Several articles examined in this post to gauge the potential to tokenize Rare Earth Elements (REEs), framing it as a key battleground in the “spreadsheet capitalism” framework and the BRICS bloc’s challenge to the US dollar. The post analyzes the promise of financial tokenization, the BRICS strategy, and the significant practical barriers that make REEs poor candidates for effective financialization compared to assets like gold.

The post first outlines the theoretical benefits of tokenizing REEs: making a strategically vital but illiquid asset class accessible to global investors, improving transparency through blockchain, and channeling capital towards sustainable mining. It then analyzes the BRICS strategy, suggesting the bloc aims to leverage its control over REE reserves to create a new, commodity-backed financial system. This system would use tokenized REEs as a semiotic and computational anchor, creating an alternative to the USD-based grid by using its own payment channels (like China’s CIPS) and exchanges.

However, the posts’s core argument is that this vision will likely struggle due to fundamental aspects of REEs. Unlike standardized gold, rare earths are not “fungible;” a token for “neodymium” is meaningless without specifying its exact purity and form. Furthermore, the REE market is opaque, lacking the transparent, global price benchmarks needed for the computational formulas that drive modern finance.

The post concludes that while specific batches of REEs might be tokenized for niche industrial purposes, their physical and geopolitical complexity prevents them from being effectively abstracted into the simple, liquid symbols required to function as a major global asset. REEs remain stubbornly tied to the real world, resisting the clean logic of spreadsheet capitalism.

The post takes a critical look at tokenizing rare earth elements that promise to bring liquidity to a strategically vital but currently inaccessible asset class. A major problem is that REEs are physically and industrially bound to specific geographies (notably China, Brazil, and Africa) and often priced through opaque or bilateral contracts. Their physicality resists the liquidity and standardization demanded by global capital markets.

Historically, REEs have been coordinated and transacted by governments, state-owned enterprises (SOEs), large corporations, and very specialized traders. Tokenization hopes to break this barrier and give alternate investors exposure to these assets. For a manufacturer here in Korea, like Samsung or Hyundai, a token representing “neodymium” could be a powerful tool for hedging against price volatility. For investors, it could offer a new way to speculate on the green energy transition.

For BRICS, tokenization may provide non-dollar financing and avoids Western sanctions. REE tokens embody “material sovereignty” that represent tangible backing for new currencies. But what are the rare earths and what are limitations for its financialization?

What are Rare Earths?

Rare Earths are a set of seventeen metallic elements integral to a wide range of modern mechanisms, from consumer electronics to advanced military hardware. Although called “rare,” they are relatively abundant but difficult to find in economically viable concentrations for mining.

Rare Earth Elements (RREs) are roughly divided between two categories based on their position in chemistry’s periodic table. The heavy rare earth elements (HREEs) are a subgroup of the rare earth family characterized by their higher atomic numbers and greater atomic weights. Known as the “Heavies,” Dysprosium (Dy), Terbium (Tb), and Yttrium (Y) are critical for modern defense applications and the green energy revolution.

The Heavier Rare Earths Dysprosium (Dy) and Terbium (Tb) serve several purposes. They are vital additives to neodymium magnets, as they enable them to retain their powerful magnetic properties at the extremely high temperatures found inside an electric vehicle motor or a wind turbine generator. Yttrium (Y) is used as a red phosphor in older CRT displays and some modern LEDs. It’s also a critical component in certain high-performance lasers and medical devices.

Other heavy metals include Gadolinium (Gd), which has unique magnetic properties that make it critical as a contrast agent in MRI scans, helping to produce clearer images of internal organs and tissues. Erbium (Er) is a key element in modern telecommunications. It is used to create optical amplifiers for fiber-optic cables, boosting the data signal as it travels over long distances without requiring conversion back into electricity.

The “Lights” are the more common rare earths, often used in magnets, catalysts, and glass. Neodymium (Nd) is the most important rare earth element, critical for creating the world’s strongest permanent magnets (NdFeB magnets). These are used in everything from the tiny motors that make your smartphone vibrate to the giant electric motors in EVs (like a Tesla Model 3) and the generators in wind turbines.

Other “Lights” include Praseodymium (Pr), which enhances high-power magnets by improving their heat resistance when combined with neodymium, while also creating a yellow hue in glass and ceramics. Lanthanum (La) enhances optical clarity in camera lenses and telescopes. It is also a crucial component in nickel-metal hydride batteries used in hybrid vehicles, such as the Toyota Prius. Cerium (Ce) serves major industrial roles, acting as a primary catalyst in automotive catalytic converters to reduce emissions and as a polishing agent for manufacturing glass screens and lenses.

