Matt Stoller of the Open Market Institute talks with EconTalk host Russ Roberts about the growing influence of Google, Facebook, and Amazon on commercial and political life. Stoller argues that these large firms have too much power over our options as consumers and creators as well as having a large impact on our access to information.

About Matt Stoller

Matt Stoller is a Fellow at the Open Markets Institute. He is writing a book on monopoly power in the 20th century for Simon and Schuster. Previously, he was a Senior Policy Advisor and Budget Analyst to the Senate Budget Committee. He also worked in the U.S. House of Representatives on financial services policy, including Dodd-Frank, the Federal Reserve, and the foreclosure crisis. He has written for the New York Times, the Washington Post, The New Republic, Vice, and Salon. He was a producer for MSNBC’s The Dylan Ratigan Show, and served as a writer and actor on the short-lived FX television series Brand X with Russell Brand. You can follow him on Twitter at @matthewstoller.

Header photo by GrungeTextures

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Excerpts from Stefan Heidenreich‘s new book on the post-currency future, republished from Transmediale.

Stefan Heidenreich’s book recently published by Merve Verlag is titled Money (2017). What it presents is not exactly a polemic against money, but rather a convincing speculation that soon we may not need money at all. While the notion that currency might soon become obsolete sounds like science fiction to many, Heidenreich argues that we are likely already within the first phase of a media transition leading to that point. Given the complex information infrastructures that have already been developed for documenting transactions, tying consumer habits to identities, and accurately predicting future exchanges, the substructure of a new kind of economy is now in place. In the following excerpts from his book (translated from the German), Heidenreich explores the potential ways this system might function, based partially on sophisticated “matching” formulas, leading to an age that could be more fair and equitable, but that might also produce monopolization and co-option in entirely new ways.

Introduction

One purpose of money is to distribute goods and labor. In the future, we will be able to solve these tasks differently, without money, instead relying on the help of networks, algorithms, and artificial intelligence.

Why do without money? The medium of money combines three functions: payment, value, and storage. In every money economy, the function of storage tends to overshadow the other functions. This tendency is unavoidable because it is inherent to money. The command “More!” is inscribed in it from the very start. The command drives toward a state in which all economic activity is forced to pay tribute. Each valuation of goods and professions shifts in favor of assets and their accumulation. Increasingly, income and property are distributed unequally. This should come as no surprise, since the measures taken by central banks after the crisis in 2008 were limited to the continuous salvaging of assets.

Designing a non-money economy would pose a fundamental utopia in opposition to the money economy. This economy would do without money, abolish the storage of value and assets, and replace the functions of value and payment with the algorithmically supported distribution of things and activities. Technically speaking, this is possible because all transactions are already digitally recorded and enough data can be calculated to enhance and replace the market’s information function. In this sense, the concept of the non-money economy represents a radical leftist utopia: an economy that strives toward equal economic distribution by changing the current system in a fundamental way, because it pertains to money’s nature as a medium.

(…)

1. Distribution

The task of the economy is to distribute money and labor. But money is not necessary for this task. Historically speaking, the medium of money came to be used to bundle necessary economic information and to communicate it. Today, almost the entire economy runs under a money regime. But neither the end of history nor an optimal solution for distribution has been achieved with this scenario. Since data and computers are now large and fast enough, we can envision alternative, moneyless, and probably better techniques of distribution. We need to begin with questions of distribution and allocation and not with markets and their monetary orientation.

The task of distributing many different things among many different participants represents a typical problem for networks, which is how to deal with a variety of connections. The core element of these connections is to form a social relation, be it through a gift or help or communication. Whenever something is distributed, a link is activated.

(…)

With the increasing amount and density of information, the relationship between prices changes radically. Prices only retroactively express what we already know about the behavior of consumers in the market. Whenever we book a flight, we can see how prices are set using algorithms. This data head-start applies not just to final consumers, but also to large sites of trading. Sporadic flash crashes show what happens when algorithms speculate on stocks and other securities.

