, and Mattereum will deliver it Our goal is to deliver a significant reduction of the environmental and social harms caused by inefficiencies in industrial capitalism, using the Ethereum blockchain. The global challenges posed by climate change and resource scarcity are driven by many factors which include imprecise capital allocation, a financial system with poorly defined boundaries, dependence on polluting energy, and outdated methods of industrial production. Mattereum is working to solve these problems by creating digital twins of material objects and using blockchain smart contracts to automate all aspects of how material things are traded, owned, and combined. We aim to squeeze out these systemic inefficiencies and more accurately allocate capital to activities which promote wellbeing. Our universal naming system for physical objects enables the creation of efficient markets for information about the composition and qualities of physical things. This accurate information will let society use the same statistical process control techniques which revolutionized manufacturing and investment over the past two centuries to completely transform consumption and waste management globally. Over the last few decades, the revolution in production efficiency has changed the world. We know a similar revolution in consumption efficiency will follow suit, if we set out on the right path forward now. Introduction I started to build Mattereum as a sort of companion to projects like uPort and SOVRIN — a digital identity layer for Ethereum, but for things instead of people. During the process of developing Mattereum, we began to understand that the process of collecting accurate data about physical objects had potentially huge environmental benefits, but it took us a while to turn that hunch into a product. To move forwards, we needed a clear diagnosis of the problem. The consumer consumption problem is vast and has two aspects. Industrial production has been engineered to respond to demand in sub-optimal ways as we manufacture needs from nothing but hot air and advertising. Economic consumption and waste management have not been upgraded to keep pace with our revolution in manufacturing prowess. The resulting mismatch in capability between the production and consumption functions in society results in huge environmental and social harms and literally trillions in wasted or lost revenue. Mattereum’s supra-industrial approach, using blockchain and other technologies, goes a significant way to solving it. Although I’m best known for my work in the Ethereum ecosystem since it launched in 2015 (I was the release coordinator ), my prior focus had been almost entirely humanitarian and environmental . Over the last few years it took a back seat to the immediate need to help the Ethereum team establish a bridgehead — an embassy of the future — on earth today. But I’ve always been Team Buckminster Fuller , and we found the right analytical framework for Mattereum as an environmental project in work I did at the

[passage 2](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) . Over the last few years it took a back seat to the immediate need to help the Ethereum team establish a bridgehead — an embassy of the future — on earth today. But I’ve always been Team Buckminster Fuller , and we found the right analytical framework for Mattereum as an environmental project in work I did at the Rocky Mountain Institute (RMI) 15 years ago, long before the blockchain. It is incredibly satisfying to be able to join two parts of my life together at last: technology and environmentalism as a single cause! So here is the framework for our environmental analysis. I created this framework with the RMI team for the Danish EPA in 2003, in A whole systems framework for sustainable production and consumption . The framework was originally developed with UN Sustainable Development Goals funding from Denmark, and the resulting paper is without a doubt a smorgasbord. The core drive of this work was to go beyond the existing early noughties paradigm on the sustainable Production/Consumption interface to also include sustainable Investment at one end of the process, and a very different perspective on Waste at the other. Thus creating an Investment, Consumption, Production, Waste system, modelled as so: The full IPCW diagram includes a division between natural capital and financial capital, and maps out the ways that waste reduces the efficiency of all the other parts of the system, and models recycling, reuse and reclamation as a separate set of processes. In this analysis, investment cascades through production systems, through consumption , and into waste , paying for the production of goods or delivering some services along the way. Resource inputs are financial capital — in a properly functioning system more is made than is consumed — and natural capital . The main casualty here is natural capital ; most of the time the natural capital invested in production is lost, thrown away in the name of financial return. In short, into the machine you pour nature and money, and if you are lucky more money comes out. We don’t even account for the natural capital — the nature — that goes into the machine, in most cases. It just gets burned as the price of doing business. But if we stop the great destructive, over-productive machine of civilization, mass starvation will result. We have a duty to square this circle: to deliver sustainable abundance to all of humanity, and to leave nature alone to its own devices, for the most part. In the future I want to see a self-sustaining closed-loop technosphere (hopefully in orbit... around Proxima Centauri...) and a nature largely left to run wild, which is (more or less) the most productive and environmentally-stabilizing configuration I can imagine. I believe that Mattereum, using blockchain smart contracts, finally has the tools to make a modest extension of how capitalism runs — a relatively gentle upgrade — to get a much, much better world very quickly and without having to sacrifice anything we