The Promise of Tokenizing Rare Earth Elements

Returning to Ms. Mason, as a blockchain consultant, she argues that tokenizing rare earth minerals promises to transform them from a hidden, industrial ingredient into a dynamic and accessible financial asset. The narrative behind this push is one of modernization and democratization, built on five key benefits.

The first benefit is a promise is to shatter the barriers of an exclusive market. Historically, investing in rare earths was a privilege reserved for governments, large corporations, and specialized investors. Tokenization aims to change this by offering everyday investors a chance to gain exposure to this critical asset class, making it globally accessible. This newfound accessibility is paired with a solution to the age-old problem of liquidity. Instead of the slow, cumbersome process of trading physical commodities, tokens enable a swift, 24/7 global market, allowing investors to move in and out of positions with ease.

Furthermore, this new market is to be built on a technological foundation of trust. By utilizing blockchain technology, every transaction is recorded on a transparent and immutable ledger. This move promises to drastically reduce the risk of fraud and create a more trustworthy supply chain. This newfound visibility makes rare earth tokens an attractive tool for portfolio diversification, offering an alternative asset that can perform differently from traditional stocks and other financial instruments during times of market volatility.

Perhaps most compellingly, the tokenization of rare earths is framed as a way to align profit with planetary goals. As demand for these minerals soars, driven by the green energy transition and the rise of electric vehicles, tokenization provides a direct channel for global capital to fund sustainable mining operations and renewable energy projects. This new ability allows investors to directly support and benefit from a more sustainable economy.

The BRICS Challenge

Cyrus Janssen’s argument that the BRICS plan to replace the US dollar with REE tokens is based on the recent 2025 Moscow Financial Forum held in mid-September. They announced plans for a dedicated precious metals exchange that would allow countries to settle payments in gold, diamonds, platinum, and also rare earth minerals. It would bypass Western systems like the London Metal Exchange (LME) that currently establishes most prices for critical commodities. After the Ukraine war started, this system excluded Russia, despite recently becoming the fifth largest gold holder worldwide.

The YouTube video argues that this new infrastructure is underpinned by the bloc’s dominance over strategic global resources. Janssen stresses that Brazil currently produces nearly all of the world’s niobium supply. BRIC countries also have significant amounts of gold. This level of resource control, he argues, is the foundation for a new system that moves away from the US’s fiat currency toward a REE-backed monetary standard.

The Watcher.guru article is more informative. It backs the claim that a viable tokenization market for rare earth elements (REEs) is planned as part of a BRICS+ strategy to create a commodity-backed, blockchain-based exchange system. Proponents of the political bloc cheer on its efforts to replace the US dollar in international trade by leveraging control over critical resources — gold, rare earths, energy, and food — to build a new pricing and settlement architecture.

The proposed mechanism would merge resource monetization (turning metals into tradable digital assets) with BRICS’ payment innovations, such as CIPS instead of SWIFT’s blockchain infrastructure, and gold-based exchange rates. The aim is to anchor a BRICS currency system in tokenized REE commodities rather than fiat trust.

This strategy is reportedly gaining attention amid a steep decline in US dollar usage, which the article notes has fallen to its lowest share of global reserves since 2000 (58%), with 68% of global trade now conducted without the dollar. The framework is said to be particularly appealing to emerging economies, especially in Africa, which see the new exchange as a way to leverage their own resource projects and escape the political influence tied to the Western financial system.

The article concludes that by combining direct control over critical commodities with an independent payment and exchange infrastructure, the BRICS bloc is creating a direct and increasingly plausible challenge aimed at systematically replacing the US dollar’s global hegemony with a new, resource-backed financial order.

However, will rare earth metals effectively tokenize on the SCT Stack of spreadsheet capitalism? The practical realities of the REE market clash with the clean abstractions required by the SCT stack. Will blockchains prove sufficient in creating a new infrastructure for REE tokenization that can back a new currency?

Major Barriers to Effective Tokenization in the SCT Stack

Rare earth metals will not tokenize as effectively as other assets like gold within the spreadsheet capitalism framework. The main reasons are their fundamental lack of fungibility and market transparency. Fungibility is the property of goods or assets where individual units are interchangeable and indistinguishable. Unlike gold, where one bar is a near-perfect substitute for another, each batch of rare earths is a unique industrial ingredient. This physical complexity resists the radical simplification needed to create a clean, tradable digital symbol. These weaknesses creates a flawed semiotic substitution, making them difficult to represent as simple, standardized symbols that the system requires.