When our profiles, our likes, and our consumer histories are used to calculate who will buy what and where, the entire market becomes condensed to a singular moment for each transaction—that is, if a profiling algorithm can determine the price one is willing to pay for a specific product at a given time and place, there exists exactly one marketplace for that sale. In that case the price of the item conveys no additional information outside of this single market. Formally speaking, distribution is still depicted in prices and calculated in terms of money, but data currents today already represent the technological foundation of a non-money economy.

(…)

2. Transactions

Transactions form the foundation of every economy. The simplest of all transactions is a gift. One person (A) gives something (x) to another person (B)—noted as a tuple (A, B, x). 1 The term “person” here refers to any kind of active agent, not just human beings, but also robots, programs, machines, or other living beings.

A gift is anything at all that can be given, not just commodities, but also information, events, access, actions, assistance, and the like. Giving, rather than labor, should be considered the foundation of economic relations, for the simple reason that one can indeed work without being part of the economy—that is, entirely for one’s own good and without any effect on others. In contrast, a transaction always represents a social relationship of some kind. This means that, with the division of labor, the foundational act is that of division, not labor. We need to take a closer look at what economic activity means. Labor is part of the money economy and relies on the concept of paid, productive activities. In a non-money field, the economic value of an activity would be decided by whether and how it is shared.

All formats and structures of giving and exchange, like payments, prices, values, purchasers, consumption, supply, demand, and markets, can be traced back to simple transactions. The entirety of all economic relationships can be understood through the elementary transaction of giving. The act of purchasing, today seen as something quite ordinary, emerged rather late in the long history of economic relationships and the advent of money. Previously, simple transactions were the rule: gifts, even forced ones, in the form of taxes, for example. Measuring and noting gifts in numeric form began not with money, but with systems of inscription that were usually linked to temples. All the stories of money that suggest the economy began with exchange are not just historically incorrect; they also refuse to recognize that an economy before money existed, and thus are not suited to conceive of an economy without money today.

(…)

3. Media and Networks 

Reaching the point when data can take over the tasks of money depends on the relationship of computing capacities to transactions. As soon as computer networks are large and fast enough to process all acts of payment, technically speaking it is possible to algorithmically emulate the function of money. We have now reached this very threshold, and are likely to cross it in the course of a few years.

As mentioned, economic forms without money are not entirely new. Before the rise of money, larger economic units were administered by systems of inscription. Their remains are not only found in the ruins of temples, but also in the myths of guilt or debt (Schuld) in many religions. In one of the most famous of all prayers, Christians demand, day in and day out, millions of times over, an end to all debt: “And forgive us our debts, as we also have forgiven our debtors.” But they have forgotten the economic core of these lines. With the shift from a centralized system of inscription to a decentralized one—i.e., using money—forgiving debts went out of fashion. This was no coincidence, for the many creditors who had taken the place of a central power were then more interested in collecting debts than in forgiving them. Christianity reacted by replacing debt with sin and replacing the forgiveness of debt with individual confession—that is, through a form of control.

Historically speaking, economic relationships did not begin with exchange and certainly not with payment. What came first was giving, helping, and lending. Property was unknown. In small village communities, memory was sufficient to keep track, more or less, of who gave what to whom.

It was only with the introduction of writing that larger economic units began to be organized over a longer term. Recordings of gifts and debts can be found at many excavation sites of ancient civilizations. Ultimately, the invention of writing can be traced back to such archives of gifts and tributes. Together with the first general medium and system of inscription, new economic units grew. The dominance of these economies of inscription, usually around temples and in cities, could expand as far as their power to collect tributes extended.

Money only came later. In a strictly technical sense, money is not a medium but a technique that uses all sorts of media to make notes transportable—and the process is read-only. For the economy, this meant that money was a fundamental innovation, for it converted the simple transaction of the gift into a symmetrical exchange. If somebody paid to acquire something, there was nothing left over. Nothing needed to be noted. Money saves data.