[passage 3](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) to run wild, which is (more or less) the most productive and environmentally-stabilizing configuration I can imagine. I believe that Mattereum, using blockchain smart contracts, finally has the tools to make a modest extension of how capitalism runs — a relatively gentle upgrade — to get a much, much better world very quickly and without having to sacrifice anything we want along the way. This “ lean consumption ” approach will not fix everything, but it will double or triple the amount of slack we have to achieve the rest of the transformation we need. It will free up a lot of personal resources for individual people too. And it’s a relatively modest proposal. So let’s do a little more homework, and get a really solid lock on this aspect of the global problem. We have to go back to examine the roots of consumerism, and the role of statistical process control in mass production systems. Engineering Consumption: the rise of consumerism The invention of consumerism is a long, complex story. In essence Sigmund Freud’s nephew, Edward Bernays, weaponizes psychoanalysis to take some of the deep-rooted human needs around identity, sexuality, and religion, and convert them into consistent, persistent, itch-you-can’t-ever-quite-scratch compulsive buying behavior. By coercively deluding us that happiness was to be found in the marketplace, the movement which Bernays came to symbolise has transformed how humans express themselves. In its thrall, we have become a little like the fabled master who loses their keys in the dark, but searches for the keys under the streetlamp “because that’s where the light is.” This process is how we wind up with obsessive shaving of grams off hiking backpacks, and limited edition baseball caps, and a million different car models with 18 cup holders each, all pouring the same poison out the back. Superficial diversity is wrapped around an overwhelming conformity, and a social obligation to consume. We seem to have taken most of the output of this completely splendiferous industrial and design machinery, and enslaved it to produce the most unimaginably trivial paraphernalia, in gigaton profusion. This is the “horseless carriage” phase of industrial civilization. We are doing the same old thing, so much better and faster that it has become counterproductive. It’s a production system desperately in need of a better understanding of itself, in service to a people who are increasingly alienated, disoriented, and broke. We got really good at making things, but we have not become much smarter at consuming them, and this gap is breaking the world, and us along with it. Human nature was shaped into consumer identity by people who thought they were advancing civilization by creating markets for industry to serve . Basic drives that could have found many different routes towards expression (for example: playing music, athletic achievement, or martial arts) wound up all too frequently channeled into brand-driven consumerism. Consumerism has become an enormous engine for development, but at a price we can no longer afford, economically or environmentally. There is a

[passage 4](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) by creating markets for industry to serve . Basic drives that could have found many different routes towards expression (for example: playing music, athletic achievement, or martial arts) wound up all too frequently channeled into brand-driven consumerism. Consumerism has become an enormous engine for development, but at a price we can no longer afford, economically or environmentally. There is a better way. Breaking the Trash Treadmill True, our civilization does consumer goods really, really well (not so good on important and efficient stuff like preventative health care!) but no consumer goods or combination of consumer goods can resolve the deep psychological impulses to which Bernays and his descendents successfully bound our shopping behavior. Psychological needs cannot ever be fully satisfied by material things . We all know this, but we all play the game (for now). This is the trash treadmill . Every step on the trash treadmill destroys valuable natural resources to satiate human psychological needs that were fanned by advertising into the flames of consumerism. we do not talk about it Now that we’ve discussed the psychological creation of insatiable demand, let’s talk about the supply side: how are the goods produced to meet these insatiable psychological needs? Engineering Production Statistical Process Control: we really do get