The first step of the stack, turning a real-world asset into a digital symbol, fails at a basic level for REEs. Gold is highly standardized. A token like PAXG can represent a claim on one fine troy ounce of a London Good Delivery gold bar, a globally accepted standard. Rare earths are not standardized. A token for “one kilogram of neodymium” is a meaningless symbol without specifying its purity (e.g., 99.5% vs. 99.99%), its form (oxide, metal, or alloy), and its origin.

Spreadsheet capitalism thrives on a single, globally synchronized price that can be fed into computational formulas. The gold market has the XAUUSD, a real-time price stream from the COMEX and LBMA. The rare earths market has no such indicators. Prices are opaque and determined by private, bilateral contracts between a few major suppliers (primarily in China) and industrial buyers.

There is no reliable, liquid, global benchmark price for a REE token to peg itself to. This makes it incredibly difficult to use the token in the computational stack for risk modeling, derivatives pricing, or collateral valuation. A token is only as good as the asset backing it. The gold market has a mature, trusted, and highly audited network of vaults (e.g., in London, New York, and Zurich). The infrastructure for storing and verifying large quantities of REEs for the benefit of token holders simply does not exist on a similar scale. Establishing this trusted custodial layer would be a massive undertaking, especially given the geopolitical concentration of the supply chain.

Tokenization and Blockchain in the SCT Stack

The tokenization of REEs’ arguments sits at the intersection of the spreadsheet capitalism framework and the possibilities of the emerging tokenization of resource value. Below is a detailed analysis of the articles’ claim for a viable tokenization market for rare earth elements, framed through the three logics of Substitution/Abstraction, Symbolic Computing, and Telecom Grid Synchronization — and their geopolitical-economic implications for de-dollarization.

This analysis challenges the claims that a viable tokenization market for rare earth elements (REEs) will successfully emerge as part of a BRICS+ strategy to create a commodity-backed, blockchain-based exchange system in the near term. The plan to replace the US dollar in international trade by leveraging control over critical resources such as gold, rare earths, energy, and food to establish a new pricing and settlement architecture will face numerous challenges.

The proposed mechanism to merge resource monetization (turning metals into tradable digital assets) with payment innovation, such as China’s CIPS instead of SWIFT, aims to anchor a BRICS currency system in tokenized commodities rather than fiat trust. Tokenization represents a shift from fiat-denominated computational pricing to resource-denominated signification.

In the current dollar-based system, metals are priced in USD units, substituting their material value through the symbolic power of the dollar grid (Bloomberg, LSEG, Aladdin). The proposed BRICS system seeks to invert this substitution with digital tokens that would directly represent fractions of physical metals or reserves (e.g., 1 REE token = 1 kg neodymium stored in Angola). This would convert matter into sign, but without passing through the dollar — a new layer of semiotic substitution detached from US spreadsheet infrastructures.

Hence, REE tokenization is not just about digitization — it’s a semiotic rebellion, replacing the dollar as the global unit of account with resource-tied symbols recorded on BRICS-led blockchain exchanges. The viability of this market depends on whether tokenized REEs can be abstracted into comparable, liquid financial instruments:

Blockchain tokens offer fungibility and fractionalization, allowing them to represent micro-ownership in rare earth deposits, making these assets tradable on digital exchanges. This transition allows integration into risk models and cross-asset portfolios, similar to how ETFs abstract physical gold into digital gold.

However, liquidity, verification, and pricing transparency remain key obstacles. Substitution and abstraction requires standardization across jurisdictions, audits, and trading rules — the very functions that spreadsheet platforms (Bloomberg, LSEG) currently monopolize.

Thus, the challenge for BRICS+ is to build alternative abstraction infrastructures, such as transparent ledgers and decentralized oracles, which substitute for Western data terminals.

Symbolic computing is the performative layer of finance that involves modeling, pricing, and hedging. It is where tokenized REEs would gain traction or fail. Once tokenized, REE assets can enter computational environments like risk models, smart contracts, and DeFi-style derivative markets. These environments could compute prices via algorithmic market-making, automated yield, or resource-backed lending using smart contracts.

Symbolic computation combines with substitution to transform natural resources into programmable collateral. It integrates geopolitics into code. In spreadsheet capitalism terms, the REE token becomes a computable symbol, allowing new forms of liquidity and leverage. The question is, will it be within the alternative BRICS grid, and not the USD-based symbolic regime?

The current USD regime faces challenges from the emerging BRICS+ token regime. The pricing infrastructure at the London Bullion Market, COMEX, and displayed on USD-denominated tickers become challenged by the Shanghai Gold Exchange and the BRICS Precious Metals Exchange. At the computational layer terminals like Bloomberg, LSEG, Aladdin (USD risk models) could be replaced by BRICS exchange APIs and smart contract oracles. Telecom synchronization provided by SWIFT, Fedwire, CLS, and T2 is challenged by China’s CIPS and new blockchain settlement layers. The unit of account for USD regimes would be challenged by REE resources- or gold-backed tokens.

