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# The Stack On Software and Sovereignty
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The next section deals directly with how essential the Addressing systems that link all layers of The Stack through ubiquitous but not always universal matrices are to the geodesign we undertake. They may be seen as planetary-scale megastructures in and of themselves, naming and mapping physical matter and temporal events at superhuman scale. Crucially, however, just like the interweaving jurisdictional volumes of The Stack itself, these systems may overlap one another in different states of alignment. They may cooperate, they may conflict, and they may be unaware of one another. At the level of the City, they may be operationalized for Stack-versus-Stack warfare, whereby one interfacial regime attacks the precisely Addressed object within another Stack, in another city, perhaps even in such a way that the other Stack is incapable of identifying and addressing the anomaly. Any one city may contain multiple addressing regimes or may be exclusive to only one (which may constitute the functional definition of the interfacial utopia of security: as pure as it is fragile). Differences between the map of the real (the Interface) and the archive of what is enumerated (the Addressed) are differences not only over a contested ground; they are differences in how to describe, think, and act on that ground in the first place. Different addressing regimes inform different interfacial regimes, which in turn ground the Cloud differently, over which their complementary and conflicting platforms contest one another. That is, their holy wars are not only over naming and enumerating the ground on which the temple might go;
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they are also over the definition of ground in the first place and over specifying into what currencies it can be converted and circulated.
72. Address Layer to Come: Platform-of-Platforms
Our extended consideration of The Stack is hardly the first time the idea of a computational governance has been considered. From the early twentieth-century science fiction, to the midcentury rise of IBM and cybernetics, to late-century campaigns to see the “ law as code ” and “ government as a platform, ” it has been a recurring thematic ideal or nightmare, depending on perspective. 48 It is curious, then, how poorly academic political science and international relations have dealt with computation as an institutional and global force. It is acknowledged as a mechanism available to statecraft and a sector over which policy is to be developed, but it is not usually considered by these disciplines as a primary seat of authority in its own right. Conversely, computer science, at least its populist variants, has had little trouble convincing itself that the social and institutional mechanisms for governing complex software and hardware systems (e.g., open source collaboration, sovereign user and administration, clustered APIs) can directly displace older models of public governance without prohibitive difficulty. But the translation between politics and programming is not automatic or inevitable, and indeed their transgenic encounter is occurring in ways that are often unpremeditated and misunderstood (being therefore the topic of this book). We observed that new forms of governmentality arise through new capacities to tax flows (at ports, at gates, on property, on income, on attention, on clicks, on movement, on electrons, and on carbon, for example). It is not at all clear whether, in the long run, Cloud platforms will overwhelm state control on such flows, or whether states will continue to evolve into Cloud platforms absorbing the displaced functions back into themselves, or whether both will split or rotate diagonally to one another, or how deeply what we may now recognize as the surveillance state (United States, China, or others) will become a universal solvent of compulsory transparency or an opaque monolith of absolute paranoia, or all of the above, or none of the above.
Between the state, the market, and the platform, which is best designed to tax the interfaces of everyday life and draw sovereignty thereby? It is a false choice, to be sure, but one that raises the question of where to locate the proper site of governance as such. What would we mean by “ the public ” if not that which is constituted by such interfaces, and where else should “ governance ” — meant here as the necessary, deliberate, and enforceable composition of durable political subjects and their mediations — live if not there? Not in some obtuse chain of parliamentary representation, some delusional monadic individual unit, or some sad little community consensus powered by moral hectoring, but instead in the immanent, immediate, and exactly present interfaces that cleave and bind us. Where should sovereignty reside if not in what is in between us, and derived not from each of us individually but by what draws the world through us? For this, it ’ s critical to underscore that Cloud platforms (including sometimes state apparatuses) are exactly that: platforms. It is important as well to insist once more that platforms are not only a technical architecture, but also an institutional form. At once, they centralize (like states) scaffolding the terms of participation according to rigid but universal protocols, just as they decentralize (like markets) coordinating economies not through the superimposition of fixed plans but through interoperable and emergent interaction. Next to states and markets, platforms are a third form, coordinating through fixed protocols while scattering free-range Users watched over in loving if also disconcertingly omniscient grace. The platform as totality draws the interfaces of everyday life into one another, again, where the maximal state and the minimal state, “ Red Plenty ” and “ Google Gosplan, ” start to look weirdly similar. From this, our own subjective enrollment in them is less as citizens of polis or as homo economicus within a market, but positioned rather as Users of a platform. As I see it, the future work of geopolitical theory (and of design and geopolitics) includes the development of a proper history, typology, and program for such platforms. These would not be a shorthand for Cloud feudalism (or for the monotonic network politics of the “ multitude ” ) but models for the organization of durable alter-totalities that command the force of law, if not necessarily its forms and formality. Our understanding of the political and economic philosophy of platforms demands its own Hobbes, Marx, Hayek, and Keynes — but until then, only a few broad strokes or, a field of dots that may provoke other inspired line drawers to connect them in ingenious ways.