The expansion of money ran in parallel to war and expansive state forms that, with money’s help, established a cycle of taxes for paying and feeding soldiers.

By way of the circulation of goods and labor, a complex structure evolved of money-like forms of notation for payments and promises of payment, from the coin to the promissory note, from paper money to digital currencies.

In the end, we have returned to a system of inscription that not only notes all payments, but also constructs the wildest derivatives and wagers on promises of payment. But the fact that money condenses data is no longer of interest, since we are able to process enough data.

Peer-to-peer currencies and crypto-currencies are nothing fundamentally new to this system. Bitcoins are still a form of money, even if separated from a central institution. On the path towards the abolition of money, they merely represent a detour. The principle of payment itself is maintained by digital and peer-to-peer payment systems. They simply reproduce old money on the new-media foundation of a distributed network. This corresponds to the first step of a media transformation.

In media theory since Marshall McLuhan, it has been a commonplace to state that newly developed media are first used to reproduce old content. Media transformations often take place in two phases. First, there is a reproduction of the old in the new: in the case at hand, Bitcoin is the internet’s replication of money. Only in the second phase will it become clear what kind of new life the new medium can develop. This step is still to come for money. It will lie in the takeover of economic functions of money by way of intelligent networks.

The most important thing about peer-to-peer currencies is the architecture in the background, the so-called blockchain. This represents the foundation for a decentralized technique of administration by which transactions can be communicated anonymously and examined by anyone. The technique works for money just as well as for other moneyless and decentralized systems of notation. Therefore, the blockchain represents a possible building block for an economy after money.

The second phase of a media transformation applies to the question of how a moneyless economy can emerge and how it could replace money. But technological development leaves many possibilities open here. At issue is not a fixed, defined path that follows deterministically set media guidelines. Technological progress opens possibilities for future activities, in terms of the ecology of information affordances. As a rule, these are achieved by way of a chaotic process full of contradictions. What drives transformation are not plans or impact assessments but rather the misuse of possibilities, the counterculture, hacking, and taking advantage of mistakes and gaps. This applies to the non-money economy as well. We will not be able to plan it. It will emerge in the niches and obscure corners of various networks and spread from there.

(…)

4. Matching

Matching is an important operation in a money-less economy. It takes on functions that are otherwise controlled by prices and by the market. “To match” means to classify, assign, or link.

(…)

The process of matching serves to integrate all participants and their desires, needs, possibilities, and abilities. It offers to mediate between transactions, to advise participants in their decisions, to accompany negotiations, and to note the results.

Theories of algorithms and networks use the term matching to refer to every cross-classification of elements from two different sets. For our purposes, these elements can be things or people or events or points in time or locations or objects of any kind. Elements of the same set may be matched with one another—such as in the case of two people connected by a dating agency, a team of programmers brought together for the development of a project, or trucks or containers coordinated for shipping purposes.

Formally, in a network-based environment, matching performs a gift based on conditional constraints. The result of a match can be described as the difference between before and after, whereby each matched transaction has effects beyond all immediate participants, no matter how small. The environment encompasses all links and information that go into the matching, that are processed along the way, and that are noted in the final conclusion. In the process, all decisions made along the way are accounted for, both on the giving side and the taking side, on the side of the good itself that is given, and on the side of the affected third party. The factors that go into making a match include comparable transactions, the history of transactions in the participants’ profiles, and the participants’ desires, needs, and capacities.

Matching processes all of these parameters to suggest one or several possible solutions. The function is not that of an auctioneer, but of a mediator. This means that it is not the goal to calculate the best solution for an ideal price and to leave things at that, but to communicate among a series of interests. Matching is scaled depending on need. Not all options have to be taken. When it comes to daily use, matching would become a formality and take less time than paying does today. If matching were to be applied to a more extensive political process, it would affect all the committees, authorities, and interested parties involved, and would thus unfold similarly.