In sum, the semiotic anchor of “dollar liquidity” is challenged by “resource transparency.” This transition amounts to a shift in the semiotic-computational-telecom stack — from dollar-based spreadsheets to distributed ledgers as the new computation and synchronization substrate.

Strategic Implications of REE Tokenization

The article implies that REEs could become prime candidates for early tokenization, for several reasons. One is resource concentration. BRICS+ control some 72% of reserves — enabling monopoly-like coordination. Strategic REEs demand for EVs, semiconductors, and defense industries ensures long-term value. The political incentive is that tokenization provides non-dollar financing and avoids Western sanctions. The symbolic appeal is that REE tokens embody “material sovereignty” — representing tangible backing for possible new currencies from domestic sources.

However, for tokenization to function at scale, pricing transparency, custodial assurance, and convertibility mechanisms must rival the computing and synchronization of Western spreadsheet terminals. Otherwise, the REE token risks being symbolic without liquidity — an “unsettled” sign in the global financial grammar.

Integration into Spreadsheet Capitalism

If realized, REE token markets would appear within Aladdin, Bloomberg, and Wind terminals as synthetic tickers such as:

Nd_TKN, Co_TKN, Nb_TKN — linked to blockchain APIs.

In real-time feeds it will pull via =BDP(“REE_TKN”,”LAST_PRICE”).

In cross-hedge models, REE tokens correlate with gold, oil, and Treasury yields and in risk modules tokenized REEs enter global portfolios for diversification. Lastly, yield analytics integrate them into DeFi-linked or BRICS exchange-backed smart contracts. Thus, even as tokenization claims autonomy from the USD, its representation and computation would still occur through the spreadsheet logic — the universal language of substitution and abstraction.

Synthesis and Conclusion

This post ultimately envisions a tokenized commodity standard where semiotic substitution (token), symbolic computation (smart contract), and telecom synchronization (blockchain ledger) merge and add a new spreadsheet layer, with and beyond the US dollar.

In this system, rare earth tokens become both symbols and settlement instruments. Blockchain ledgers enter the grids of computation and coordination while AI-driven analytics and terminals (like Wind or Aladdin) price, hedge, and optimize across these new semiotic surfaces.

Tokenization will provide a niche tool for the near future, not a global asset. While specific, standardized batches of rare earths could be tokenized for supply chain tracking or to collateralize a specific loan between industrial partners, they are unlikely to become a liquid, globally traded asset class like tokenized gold. The very physical and geopolitical complexities that make rare earths strategically critical are what prevent them from being effectively abstracted into the fungible, placeless symbols of spreadsheet capitalism. They remain stubbornly tied to the physical world.

The operational grammar of symbolic computing is how spreadsheet capitalism expresses financial meaning as formulas and returns. When this is applied to tokenized assets — i.e., digital representations of securities, commodities, or currencies living on blockchain or managed through APIs — the symbolic layer translates blockchain state into spreadsheet logic.

But the paradox remains. While tokenization decentralizes value representation, symbolic computation re-centralizes it in global grids. Whoever controls the grid of valuation models will control the next monetary order. USD’s centrality equals control over pricing, modeling, and messaging. BRICS’ challenge is to create a parallel semiotic and computational infrastructure built on tokenization that global finance can compute with. Whoever defines the physical custodial layer (i.e. Chinese gold vaults in Saudi Arabia) and the symbolic grammar of tokenized commodities will be in a good place to define the new world order.

Notes

[1] This was written a few days before China announced new licensing restrictions on REEs that caused a significant drop in financial indexes and understandable furor in the White House.

Citation APA (7th Edition)

Pennings, A.J. (2025, Oct 8) Will BRICS Effectively Tokenize Rare Earth Elements to Back a New Currency? apennings.com https://apennings.com/dystopian-economies/will-brics-effectively-tokenize-rare-earth-elements-to-back-a-new-currency/

© ALL RIGHTS RESERVED

Not to be considered financial advice. LLMS were used in parts of this post.