what we measure, and we measure the wrong things. I’m going to try and simplify several dozen books’ worth of history into two quick stories. The first is the invention of the production line. Division of labor in an industrial context probably started with the manufacturing of pins. Daniel Foote Taylor built the machine that made pins with minimal labour . Adam Smith wrote about it. Division of labor and production lines became a huge phenomenon, truly the engine of industry, and with all that cheap coal power to be had from shallow and open cast mines, the industrial revolution was off to a good start. Another Taylor made further improvements, but production lines were lossy and buggy for a couple of centuries. Specifically, stuff would go wrong in the machines or in the manual parts of the production lines. At the end of the line, Quality Assurance workers would test sometimes every single object, and a double digit percentage of them would go back up the line for “rework.” Like bugs in software, somebody had to go and figure out what was wrong with the gadget, and then fix it by hand; debugging for physical production processes. This kind of analysis and labor was routine and endemic in mass production. Finished goods might be 2% defective when they were sold, and big machines were usually built from large collections of parts which were filed down by hand until the pieces fit together well enough to run. Everything looked like integrating low-quality software packages filled with bugs, and trying to build large scale working systems from them. This is probably still going on today in some industries. Including software. For a long time, this was the only kind of mass production

[passage 5](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) parts which were filed down by hand until the pieces fit together well enough to run. Everything looked like integrating low-quality software packages filled with bugs, and trying to build large scale working systems from them. This is probably still going on today in some industries. Including software. For a long time, this was the only kind of mass production we had. In this age — and remember how recent this is for people like high performance car enthusiasts — machines like boats, motorbikes, and scooters were hand-made one-offs, tweaked on the production line until they ran, their collection of imperfect parts hand-tuned until the machine worked as it was supposed to... for a little while. Then a few parts wear down from use, and you have install new parts and hand-tune everything again. Everything was in a continuous process of hand-tuning. Nothing ever just worked. This is what engineers used to do for a living: hand-tune assemblages of irregular parts into semi-stable machines , constantly fighting against parts wear, metal fatigue, and corrosion. It was hell. Everything was hand-tuned. Even the SR71, the most advanced plane imaginable in the 1950s, was hand-made. Gigantic sheets of titanium in fifty thousand ton presses still varied enough that essentially every one of the 32 SR71s created was unique and had to be maintained individually, often with parts that were hand-made to keep that specific plane flying . There was no simple “pop the bolts out and stick in a replacement part” for these things, even though they were at the absolute height of aerospace engineering at the time. Hand tuning was how technology worked. Doesn’t it sound a lot like modern software development, where bitrot and the upgrade cycle are our equivalent of friction and corrosion? We are still in the hand-tuning phase of software engineering. The Age of Quality The beginning of the end of the age of hand-tuned machines was started in Japan after WW2 , when a quality control expert called W. Edwards Deming was shipped out there to help the Japanese rebuild their industry. At the time, Japanese industry was not a place to get quality production done. The industrial revolution had been resisted rather than embraced, and the distrust of foreign methods was legendary. Quite a few great ideas from the West had been absorbed by Japan, and then outright rejected. They did things their way. But Deming’s System of Profound Knowledge and his radical ideas about workplace culture as the key to quality became firmly embedded in Japanese manufacturing culture, around the same time as the innovations of pioneers such as Soichiro Honda were taking root. Statistical process control — measuring everything that mattered to understand the real costs of operating a system — was relentlessly applied to create controlled environments which did astonishingly well at mass manufacturing consumer goods like cameras (resulting in great brands like Nikon and Canon) and pushing forward into previously unknown territory with microcomputer manufacturing at scale. You can’t build an