(…)

Matching procedures would make suggestions on the path towards a decision, show opportunities, and accompany the process of negotiation. It might well be the case that the algorithm becomes active before we even think of wanting something particular. Some suggestive apps already do this, by evaluating our desires and predicting them. Whether we want this influence or not is perhaps a hypothetical question. The more advantages people see in algorithms, the more they will take recourse to them. In this way, socially recognized patterns of behavior arise all on their own. The future, present, and past of media transformations are never foundationally subject to social intention, but driven by a technological dynamics all their own.

(…)

Seen from the users’ perspective, every process of matching begins with a desire or a need. The algorithm then suggests various solutions. If one of them fits, the other participants—producers, suppliers, inventors, machines, or algorithms—are contacted. If an agreement is reached, the transaction is carried out and noted. The impulse to make a match can emerge from each of the four participating sides: from those interested, from those offering, from the product itself, or from the algorithm. Most steps in a match are basically familiar to us already. We carry them out all the time, looking for something online or offering and selling something of our own.

The matching process encompasses an entire bundle of functions around a transaction. Whether these functions are encounters in a unified framework or are divided among a variety of apps is of no relevance in terms of a currency-less economy. The decisive feature is that matching does not operate with money, but organizes distribution directly. This also means that transactions are noted and stored, but not valued with fixed prices and calculated as such.

Matching is also omnipresent within an economy like the current one that operates with money. When we buy things or somebody pays us for our labor, matching is also taking place. But this usually follows different rules than it would in a moneyless world. Without money, the selection criterion of simple and one-dimensional value would fall by the wayside. Instead, an entire series of various decision-making factors become available.

Consider for a moment how matching works under conditions of money. Let’s say we go into a store and purchase something. The product already has a history behind it. Somebody designed it, others made it, and the store has it in its assortment because it could count on customers like us. Our purchase is thus preceded by several decisions that are all linked to the exchange of information. But before we take the product and pay for it, we undergo a more or less intense process of deliberation: weighing the costs, our budget, our desires, and our needs. This internalized matching can take place in very different ways depending on the person and the situation. Some have to consider every single cent they spend, whereas others are largely free of this concern. In a moneyless economy, there is no guarantee that all will be freed of such concerns.

There will continue to be unfulfilled—and unfulfillable—wishes. Even in an economy without money, we won’t be able to possess all that is denied us under a regime of money. Only the conditions and procedures will change, fundamentally, and for the better.

Whether with or without money, our personal decisions are integrated into a broader cycle of information. In today’s economy, a purchase sends the information that more of the same product is needed. It combines with similar information at the point of sale and reaches the producer from there. Parallel to the flow of money and payment, there is always a second current of information that controls how paths of production are organized and goods are distributed. Matching without money would dock directly onto this secondary flow of information.

1. In mathematics a tuple is a finite ordered list.

Translated from the German by Brian Currid.

This excerpt is part of the transmediale journal – face value edition. You can buy a print copy here.

Photo by Dyroc

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This image is a favourite of network coordinators everywhere. You’ll see it in every presentation about the benefits of decentralisation, and people find it very intuitive that the situation described by the diagram on the right (distributed) is somehow better than the one on the left (centralised). No evil oligarch sitting in the middle controlling everyone’s access to information. No critical nodes that, if destroyed, would break the network.

(It’s a little ironic that most network coordinators then proceed to do something that looks a lot like trying to be the central node in the diagram on the left. If your first instinct is to try and make a map, then spend a minute thinking about what a map is.)

I want to talk about what it feels like to be a node in the diagram on the right. You’re connected to four, maybe five other nodes. Most nodes in the network are several steps away from you. Lots of your connections mostly know the same people. Fundamentally, you don’t really feel like you have a very good idea of what’s going on.

This doesn’t sound so great? But it hints at what the true value of a distributed network is; in most environments where humans are trying to work together to process a lot of knowledge, the overriding problem is not a lack of input, but of effective filters. A librarian exists not because books are precious, but because there are just too many books. We don’t like our central node on the left not because it isn’t efficient – in fact, it’s super efficient – but because we’re afraid the filter they use isn’t the one we want.