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI policy and broadband economics. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: blockchain, data analytics and meaning, digital geography, digital media economics, digital spreadsheets, dystopian economies, electric money, enabling frameworks, financial news, geopolitical risk, global communications, meaning makers, science and technology studies, smart new deal, sustainable development, technologies of meaning, telecom policy and net neutrality, telegraphic political economy
Tags: BRICS > fungibility > Rare earth elements (REEs) > SCT Stack

Tokenization of Gold in Blockchained Spreadsheet Capitalism

Posted on | October 5, 2025 | No Comments

When I was teaching my Macroeconomics course at New York University (NYU), we would often go down to Wall Street and deep (80 feet below street level) into the vaults at the Federal Reserve Bank. Over 6,000 tons of gold bullion were stored there from countries around the world. If no one was looking you could put your finger through the mesh fence and touch a few gold bars.[1]

This post describes how the tokenization of gold on a blockchain, representing ownership rights, operates in global spreadsheet capitalism. Within its core logics of semiotic substitution, symbolic computation, and grid of telecommunications synchronization (SCT stack), gold bullion becomes a tradable token represented in a spreadsheet cell. It then becomes a computable variable (risk metrics, yield structures, and algorithmic trading inputs), and finally, it is synchronized data in the global financial grid. Real-time ledger entries of tokenized harmonize over time and distance through connected financial terminals.[2]

Tokenization is emerging as a major strategic trend (not just a niche experiment) that’s likely to reshape financial markets. It will reconfigure how many financial instruments are used, priced, and accessed. Below I lay out the mechanism, plausible pathways, and likely effects on gold.

Tokenization transforms ownership claims and cash-like instruments into programmable, fractionable, and 24/7 tradable tokens. It makes previously illiquid real-world assets (RWAs) indexable and fungible in ledger-based markets. This innovation is not merely new tech; it changes market structure (settlement, custody, market-making), product design (fractionalized RE, tokenized treasuries, tokenized funds), and distribution (global retail access).

Market evidence and institutional surveys (2024–2025) show rapid growth in tokenized RWAs, stepped-up institutional pilots (tokenized treasuries, funds, tokenized cash/stablecoins), and consultancy roadmaps that treat 2025 as an inflection period when tokenization starts a major growth trend.

Semiotic Substitution

Gold has always lived between the material and the symbolic (a shiny metal, a bar in a vault, a futures contract, a line on a central bank’s balance sheet). Tokenization intensifies this dual life.

The SCT stack begins with semiotic substitution. The physical gold bar is abstracted into the universal ticker XAUUSD. This symbol represents abstract ideals — safety, enduring value, an inflation hedge, and a non-sovereign store of wealth. In tokenization, a bar of gold stored in a vault is represented on-chain as a digital token (e.g., “1 PAXG = 1 fine troy ounce of gold in custodian X’s vault”). The heavy, immobile metal is substituted by a new portable, tradeable signifier that facilitates purchases and acts of exchange.

In tokenization, a bar of gold stored in a vault is represented on-chain as a digital token (e.g., “1 PAXG = 1 fine troy ounce of gold in custodian X’s vault”). The heavy, immobile metal is substituted by a new portable, tradeable signifier that facilitates purchases and transactional exchanges. Gold, traditionally divisible only with difficulty, can now be fractioned into decimalized tokens (0.001 token = 0.001 oz), widening participation and enhancing its substitutability.

In Bloomberg, Aladdin, and Wind terminals, a “GoldToken” would appear as just another asset row with ticker, price, volatility, custody field. The token displaces bullion-as-object with a signifier that can circulate in the spreadsheet logic alongside equities, bonds, and derivatives.

To make the semiotic substitution especially vivid, here is a side-by-side comparison of how physical gold versus tokenized gold would appear and function within the fields of a modern financial spreadsheet. The table below illustrates how tokenization completes the abstraction of gold, transforming it from a tangible object with real-world constraints into a liquid, placeless symbol in the global grid.

Symbolic Computability of Gold-as-Token

Symbolic computing in spreadsheet capitalism transforms blockchain’s distributed ledgers into centrally abstracted calculation spaces. Even as tokens decentralize ownership, their meaning is reinscribed through formulas like VaR, Sharpe risk ratio, and discounted cash flow (DCF). This activity reintegrates them into the semiotic–computational telecom grid of the USD-dominated spreadsheet world.

Once gold is represented as blockchain tokens, it becomes programmable — available for smart contracts, algorithmic trading, collateralization, and automated settlement routines. Portfolio software in Aladdin and other terminals (MSCI risk engines, etc.) treats tokenized gold as a computationally tractable input. This development means it has an algorithm that can efficiently and quickly solve instances of a problem, such as volatility, correlation with USD, VaR, and stress tests. The system doesn’t “see” gold bars; it only sees the token’s price feed and contract logic.

Derivatives and structured computational products define “gold.” Symbolic computing layers tokenized gold into DeFi protocols (yield-bearing vaults, tokenized swaps) or institutional products (ETFs that wrap tokenized holdings). The computational layer abstracts gold from its material scarcity into formulas, models, and recursive instruments.