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In the “ platforms ” section of the first chapter, I briefly discussed the history of centralized cybernetic economic planning programs, including during the 1950s and 1960s in the former Soviet Union, under the supervision of many, including especially mathematician Leonid Kantorovich, as well as the Cybersin initiative, undertaken in the early years of Salvador Allende ’ s rule in Chile, as designed by British cybernetician Stafford Beer. Abstracted from the politics of their host nations, the Soviet Union and Allende ’ s Chile, there has been renewed interest in the sometimes tragic stories of these primordial computational economies that place them both on the shelf with other wistfully unrealized past utopias, as well as a more pragmatic interest in properly constructing a history of the present and perhaps to discover overlooked and highly relevant accomplishments, both technological and economic. 49 As part of a cyberleftist archaeology, these projects are included among Nikolai Federov ’ s “ Cosmism ” ; Alexander Bogdanov ’ s revolutionary-era proto-systems theory, Tektology, and Red Star, his science-fiction novel about a socialist utopia on Mars; Konstantin Tsiolkovsky ’ s involvement with Kosma Vojagho; Pavel Klushantsev ’ s space exploration films, even Marcuse ’ s speculations on automation and the end of scarcity; and any number of other interfaces between science fiction and speculative communistic futurism. 50 At the same time, in their matching of totalities, and of computational systems with economic and territorial totalities, they are also part of a larger genealogy that includes, on the one hand, the modernist design value for the rational manufacturing and distribution of a universal baseline of material goods based on the most advanced available chemistry and calculations, and on the another, capitalist platforms for economic governance, such as simulating markets, calculating optimal prices, futures modeling, consumer profiling, and logistical optimization. Liberal technocracy has its own (sometimes overlapping) utopian archaeology. As we ’ ll see from the perspective of the platform looking out at the economies it is being asked to compose, the differences between state and market planning are far less dichotomous than they may appear from perspectives looking in. In the 1960s, programmers tried to use available computing capacity (incredibly limited by today ’ s standards) to implement the multifactoral calculations demanded by Gosplans, the State Board for Planning, that supervised the Soviet five-year plans. They were attempting to rationalize through planned centralization the supposedly spontaneous pricing computations of the market — what Hayek called catallaxy. For Hayek, a market is itself a distributed computer of sorts that will always have better information with which to work because calculations happen at the very end-points of the network, within individual transactions and on their cascading pressure on aggregate supply. To the socialist cyberneticians, the market ’ s transactional calculations would always be fatally inefficient because they are driven not by the optimal distribution of goods and value but by the tactical extraction of profit, always providing a price that is a distorted reflection of that surplus and not the need fulfilled (among other reasons, of course). These are caricatures of real economic mechanisms that are always anything but pristine, but the terms of abstracted oppositions posed here are useful in that they may clarify what is most important about the platform economies that straddle both types.