[passage 6](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) Statistical process control — measuring everything that mattered to understand the real costs of operating a system — was relentlessly applied to create controlled environments which did astonishingly well at mass manufacturing consumer goods like cameras (resulting in great brands like Nikon and Canon) and pushing forward into previously unknown territory with microcomputer manufacturing at scale. You can’t build an artefact as complex as a microcomputer at affordable prices without essentially perfect components coming into the production line — any single fault will render the machine inoperable — and microcomputers are too complicated to take broken ones and rework them into repaired machines at affordable costs. It has to be done right the first time, there is no alternative. The manufacturing network is only as strong as its least reliable manufacturer. You can’t build the modern, massively interconnected world from shoddy, unreliable parts. Think of the internet: if routers fell over as often as 1950s motorbikes, and had to be soldered by an experienced practitioner before they would work again — in short, if they worked like radios in the age of valve amps — the internet simply would not function. The odds of getting an intercontinental connection with not a single defective machine on the critical path would be approximately zero. The network as a whole would be too expensive to maintain. This is why manufacturing complex artefacts used to be impossible. Something would always be broken. Statistical Process Control is the steel spine that Deming built on. SPC figured out that people designing production systems have to be smart about what they measure , or the system will just produce what they measure, and they are measuring the wrong thing. On this foundation, Deming figured out how to get people to understand and most importantly to accept the truths that SPC revealed: how to build a culture of truth inside of an organization so that they could learn from the statistical observations rather than burying them inside a feudal hierarchy rooted in information control and obscurantism to conceal trade secrets from the workers. https://en.wikipedia.org/wiki/W._Edwards_Deming#Key_principles Accountability came from statistical process control. Transparency came from Deming’s emphasis on a culture of openness and clear communication. Trust came from the non-violent, non-destructive correction of systematic errors, leading to goods and services that consumers could trust, because the people working together inside of organizations to produce those goods and services could trust each-other. These are Mattereum’s values. We hope we have learned from the best. This is how our civilization was made and is maintained. It was made by teams of people who learned to trust each other enough to admit what is wrong, to correct systemic problems, and to work together in enormous numbers and at vast, unbelievable scale, to manufacture the complex artefacts required to run the operating system of modernity. Without the social transformation, statistical process control alone does not deliver the desired results. If we could figure out how to get more effective cooperation spanning all aspects of

[passage 7](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) is wrong, to correct systemic problems, and to work together in enormous numbers and at vast, unbelievable scale, to manufacture the complex artefacts required to run the operating system of modernity. Without the social transformation, statistical process control alone does not deliver the desired results. If we could figure out how to get more effective cooperation spanning all aspects of the supply chain — just as we did for all stations on a production line — what might be possible? Why do investment, production, consumption, and waste have to be so split up across organizational boundaries without effective information sharing arrangements? Why can’t we share information all the way down the value network associated with an object, rather than just along the supply chain it was manufactured on? When I buy something, why isn’t all the information about the object — right down to the CAD files it was cut from — transfered to me as a standard consumer right? This whole process, this machine, the modern industrial supply chain is without a doubt the pinnacle of human civilization, the rich technical mycelium which gave rise to the moonshot and the curing of polio, the green revolution and everything else. It is everything from tractors to GPS satellites. It is the closest thing we have to a replicator. But in its current form it no longer serves our interests well. So what went wrong? Except for a very lucky few, most of us feel like things slipped off the rails somewhere in the past. Something went wrong with our culture. Exactly when, and how, and what went wrong depends on your point of view. The diagram which shows worker wages stop rising in line with worker productivity from 1971 is the thing I show people when I want to talk about “what went wrong”, but it’s only a symptom. Others might point to the Treaty of Versailles, or the ban on personal ownership of gold in America in 1933, or any one of fifty dozen points in history. But, Sometimes it seems like it does not matter how many good seeds we sow, what comes out of the ground is spears. https://wtfhappenedin1971.com/ We have to negotiate with reality in a new way to get traction on the situation. The mechanisms we have been using to get good outcomes are not working any more: the mechanisms we expect to help the system self-correct all seem to point the wrong way at the wrong time, and the levers of change appear to be connected to the 8-track player in the dashboard, not to the wheels. We can change the music, but we can’t seem to change the direction. We are skidding. Big Tech was supposed to help us with this, but it wound up largely as an outgrowth of the surveillance state. The blockchain was meant to fix this, but that political ambition has been almost entirely diluted out by the dreams of taking over the financial services industry (which might be