Telecommunications Grid Synchronization

Blockchains are synchronized ledgers where identical copies of the transaction record are stored on many computers (nodes). They are automatically updated to maintain a single, consistent version of the truth across the network. Tokenized gold trading relies on the blockchain’s global, time-stamped ledger. This distributed spreadsheet synchronizes ownership claims across jurisdictions. Every transfer is logged throughout the shared, machine-readable “grid” of nodes.

Gold tokenization is integrated with terminals leased to traders and researchers by Bloomberg, LSEG, and Wind. They ingest and display their feeds and synchronize them with other market data streams. Price ticks, custody updates, and compliance flags flow into the same tabular interfaces that already synchronize FX, equities, and bonds.

The Telecom grid facilitates a 24/7 liquidity layer. Unlike futures markets that close, blockchain-based gold tokens synchronize continuously, aligning with the always-on rhythm of digital networks. This real-time synchronicity remediates gold’s status as a slow, heavy, “ancient” money into the tempo of spreadsheet capitalism’s high-frequency grid.

Putting It Together

In spreadsheet capitalism, tokenized gold serves as a substitute for the financialized metal. Vaulted bullion becomes a tradable token represented in a spreadsheet cell. Gold becomes a computable variable (risk metrics, yield structures, algorithmic trading inputs) and a synchronized signal in the global financial grid. Real-time ledger entries harmonize with financial terminals like the Bloomberg Box and portfolio dashboards provided by BlackRocks’s Alladin.

Thus, tokenization pulls gold fully into the abstract, programmable, and globally synchronized order of spreadsheet capitalism, where its ancient materiality (bars in vaults, central bank storage) is absorbed into the logic of substitution, computation, and synchronized grids.

Citation APA (7th Edition)

Pennings, A.J. (2025, Oct 06) Tokenization of Gold in Blockchained Spreadsheet Capitalism. apennings.com https://apennings.com/technologies-of-meaning/tokenization-of-gold-in-blockchained-spreadsheet-capitalism/

Notes

[1] I really wanted to see the Open Market Operations (OMO) traders who bought and sold US securities but the gold was interesting, and even more so a decade later when its value more than doubled.
[2] For a more explicit analysis of political economy of gold, see Pennings, A.J. (2018, Nov 11). From Gold to G-20: Flexible Currency Rates and Global Power. apennings.com https://apennings.com/how-it-came-to-rule-the-world/digital-monetarism/from-gold-to-g-5-flexible-currency-rates-and-global-power/

Share

Tweet

© ALL RIGHTS RESERVED

Not to be considered financial advice. LLMs used in researching parts of this post.

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: blockchain, data analytics and meaning, democratic political economies, digital media economics, digital spreadsheets, financial news, financial technology, geopolitical risk, global communications, sustainable development, technologies of meaning, telecom policy and net neutrality
Tags: blockchain > gold > spreadsheet capitalism > Tokenization

The International Politics of Domain Name (DNS) Governance, Part 3: ICANN and AI

Posted on | September 22, 2025 | No Comments

As of September 2025, the international politics of the Domain Name System (DNS) have evolved into a high-stakes battle for control over the Internet’s foundational address book. The era of viewing the DNS as a purely technical utility is over. Today, it is a central arena where the competing interests of governments seeking control, corporations protecting valuable brands, and a lucrative domain registration market all collide.

In this post, I continue to examine DNS developments during the few short decades since the Internet was created, particularly primary debates over Internet governance, and even struggles over the balance of power in the digital world. I started the discussion with a post on the early development of the DNS system when it could be handled by one person, Jon Postel, during the early days of the ARPANET.

As Daniel W. Drezner pointed out in his All Politics Is Global: Explaining International Regulatory Regimes (2008), the Domain Name System (DNS) is a crucial technological resource that must be effectively managed worldwide. Drezner raised three concerns:

– Governments and corporations are acquiring the capability to control access to the Internet and specific services
– DNS management is essential for maintaining the trademarks of organizations such as samsung.com and tesla.com
– Registering Domain Names can generate a lot of money. Where does it go? [1]

A core conflict is the clash between two fundamentally different philosophies of Internet governance: multi-stakeholderism, the original model, championed by the US and its allies, where a consensus between technical experts, academics, corporations, and civil society governs the Internet. The Internet Corporation for Assigned Names and Numbers (ICANN) embodies this model.

Digital sovereignty is the alternative model. This state-centric model, pushed by nations like China and Russia, argues that a country has the right to control the Internet, including the DNS, within its own borders, just as it controls physical territory.