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Platforms locate the signal processing of pricing intelligence in both central mechanisms and in the indeterminate activities of Users, whose behavior may be modeled in advance but is not legally fixed to the dictates of that model (we hope). Furthermore, the functional difference between goods provided without profit by public utilities versus goods provided at or near zero-marginal cost by quasi-private platforms suggests a paradoxical alignment between the absolutization of monetary signification and its practical obsolescence (more on this below). A centralized system may be based on input-output models that are agnostic as to exchange value of goods and are therefore able to include the entire life cycle of resources in their models of economic activity, in principle if not in practice, but historically have been crippled by the slow feedback of demand signals back into those models. For expenditures with a long duration and widely shared return on investment, such as building a bridge, this slow relay is not such a problem, and most likely an advantage. Market governance works by building aggregate systems out of the emergent intelligence of zillions of individual transitions, including the distributed planning and forecasting of commodities and futures, and in doing so, they can have difficulty modeling totalities with long durations, especially ones composed of resources with tremendous value but no explicit price, such as a rainforest (or perhaps a bridge), and which therefore can be excluded as “ externalities. ” 51 (Again to preempt criticism from economists and ideologues alike, I grant that my treatment of these is artificially reductionist. They are meant to diagram a dynamic of convergence between what are conventionally understood as polar opposing tendencies into platforms , shown as technical-institutional systems that combine aspects of both and perhaps the ascendant infrastructural typology for contemporary planetaryscale computation.) Of particular interest is when very large-scale market actors also take on the governing role of central planning of the vast numbers of transactions that they engage in and enable. Problems of asymmetries of information between market actors engaged in a transactions are well known and in many respects presumed as part of a regularized cycle of buyers and sellers turning into winners and losers. However, when the sheer scale of one actor also allows it extraordinary omniscience and influence over the very possibility of a transaction, perhaps even by controlling the determining signals of prices already in advance of any impact they may have on any “ open ” transaction, then a form of governance is discerned. For example, the platform scale of Walmart and Amazon allows them line-of-sight into the supply chains that is so comprehensive, from the raw materials on which their suppliers depend through to the tastes of individual Users, that they can set wholesale prices (and wages) at skinthin margins because they know more about their suppliers ’ bottom-line costs than their suppliers do. This is one aspect of how platforms can manage a kind of synthetic catallaxy.
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Before discussing the key difference between these two platform actors, one from Arkansas and one from Seattle, we should first quickly revisit Jameson ’ s infamous consideration of “ Walmart as Utopia ” (perhaps in light of Lenin ’ s celebration of monopoly). On the one hand, Jameson sees the incredible accomplishments of this most rapacious of capitalist organisms: keeping prices low enough that lower-income shoppers can afford a diverse range of standardized goods modeled to satisfy standardized desires, driving logistical and production innovations and with them rationalizing the deep chemistry of industrial production in ways that would have seemed impossibly attractive to the early modernists, and many others. He writes, “ So it is that Wal-Mart is celebrated as the ultimate in democracy as well as in efficiency: streamlined organization that ruthlessly strips away all unnecessary frills and waste and that disciplines its bureaucracy into a class as admirable as the Prussian state or the great movement of instituteurs in the late nineteenth-century French lay education, or even the dreams of a streamlined Soviet system. New desires are encouraged and satisfied as richly as the theoreticians of the 1960s (and also Marx himself) predicted, and the problems of distribution are triumphantly addressed in all kinds of new technological innovations. ” At the same time, this extraordinary logistical accomplishment comes at equally extraordinary costs. Jameson continues, “ This dialectical character of the new reality Wal-Mart represents is also very much the source of the ambivalence universally felt about this business operation, whose capacity to reduce inflation and to hold down or even lower prices and to make life affordable for the poorest Americans is also the very source of their poverty and the prime mover in the dissolution of American industrial productivity and the irrevocable destruction of the American small town. ” In other words Walmart ’ s relentless synthetic pricing and production megastructure allows the working poor to afford a diverse collection of commodities from roughly 11,000 stores in twenty-seven countries, but at the expense of keeping them poor. Walmart is known to pay wages so low that many full-time employees may receive regular government assistance just to survive, effectively treating marginal labor costs as an externality and outsourcing them to the state as just another manipulated supplier, and all the while realizing global net profits of over \$17 billion. A platform actor of this scale could exercise its sovereign influence to radically restructure and improve production and labor conditions, but largely does not do so at the scale of need and opportunity. 