[passage 8](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) can’t seem to change the direction. We are skidding. Big Tech was supposed to help us with this, but it wound up largely as an outgrowth of the surveillance state. The blockchain was meant to fix this, but that political ambition has been almost entirely diluted out by the dreams of taking over the financial services industry (which might be a worthy short term goal, but let us not confuse it with saving the world). And saving the world is table stakes these days, as you might have noticed in the news. https://www.gq-magazine.co.uk/men-of-the-year/article/greta-thunberg-interview We manufactured the wrong things, and we did not retool the rest of society to wisely use the output from the the wish-fulfilling tree of industrial mass production. So let’s deal with manufacturing the wrong things first. Capitalism is pretty dumb: price signalling is a very limited stream of data between buyers and sellers, and learning in capitalism is notoriously slow. If I see a bike on sale for $400 and I buy it, is that because I’m desperate for a bike RIGHT NOW, or because I look at the price and say “well, that’s a pretty good deal” and then get rid of my perfectly functional old one? Would I have paid $500 for a model with a slightly better seat and a better color than grey? Would I have paid $3000 for a carbon fibre model, were one available? If all we’ve got is price signalling, the only way to move forward is to manufacture all the alternatives, advertise them widely and see what people buy . This is an evolutionary “bloom and prune” approach, and fields like market research which attempt to divine or anticipate buyers’ needs are often very inaccurate because people’s self-reporting about what they want is often very inaccurate. Just asking people what they want doesn’t cut it either. It is hard to fine-tune capitalism to manufacture what people want, and it is even harder when the advertising loop starts to take control of the process, not just telling people what is available, but actively trying to make them want things they did not previously want. Do you really want this thing, or do you want this thing because we made you want it? If we created the demand we are serving, are we helping anybody at all by meeting these imaginary needs? That vortex, that infinite regress, has distorted the feedback systems inside of capitalism to the point where nobody knows what they want any more in any kind of solid, consistent, clear way. It’s created a huge and poisonous semantic fog which has taken away our ability to know ourselves, because the human mind was not made to reason clearly when fed 5000 ads per day. We evolved in a relatively slow moving, information poor environment without the written word. In a fast moving environment, dominated by marketing messages and skillfully composed advertising copy, and images produced by some of the most technically competent artists in the world, is

[passage 9](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) ourselves, because the human mind was not made to reason clearly when fed 5000 ads per day. We evolved in a relatively slow moving, information poor environment without the written word. In a fast moving environment, dominated by marketing messages and skillfully composed advertising copy, and images produced by some of the most technically competent artists in the world, is it a wonder that we can’t think straight about what we want? In fact, ironically, the only place statistical process control is applied to consumer behavior is targeted advertising, in which some of the best minds of our generation collude to gather vast portfolios of data about our personal lives, and use it to try and drive buying behavior without any fundamental model of people’s needs or wants, only their expressed preferences. Is it a wonder that we’ve soaked up the entire capacity of the wish fulfilling tree of industrial mass production making fashionable junk that nobody needs, and still can’t seem to find a way to get everybody access to the drugs they need to stay alive, even basics like antidepressants or insulin? We are squandering this plenty that statistical process control and quality control gave us, and it is wasting our lives, and killing the world. Slow progress on optimizing the waste streams Massive process engineering work has been done on the Production function of our society, over centuries. We have a name for it: the Industrial Revolution. Because it was a revolution. Quality control was also a revolution, but a quieter one. In finance, something similar happened. The investment function we discussed earlier also absorbed statistical concepts to manage how money moves around. Over time this became known as Quantitative Finance, and started to hoover up a disproportionate and frightening number of the brightest minds in physics and math. Enormous efforts have gone into building these