The Internet Assigned Numbers Authority (IANA) emerged informally in the 1970s as a set of technical functions managed by Postel and others. It maintained control of the Internet’s core address book through a direct contract with the United States government. It wasn’t a formal organization but managed domain names, IP addresses, and protocol numbers that were crucial for the network to operate as a single, interoperable system. In the 1990s, the Clinton-Gore administration recognized the emerging problems and created ICANN, the Internet Corporation for Assigned Names and Numbers, although overall management still remained with IANA.

In March 2014, the Obama administration asked ICANN to convene the Internet’s global multistakeholder community and come up with a new system for managing the Domain Name System (DNS), explicitly transitioning the oversight of specific key Internet functions away from the US government. This process gathered academics, civil society, governments, individual users, technical experts to come up with ideas to replace NTIA’s historic stewardship role.[2]

In 2016, the US government officially transitioned oversight of the Internet Assigned Numbers Authority (IANA) functions to ICANN. The transition was a landmark event that marked the end of the US government’s direct, formal oversight role over the DNS root zone. However, it did not create a fully privatized system, nor did it eliminate government influence. The reassignment simply transformed and globalized it.

Before 2016, the US Department of Commerce’s National Telecommunications and Information Administration (NTIA) held the contract for the IANA functions. This agreement meant the US government had the final, formal sign-off on any changes to the DNS root zone file, the authoritative master list of all top-level domains. While evidence of abuse was never established, its existence was a central point of political contention, giving the US a unique position of ultimate authority.

The 2016 transition let this contract expire. This change officially ended the US government’s unilateral oversight. The direct, “keys to the kingdom” role was replaced by a system where accountability flows to a global, multi-stakeholder community. The US moved from being the system’s overseer to being one of its most influential participants.

The transition did not create a “fully privatized” structure. The goal was not to sell the DNS to the private sector but to cement the multi-stakeholder model of governance and ward off authoritarian control. ICANN is a non-profit public-benefit corporation, not a for-profit company.

This model represents a unique global governance structure that allows different groups to have a voice in the decision-making process. This structure included the technical community, such as engineers and academics, who built the Internet’s infrastructure. Corporations (like Samsung here in Korea) that rely on the DNS for their brand and operations have important input. Civil society, including non-commercial users and public interest groups also participates. Lastly, nation-states with an interest in public policy and security participate. The system is designed so that no single entity, whether a company or a government, can capture or control the DNS.

While direct US control has diminished, government influence is still a powerful force within ICANN through the Governmental Advisory Committee (GAC). The GAC is the formal channel through which over 170 nations, including the US, China, Russia, and South Korea, provide advice to the ICANN Board on public policy matters.

The GAC’s advice is technically non-binding, as ICANN’s bylaws require the board to formally address and justify any decision that goes against it. In practice, the GAC holds significant sway, ensuring that government perspectives on issues like security, sovereignty, and law enforcement are deeply integrated into the DNS management process.

Therefore, the transition did not remove governments from the equation; it shifted the dynamic from unilateral US oversight to formalized, multilateral government influence within the broader multi-stakeholder community.

This overarching conflict is playing out across several key political battlegrounds. One is the rise of National DNS Firewalls and “Splinternets.” This development is the most direct manifestation of government control. Increasingly, nations are mandating that Internet Service Providers (ISPs) within their borders use state-managed DNS resolvers. These resolvers act as a national firewall, allowing the government to block access to specific domain names associated with foreign news outlets, opposition movements, or social media platforms.

China’s Great Firewall is a notable example, but Russia’s efforts to create a “sovereign internet” (RuNet) that can be functionally disconnected from the global DNS root represent the ultimate goal of this movement. This trend is creating a fragmented Internet, or “splinternet,” where a user’s access to information is determined by their geographic location, directly challenging the idea of a single, global network.

The Geopolitics of ICANN and Root Zone Management

At the highest level, the political struggle centers on who controls ICANN and the DNS root zone—the master list from which the entire global DNS hierarchy is derived. Although ICANN is now an international non-profit, its historical ties to the US government remain a significant point of contention.

Nations advocating for digital sovereignty are deeply uncomfortable with this US-centric arrangement. They consistently campaign to transfer the authority for Internet governance from ICANN to a United Nations body, such as the International Telecommunication Union (ITU). This move would shift power from the multi-stakeholder community to nation-states, giving governments a direct vote on how the Internet is run. This potential divide is a fundamental geopolitical fault line that defines nearly every international discussion about Internet governance.

The DNS is also a critical piece of commercial infrastructure. For a global corporation like Samsung in South Korea, the integrity and exclusive control of samsung.com are non-negotiable for its brand identity, security, and global e-commerce.