52 Perhaps in an alternate universe (or year to come), Bizarro Walmart will exercise its ubiquity toward another and better Cloud Polis. Amazon ’ s total revenue is still a fraction of Walmart ’ s but it is all e-commerce, a domain in which Walmart still struggles for various reasons, but obviously where the long-term growth in retail will be realized. 53 By comparison, and to the ongoing chagrin of some of its investors, Amazon regularly loses hundreds of millions of dollars a year, with revenues well below the cost of its operations and aggressive infrastructure expansion. 54 What is the proper name for this kind of platform actor? Forget your associations with “ Amazon ” as real brand and company and imagine something as yet unnamed that does the following: it aggregates the most comprehensive catalogue of commodities ever enumerated; provides supply chain omniscience, a comprehensive synthetic catallaxy that is arguably rivaled only by Walmart or Google (among remotely similar companies); uses this leverage to lower unit costs by deflationary degrees each year; introduces its own proprietary unit addressing system; innovates the use of robotic warehousing processes to distribute objects with a minimum of physical intermediation; and does so at global scale without making a profit. Public utility? Monopoly? Neoliberal deterritorialization incarnate? Object-oriented Cloud feudalism? What would have the mid-1960s engineers of Red Plenty have called it? 55
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There is a joke (now an old joke) that goes like this, “ Question: What is the most significant accomplishment of communism? Answer: The Apollo Space Program. ” The implication is that state communism not only accomplished nothing with the violent upheavals of its misguided and self-corrupted effort at building egalitarian society from scratch, except by way of stimulating market-based societies to greater heights in response. It ’ s not my interest to revisit or revitalize Cold War ideologies (or evangelize twentieth-century economic ideologies, as should be clear by now) and so will offer instead an update and correction of this joke. 56 The most significant indirect contribution was not Apollo; rather it was Google. Is that still even a joke? The Page-Rank algorithm that formed the initial core of Search was based on “ collective evaluation ” as opposed to expert evaluation, which would be more expensive, slower and less reliable when dealing with massive amounts of unstructured and dynamic data. As described by Massimo Franceschet in his article “ PageRank: Standing on the Shoulders of Giants, ” which locates Google ’ s algorithmic methods in the long and diverse history of econometric, sociometric, and bibliometric information evaluation and calculative techniques, “ PageRank introduced an original notion of quality of information found on the Web: the collective intelligence of the Web, formed by the opinions of the millions of people that populate this universe, is exploited to determine the importance, and ultimately the quality, of that information. ” This too is synthetic catallaxy, the real-time weighing of the value of information within a differential field too large for any one actor to envision or evaluate, let alone steer. But instead of this system taking place “ spontaneously ” and for the purpose of realizing profit by one side of incremental transactions (there is no buyer or seller — yet), it is done through the unilateral centralization of decision-making algorithms into a single governing computational platform. For Google, that is itself an incipient intelligence as taught by its Users, is guided by the cosmic vocation “ to organize the world ’ s information and to make it universally accessible and useful ” and to do all this at a unit transactional price of zero and for half the planet at once. Again, what would have the engineers of Red Plenty have called this? 57 Perhaps they would call it “ my employer ” ? The genealogy of a project as complex as Google is much more twisty than any straight line from 1958 to 1968 to 1998, but it is impossible to understand the Google variant of Cloud Polis, and the accomplishment of engineering a freely available, global-scale econometric infrastructure, let alone the impetus to do so without also understanding the design ambitions of socialist/ communist cybernetics for a universal platform-of-platforms that produces nothing on its own but would optimize everything to everyone. 58 By some Gordian knot in political-economic history, among the most important contemporary accomplishments of capitalism is a descendant flower from the rubble of communism, our beloved and feared Google Gosplan (NASDAQ: GOOG). Perhaps — it is as yet to be determined — the inverse may also be true, and an ultimate consequence of Google ’ s platform universality will be an economic and informational social apparatus that bypasses the pricing and planning deficiencies of twentieth-century economic doctrines. In some variants of Marxian theory, it is an article of faith that socialism will emerge once capitalism has perfected technological systems to a degree that competitive ownership is unnecessary. In time, so the parable goes, the state itself will give way and dissolve into the generalized sovereign network of the general intellect. In the future, once all the information is “ made universally accessible and useful, ” it is unknown whether the future descendant(s) of today ’ s Google Gosplan will also fade away. “ My work here is done, ” says the Interface one morning. “ OK, Google, ” we reply.
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In the meantime, the design dilemmas of algorithmic governance are undecided but of pressing importance.