So if you’re a network coordinator and you want your network to work effectively so everyone can find the information they’re looking for, what should you tell the people in your network to do? Here are my current best suggestions:

1. don’t worry too much about connecting to lots of people, and strive for diversity over quantity
2. worry primarily about what kind of information you care about – be discerning & review frequently
3. regularly collect that information from the people you’re connected to, and pass it on quickly & clearly
4. connect people that you see are using similar filters
5. spread these principles

Corollary: the most important thing you do in a social network is decide when to press the share button.

In particular, this advice suggests: don’t try and share stuff you think people will like. Focus on your specialisation, hobbies or whatever makes you unusual. Likely for the people you’re connected to, it’s the only way they could ever discover this information. Scrolling past irrelevant things is cheap; finding out quickly about something obscure can be invaluable.

Edward Saperia is Dean of Newspeak House, the London College of Political Technologists. Through a busy programme of events and residential fellowships, it convenes and supports practitioners working on the applications of communications technology throughout the public sector and civil society. Find out more at www.nwspk.com.

Originally published in Edward Saperia’s Facebook
Photo by isabelle.puaut

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He says here: “In one sentence she encapsulated everything I’ve ever wanted to do.” (1:23:10) He is serious, starting out with, “This is about taking things seriously. To take something seriously is to make it your way of being in the world.” (0:50)

This talk encompasses a great sweep of his personal history, quoting from the people who have most influenced him, over the decades, and including his own past work from 1970 to the present. He focuses first on Buckminster Fuller, with the well-known quote, “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.”

“Bucky”, to him, was first and foremost a Utopian Radical. “‘Utopian’ is the desire for transformation at the root. ‘Radical’ is acting upon that desire: actively trying to transform the root.” (40:00) as Youngblood explains, and he saw himself, from early on, as “building, or proposing, or theorising, models of communication”. (05:00)

The ‘ecosocial crisis’, according to Youngblood, is counterbalanced by the rise of the internet. The scales are finely balanced. Will we see a communication revolution? (Or ‘radical evolution’, he suggests as alternative.) “A communication revolution is the decentralization and pluralization of the social construction of reality. That can’t be allowed, because you can see instantaneously that’s the end of the dominating system.” (31:10)

“Creating on the same scale as we can destroy begins by re-creating ourselves, as imaginative beings — resocializing ourselves to become the kind of people who would be capable of mobilizing radical will on the scale that is needed. We need mass radicalization.” (38:20)

Using concepts from Husserl, he says: “From that huge media lifeworld out there, that we call ‘the cloud’ or ‘the commons’ each of us is actively engaged in building our personal media homeworld.” (55:25)

“The threat of the digital condition to the dominators is that that opens up the ability to first of all seed the commons with materials which we then as individuals download from the commons, and build media homeworlds whose content is exactly counter to the imperatives of social control. This is why they’re hysterical.” (55:45)

This gives just the initial sense of Youngblood’s deep and rich concept of “The Build”. This wide-ranging and inspiring talk challenges us all to secede from the broadcast culture; to cultivate ‘radical will’; and to channel the resulting righteous anger and outrage, without futile ‘hope’, towards this ‘Build’. We need to learn how to create at the same scale as we can destroy.

Lead image, Wikipedia Commons

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Yesterday*, Steve Bannon clearly articulated what many people have felt and known for quite some time when he told journalists, “You’re the opposition party. Not the Democratic Party… The media’s the opposition party.” This builds on earlier remarks by Trump, who said, “I have a running war with the media.”

Journalists have covered this with their “objective” voice as though it was another news story in the crazy first week of WTF moments. Many of those who value the media have looked at this with wide eyes, struggling to assess which of the many news stories they should be more horrified by. Far too few are getting the point:

News agencies, long trained to focus on reporting information and maintaining a conceptual model of standards, are ill-equipped to understand that they may have a role in this war, that their actions and decisions are shaping the way the war plays out.