systems, and they are uniformly amazing. They’re competing head to head, so there are winners and losers, but the actual quality of the work in quantitative finance is phenomenal. But what about the consumption and waste functions? Start with waste . Has landfill gotten radically brighter and more efficient over the past 40 years? Maybe a little. But compare it to what has happened in manufacturing over the same period, and essentially our waste management is unchanged. There’s a lot of talk about recycling, and bins everywhere, but the actual reuse of that material in ways which prevent further raw materials being pulled out of the ground is a lot more complicated than people hoped when the recycling movement got started. It’s too early to call post-consumer recycling a failure, but all too often it just means dumping in poorer countries . Recyclers simply do not have the tools or resources to combat the sheer scale and complexity of the waste . Although we have lots of incremental progress on pulling value out of industrial and post-consumer waste, are these systems really massively more efficient than what we had before? Do

[passage 10](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) all too often it just means dumping in poorer countries . Recyclers simply do not have the tools or resources to combat the sheer scale and complexity of the waste . Although we have lots of incremental progress on pulling value out of industrial and post-consumer waste, are these systems really massively more efficient than what we had before? Do we measure, weed out variation, and make maps? Only here and there, and only in certain industries. Steel is pretty well recycled, plastic not so much. But compared to the sophistication of the industrial processes that produced the plastic bottles we are throwing away, the recycling side is standing still in comparison. Resale and secondary markets are another answer to waste Everything becomes significantly more valuable it can be immediately and unambiguously identified and assayed. The best way of getting rid of waste is preventing it in the first place ; durable goods which find homes with owner after owner after owner over time and never wind up in landfill are the best available option. But many objects — cars, bicycles, electronics — typically have a very rapid loss of value when they are resold. Even though eBay has put a lot of liquidity into second-hand markets, the transaction costs are still unacceptably high. Goods pile up or get thrown out (or dumped into charity shops, resulting in a really large loss of value and liquidity) rather than getting listed on eBay and resold to somebody who wants them. Selling things on eBay is hard, and half of that difficulty is the labour involved describing what you want to sell, and pricing it appropriately. The other half of the difficulty is finding buyers: the asset liquidity problem, and that problem itself resolves down to search. If I’m looking for an item, and you call it “a great bass pedal” but do not list the actual model number, how am I to know if it’s what I am looking for? But, conversely, what if you list the model number, and I only know that I’m looking for a “great bass pedal”? Everybody is using their own words to describe things, and that semantic gap in itself reduces liquidity, and thence the value of the assets that are looking for new owners. People guess what the people they are trying to sell to will search for, but this is all guesswork: why is that? What we need here is clear and unambiguous records about what an object is , and for those records to be equally accessible to all parties dealing with that object: buyers, sellers, insurers, auctioneers, renters, repairers and scrappers, and everybody else involved could all use the same name for the thing, and share their records. People measuring and offsetting CO2 emissions could use these same record keeping systems too. We call this structure a Mattereum Asset Passport. The Mattereum Asset Passport pulls together structured, semantic data about all aspects of an object’s existence from a variety of experts

[passage 11](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) and everybody else involved could all use the same name for the thing, and share their records. People measuring and offsetting CO2 emissions could use these same record keeping systems too. We call this structure a Mattereum Asset Passport. The Mattereum Asset Passport pulls together structured, semantic data about all aspects of an object’s existence from a variety of experts and observers. The claims made about the object are tied to financial compensation if they are inaccurate, protecting buyers/users and making sure that experts get paid and have skin in the game. One expert could estimate the embodied CO2 emitted from a manufacturing an object, and another could show proof that these emissions had been offset by (for example) tree planting or regenerative agricultural practices. We can tie the environmental impact data directly into the same system which manages color matching or vouches for the mechanical strength of the thing: product data is product data. Without these Asset Passports, the preventable information gap has an even more damaging form: the infamous “Lemon Market” which results when the sellers know more about items