The infrastructural determinism of platform economics shifts where politics might be located and what its compositional limits might be in relation to markets, agora, and polities is solved differently by different systems. The economic architectures of China, the United Arab Emirates, Wall Street, and Silicon Valley (for example) all represent different genres of capitalism, differently expressed by similar computational substrates, enrolling or refusing available layers of The Stack. More important, components of those architectures are as available without prejudice to geodesign as much as the legacies of red futurism. We are interested in systems that can adjudicate the “ socialist pricing problem ” (knowing that centralized systems can be too slow to sense and calculate individual price signals) and as well as the capitalist pricing problem: that market models can confuse the emergent effects of transaction liquidity with systems planning and do so at the expense of artificially segregating and suppressing the real costs of near- and long-term “ externalities. ” We allow, to the pronounced consternation of both socialist and capitalist realists, that some polypaternal supercomputational descendant of Google Gosplan might provide a mechanism of projection, response, optimization, automation, not to mention valuation and accounting, beholden neither to market idiocracy nor dim bureaucratic inertia, but to the appetite and expression of a curated algorithmic phyla and its motivated Users. Perhaps to an extent, it already does. As suggested, such a platform-of-platforms might be idealized as pure governing medium, creating almost no original content in and of itself, because its fundamental role would be to interface, sort, and optimize the logistics of physical and virtual value, moving in and out. Its politics are fought over the naming, archiving, optimizing, disseminating, and recapitalizing what has been or will be produced by User polities that can possibly be Addressed. Its vision, “ seeing like a state, ” would be defined by the particular constellation of addressable objects and processes that constitute its world and by how it gives interfacial narrative to these through binding metadata about its uniquely cohered archive(s). Now, consider not just one of these universal apparatuses at work, but several, each interlocking, opposing, or ignoring the others, each social totality of planetary-scale computation enrolling the whole globe at once, along with the others. Comparative planetology, we now realize, does not necessarily require going to Mars. 59
The calculation problem for centralized plans or decentralized markets or any combination of these depends on the availability of data, which itself depends not only on the worldly divulgence and figuration of information from signal to sensor, but on how any platform apparatus is constructed to construe the world as an Addressable surface in the first place. A old growth redwood falling in a forest is not registered as a governable signal if the sensing apparatus is ignorant of its existence or relevance. It is not data until it is made so. Sociology has been aware of the potential and perils of diagramming the world by immanent statistical self-transparency going back at least to
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Tarde ’ s Monadology and Sociology (1893). 60 Tarde writes, “ If statistics continues to progress as it has done for several years, if the information which it gives us continues to gain in accuracy, in dispatch, in bulk, and in regularity, a time may come when upon the accomplishment of every social event a figure will at once issue forth automatically, so to speak, to take its place on the statistical registers that will be continuously communicated to the public and spread abroad pictorially, ” and so big data optimism is born, at least in theory. With the benefit of second-order cybernetics in hindsight, we understand that the “ registration ” process is bidirectional, that reporting agents in such a system both send and receive information to a higher-order governing abstraction. The swarm is measured in relation to how algorithmic governance feeds back to it, resensing its reactions, and so on. From the opposite perspective of the User looking to the platform, what may appear as data visualization may prove to be an Interface allowing delimited access and even control of the platform network and its data, and so between the edge-and-node visualizing one another, the Interface also becomes a visual diagram indexing the current state of this multiscalar recursion (at least in principle). The immediate question to ask on behalf of governance to this idealized cybernetic flow is where to locate anything like planning. Is the plan still a future model pushing from the center out, or is it now an emergent pricing index pushing from the periphery in? Neither extreme is really adequate on its own, and so instead we would focus on how planning and programming, some with the force of law, may be situated at (if not originate from) the Interface layer in the form of the model-simulation. We hold that the epistemic significance of big data would be realized by their ability to find and surface utterly alien patterns and relationships among the measured, and thereby to disturb our doxic conventions, even, and especially when, those interpretations are sensible only to machine Users (more on this below). Unfortunately, to date these methods seem to more disposed to optimize surgical correlations, confirming basic presumptions, and delivering high-resolution skeuomorphologies that don ’ t feel as fragile as they really are only because everyone else is making queries and visualizing test data based on the same conceptual conventions.