When Kellyanne Conway argued that they were operating with “alternative facts,” the media mocked her. They tried to dismiss her comment that the media has a 14% approval rating by fact-correcting this to point out that this was only a Gallup poll concerning the media’s approval rating among Republicans. But they missed her greater point: there’s no cost to the administration to be helpful to the media because the people the Trump Administration cares about don’t trust the media anyhow.

How many years did it take for the US military to learn that waging war with tribal networks couldn’t be fought with traditional military strategies? How long will it take for the news media to wake up and recognize that they’re being played? And how long after that will it take for editors and publishers to start evolving their strategies?

As I wrote in “Hacking the Attention Economy,” manipulating the media for profit, ideology, and lulz has evolved over time. The strategies that hackers, hoaxers, and haters have taken have become more sophisticated. The campaigns have gotten more intense. And now many of the actors most set on undermining institutionalized information intermediaries are in the most powerful office in the land. They are waging war on the media and the media doesn’t know what to do other than to report on it.

We’ve built an information ecosystem where information can fly through social networks (both technical and personal). Folks keep looking to the architects of technical networks to solve the problem. I’m confident that these companies can do a lot to curb some of the groups who have capitalized on what’s happening to seek financial gain. But the battles over ideology and attention are going to be far trickier. What’s at stake isn’t “fake news.” What’s at stake is the increasing capacity of those committed to a form of isolationist and hate-driven tribalism that has been around for a very long time. They have evolved with the information landscape, becoming sophisticated in leveraging whatever tools are available to achieve power, status, and attention. And those seeking a progressive and inclusive agenda, those seeking to combat tribalism to form a more perfect union — they haven’t kept up.

The information war has begun. Normative approaches to challenging the system will not work. What will it take for news media to wake up? What will it take for progressives to start developing skills to fight back?

*Originally published January 27, 2017

Photo by Mark Deckers

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I was recently challenged by a friend around my model of abundance and put together this set of axioms that drive my thinking. I have no doubt that there are many other paths to thinking about abundance, but this is mine.

I.

1. Some portion of the universe is rivalrous. I’ll call this “energy”.
2. Some portion of the universe is anti-rivalrous. I’ll call this “information”.
3. It appears to be the case that information can have causal effect in only one direct way—by being “instantiated” in some energetic form.
4. All other causal relations in the universe are “mediated” by energy.

A very large amount of thinking could be done just with 1–4 above and they are far from certain. For our purposes, we will take them as axioms.

II.

5. The rivalrous operates under specific dynamics such as diminishing returns and entropy. The anti-rivalrous operates under very different dynamics such as accelerating returns and the network effect.
6. It appears, specifically, that the rivalrous (energy) is subject always to the second law of thermodynamics and heat death. But it does not appear that thermodynamic entropy has any direct impact on information.
7. As a consequence of these dynamics, the universe appears to consist of three different fundamental system dynamics.

7a. Those that are dominated by the dynamics of energy—these are linear systems characterized by the principle of least energy (e.g., a falling rock, a lightning bolt, a salt crystal, etc.)

7b. Those that are dominated by the dynamics of information—these are exponential systems.

7c. Those that are a mix of energetic and informational dynamics—these are dissipative structures characterized by S-curves and the principles of maximum fitness (i.e., all the laws of evolution).

III.

8. Dissipative structures are the result of energetic systems accessing and “taking advantage” of informational dynamics. All things being equal, the more a dissipative structure participates in / accesses information dynamics, the more bang for the buck it will get (the more fitness for energy input) and, therefore, the more fit it will tend to be.

8a. This is the fundamental driving the emergence of sensory cells, neural anatomy, complex neurology, etc. Each case is an example of an expansion of the capacity of dissipative structures to access and take advantage of information dynamics.