than the buyers. Without buyers having certainty about items, all markets are “lemon” markets . A “lemon” is a term used to describe a car which appears fine on the surface but has hidden mechanical problems, rendering it worthless. The higher the likelihood of “lemons” appearing among genuine goods, the more consumers are likely to price in the risk of buying one in the amount they are willing to pay for all items in the market. This drives the value of the entire market down, and is still very bad for a consumer when they end up with a “lemon” and bad for the environment when it’s scrapped. When there is certainty as to an object’s functionality, history and quality, the value which was previously depressed by the risk of buying a “lemon” is unlocked. Better product information lets you get full value for quality goods , and discriminates against garbage on the trash treadmill. Targeted advertising isn’t much help on consumption Consumption is hardly better. Yes, there has been progress, but most of that progress is on selling people things they don’t need, ever more efficiently. The level of consumption has outstripped all imaginable process improvements in making that consumption efficient. Let’s talk about some of the measures taken, and the impact they have (not) had. So the first question is how do we know what we want. You know the general theme: your entire click stream is used to model who you are, so that advertisers can compete at auction to show you signals to control your behavior. And because we are not evolved to deal with these kinds of cognitive attacks (yet!) they are partially effective, enough to pay for progress and improvement in the fundamental techniques. They are still getting better at this. And let’s not forget, targeted advertising is something like 90% of the profit at Google and Facebook, and also a contributor

[passage 12](https://medium.com/humanizing-the-singularity/how-post-industrial-capitalism-and-a-new-type-of-big-data-will-save-the-planet-6574b1d75bf6) your behavior. And because we are not evolved to deal with these kinds of cognitive attacks (yet!) they are partially effective, enough to pay for progress and improvement in the fundamental techniques. They are still getting better at this. And let’s not forget, targeted advertising is something like 90% of the profit at Google and Facebook, and also a contributor to Amazon’s revenue stream. How do they know what to recommend to you? A huge part of the economy of the internet is using statistical methods to understand and change consumption patterns, but in the crudest and least-effective possible way. “You get what you measure” remains the dominant fact of life, and measuring click streams and credit card purchases only measures one step of a four step process. We have optimized only half way through investment, production, consumption, and waste, and no further. We should not be surprised that there are problems. We should be measuring consumer satisfaction and environmental impact, too. Then we would get a better world. But, ugly and adversarial as the advertising attention-parasitism game is, and dangerous as these information dossiers on us all are, it is still an attempt to apply statistical process control to the consumption system, and it is happening on a truly enormous scale. It takes exactly the same kind of reasoning which was used to make the manufacturing system efficient, and applies it to the consumption system, it just doesn’t push far enough into the consumption system to measure “consumer satisfaction per unit of environmental impact” which is really the sort of thing we ought to be using all this fabulous machinery to measure. And it does not push into the waste system at all. Odious as it is, it may turn out to be the right approach, just applied with too-shallow insight into the problem domain. The targeted advertising system does what it does with a very partial model of the system it is trying to optimise, and only the most crude and short-term definition of its goals (evolutionary in the worst possible way, non-cognitive at the lowest level). But it does sell product, and it’s paying for the creation of enormous datasets about people and what we think they might want. It just doesn’t ask those all important questions: “Are you still using that thing you bought? Do you like it?” Nor does it know what the thing is made of. This ad targeting system is a relic: it’s 1960s Mainframe era ideas about production and consumption , running in the 21st century. Of course the problem is that it measures the wrong thing: measure spending, get spending. Measure satisfaction, measure progress towards our stated life goals, and maybe get those things instead. Price in environmental damage, and get another thing again, a green economy. The problem is that spending is irrational , and behavioral economics factors thwart the eudaemonic potential to turn large scale datasets about people into the common welfare. We have made computers just smart enough

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Continues in https://guptaoption.com/texts/165-2.md (part 2 of 3).
End of [165] The Mattereum Manifesto: green capitalism, product information markets, and the blockchain, part 1 of 3. Its connections are at the top of this file; the map is https://guptaoption.com/llms.txt.