In the Address chapter, I introduced the notion of “ deep address, ” an expansive concept suggesting the identification of objects and events with a granularity that far surpasses the scales at which humans perceive physical space and duration. We observe the world as given by the capabilities of binocular vision that can register light between infrared and ultraviolet wavelengths, memory that can capture and forget events that happen in seconds or years, and so on. The physical world itself also works much faster and slower than that, and between nanometric and astronomic magnitudes, there is much we miss without using microscopes and telescopes. As for all of the things and events beyond natural perception, the design program of deep address considers how it is that some as yet unspecifiable means to sense their presence and to identify them according to a generic addressing matrix, and even to network them one to the other, would crack open the world ’ s information portraiture well beyond the normal scale of Internet of Things. 61 That is, the governable space of deep address is not only limited by the technological ability to see and sense something but also by the conceptual categorical systems in place that interpret what is seen and sensed as being something worthy of a discrete address or not. As discussed, any governing system, especially those situated as Cloud Polis, congeals into a functioning governing platform by the combination of these two contingent forms of power and knowledge. The platform sees what it can, what it is programmed to sense, and it identifies and addresses those perceptions according to how it is programmed to “ think, ” seeing what it thinks and thinking what it sees. At the same time, this is a highly dynamic process and one feeds back into the other, and any durable platform will evolve according to how and what it thinks about anomalous signals. The “ alien insights ” we hope appear from any sufficiently smart data analysis may begin as entropic noise and in time become foundational typologies and ontologies. This is where the nomos of the Cloud really works itself out, inch by inch. As Stewart Elden writes, “ Territory should be understood as a political technology, or perhaps better as a bundle of political technologies. Territory is not simply land, in the political-economic sense of rights of use, appropriation, and possession attached to a place; nor is it a narrowly political-strategic question that is closer to a notion of terrain. Territory comprises techniques for measuring land and controlling terrain. ” 62
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In the near term, before its holy wars kick in, we can plot the Address layer-to-come by tracing how it works within the forms of algorithmic governance that we already have. We ’ ve suggested that the recent financial crisis was also a crisis of addressability in that the kaleidoscopic nesting of asset debt inside collateralized futures inside options and so on not only allowed contagion to spread without quarantine, but that the absence of any reliable map of this haunted house of intertextual valuation made untangling the rot from the flesh all but impossible. The redesign of money — not just the currency vehicle of exchange, but of the valuation of things and events as such — may also require, or even entail, a more rigorous, flexible, and intricate mechanism for the identification of discrete assets as they twist and turn their way through financial wonderlands. What we now call “ high-frequency trading ” or algorithmic trading may continue to represent an increasingly larger percentage of all transactions, and as these techniques become more institutionalized, their methodologies and mechanisms become more normalized for even long-term investments. At the same time, the ability for deep address to engender not one but multiple address topologies describing the same set of events means that the potential for unprosecutable chaos is increased unless there are some workable standards for financial singularities, bifurcators, and resolvers that can police these data ontologies. Among the key drivers in the emergence of HFT were proprietary market simulations with which traders could execute mandated best prices and which helped inaugurate the supercomputing arms race on Wall Street. 63 Money, as we know, signifies not only value but debt, and anthropology confirms that debt as a technology of social organization precedes the innovation of material tokens to measure it. In time, some traditional materials became reference standards, however unlikely, such as the element Au, a soft, shiny, yellow rock. This option reintroduces the problems posed by a delimited total amount of value or debt reference, which are elastic by definition, but which are supposedly equal to the total quantity of that signifying substance. That total may be continually subdivided into units with less and less value, but the zero-sum economics is guaranteed by the physics of the whole. Moving off the gold standard increased the scale and granularity of debt to both increase, and with them the quantitative intensity of the social bonds that debt binds to itself (in principle at least). It allowed currencies to swell and contract in relation to one another and to the vagaries of unit value purchasing power, but the indexing of price is not the same as the indexing of value which is the tabulation of what should be most scarce within an economy. For example, a carbon tax may help force the real deexternalized costs of carbon to rise, to undistort transaction pricing signals, and in principle to make its continued overdigestion by ecological sinks prohibitively expensive and hence scarce by design. This dovetails with the logic of computational megastructures like Planetary Skin, which would wish to identify, address, and ultimately sort the price of ecologically sensitive molecules and chemical reactions. Some future permutation of these sensing apparatuses that is also a kind of banking or insurance infrastructure (and what are banks and insurers if not also already sensing apparatuses) may turn carbon itself into the reserve standard against which units of currencies can enumerate debt and value (including our species ’ carbon debt and the value of the ecosystems we have remaining), or at least a kind of standard conversion currency. If Au has already established that we can link currencies to the table of elements, then why not to C? Would it do more to ground money in a marking fabrication of total debt that is more relevant to economies defined by the paradoxes of Anthropocenic growth?
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