9. The emergence of novel capacities to operate in and with the “information domain” is one of the dominant structures of the arc of evolution writ large.

9a. Each such emergence appears to generate what is called a “portal pathway” in the evolutionary fitness landscape—an almost one-way ticket to a “higher order” fitness landscape. For example, the emergence of multi-cellularity was a portal pathway. While multi-cellular organisms continue to co-exist with single cell organisms—they effectively are no longer in competition with them. Similarly, the emergence of technical civilization was a portal pathway. While contemporary humans continue to co-exist with chimpanzees and lions—they effectively are no longer in competition with them.

10. Portal pathways are called this because while it is certainly possible for an emergent fitness landscape to “fall apart” and transition to some other set of dynamics, it has never so far occurred that the novel capacities that unlocked the portal pathway have been entirely lost. Accordingly, any future fitness landscape takes into account these new capacities and their relatively dominant effectiveness in comparison to prior regimes.

IV.

11. An examination of a very large number of metrics including population, energy consumption, CO2 production, information production, etc. indicates that something occurred somewhere around the 15th or 16th Century in the world that represents some kind of portal pathway.
12. Per the logic of 7c and part III, the historical effectiveness of this portal pathway is that it was able to more effectively access and take advantage of information dynamics than all previous eras.
13. A very large number of human dynamics (interpersonal relationships, violence, individual psychological assumptions and habits, family and social structures, etc.) have changed under the new “rules” of this new fitness landscape.

V.

14. The hypothesis of “abundance” or a non-rivalrous economy is based upon the proposition that we are currently in the process of traversing a new portal pathway into a system that is even more able to access and take advantage of information dynamics than has been available under the 15th—20th Century regime.
15. Under the abundance hypothesis, we are near or past a tipping point between a legacy system that has been dominated by the “rivalrous attractor” and an emergent system that is dominated by an “anti-rivalrous attractor”.
16. The deep insight of this transition consists of two elements.

16a. It is possible in principle for a sufficiently mature abundant economy to provision comprehensive wellbeing for every agent in the system. More on this later.

16b. Because of the nature of information dynamics, the movement toward provisioning comprehensive wellbeing is synergistic. That is, as more people are more fulfilled, the capacity of the system to provide more fulfillment to more people increases.

Note. While the abundance hypothesis establishes a firm direction on the evolution of the system from this point forward, it is difficult to predict the timeframe associated with the amelioration of the legacy consequences of the rivalrous attractor and the rollout of accelerating wellbeing.

It is possible that the synergistic effects of abundance (16b) are ramifying which would result in “accelerating returns” and a relatively rapid acceleration from legacy systems that evolved under a dominant rivalrous regime to new systems that optimize for anti-rivalrous dynamics.

For example, given our understandings of developmental psychology we might imagine that the longer a person has been alive and adapted to the rivalrous attractor, the harder it will be for them to adapt to the anti-rivalrous attractor and the more that they will inhibit the rollout of the abundance economy.

Thus, if we imagine *only* a vector where the ability to operate with anti-rivalrous dynamics is pushing against psychological plasticity and legacy inertia, it seems likely that a comprehensive transition of the entire species could take as long as eight generations.

But, of course, while it is implausible to imagine billions of people making significant moves into an “abundance mindset” under current constraints, it is trivial to imagine new capacities that could deliver on this potential.

For example, lets imagine that in 90 years we are 1000X more capable at directly influencing neuro-cognitive states in a long-term and sustainable way.

Looking back over the last 90 years, and projecting forward accelerating change, this is a perfectly plausible hypothesis. In this circumstance, we could imagine that every human’s subjective experience of wellbeing would be largely decoupled from their actual physical environment. The presence or absence of mates, food, etc., would be as irrelevant as the actual outside temperature to an air conditioned resident of Houston, Texas. This obviously raises its own issues—but the key point is that these are entirely new and different issues. Legacy rivalrousness and legacy human developmental plasticity is no longer a driving consideration.

Photo by Barbara Gilhooly

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