Corporations exert significant political influence within ICANN to create and enforce strong trademark protection policies. This is a constant battle, as they fight against cybersquatting and seek to control how their brand names are used in new Top-Level Domains (TLDs).

From .com to .xyz, the TLD market has been lucrative since the commercialization of the Internet in 1995. Assigning domains has been like printing money. The creation of new gTLDs, such as .app, .shop, or .news, has transformed domain names into a multi-billion-dollar industry. The political process within ICANN for approving and auctioning these new domains is intense, pitting powerful corporate consortia against each other as they vie for control over valuable digital real estate.

Challenges from Alternative DNS and AI

A growing counter-movement seeks to bypass this entire political structure. Decentralized DNS systems, such as the Ethereum Name Service (ENS), built on blockchain technology, and privacy-focused public resolvers like Quad9, offer an alternative to the traditional, centralized, hierarchical model. These systems are inherently more resistant to censorship by a single government or corporation. While still niche, they represent a significant technical and political challenge to the established order, promising a return to a more distributed and less easily controlled Internet.

AI is poised to fundamentally transform the DNS system by transitioning its management from a reactive, human-supervised process to a predictive and automated one. While this will bring significant technical benefits, it will also intensify the geopolitical tensions between the US and other nation-states by creating powerful new tools for both centralized control and decentralized resistance.

The core conflict over whether the DNS is governed by a US-centric, multi-stakeholder model (ICANN) or by sovereign nation-states will be amplified, with AI becoming a key weapon in this struggle. Operationally, AI will enhance the DNS, making it faster, more efficient, and vastly more secure. Instead of just reacting to DNS-based attacks like DDoS, an AI will analyze global traffic patterns to predict attacks before they happen. It can identify the anomalous buildup of a botnet and proactively block malicious queries or re-route traffic, neutralizing threats in real-time.

AI will automate the complex and sensitive process of managing the DNS root zone. It can validate requests for changes, check for errors, and implement updates with a speed and accuracy that surpasses human capability, reducing the risk of catastrophic configuration mistakes. AI-powered resolvers will be able to optimize DNS lookups based on real-time network conditions and user behavior, creating faster and more resilient connections.

These technical advancements will become powerful tools in the ongoing political battle over who controls the Internet’s core infrastructure. For nations like China and Russia, which advocate for state-centric control, AI is a potential game-changer. It allows them to build vastly more sophisticated national DNS firewalls.

An AI-powered system can move beyond simply blocking a list of domain names. It can analyze traffic patterns in real-time to identify and block the behavior associated with VPNs and other censorship-evasion tools, making state control more dynamic and difficult to circumvent.

This change gives these nations a powerful new argument. They can frame their sovereign DNS as a matter of superior national security and efficiency, managed by an AI tuned to their country’s specific needs. Conversely, the US and its allies will argue that only the current global, multi-stakeholder model can provide proper Internet security.

They will argue that only a global system has access to the diverse data needed to train an unbiased AI capable of defending the entire Internet. A national AI, they will claim, would be inherently blinkered and less secure.

This innovation transforms the debate at ICANN. The political tensions will shift from who has formal oversight of the root zone to questions like whose AI is managing the system? What are its hidden biases? Can the algorithms be audited for neutrality? The battle for control of the DNS will become a battle for control over the AI that runs it.

Summary and Conclusion

This post outlines changes in the Domain Name System (DNS) from a simple technical ledger into a central battleground for international politics. The core conflict lies between the US-led multi-stakeholder model of governance, embodied by ICANN, and the push for digital sovereignty by nations such as China and Russia, which seek state-centric control. The 2016 transition of IANA oversight from the US government to the global multi-stakeholder community did not end government influence, but rather formalized it on a multilateral basis.

This tension now plays out in several arenas: the rise of national DNS firewalls creating “splinternets,” geopolitical struggles over who controls ICANN, intense corporate lobbying for trademark protection, and the lucrative market for new domain names. Emerging technologies, such as decentralized DNS and AI, are poised to intensify this conflict further, offering powerful new tools for both state control and censorship evasion.

The emergence of multilateral DNS governance reveals that no amount of technical or organizational change can erase the fundamental political struggle for control. The 2016 transition was not the end of this tension, but merely the beginning of a new, more complex chapter. The introduction of AI will not solve the debate between multi-stakeholderism and digital state-centric sovereignty. AI will become the next powerful weapon in that fight.

Ultimately, the battle for the Internet’s future will not be about who holds the management contract, but about who writes the code and controls the intelligent algorithms that will soon manage the world’s most critical address book.

Notes

[1] Drezner, Daniel W. All Politics Is Global: Explaining International Regulatory Regimes. Princeton, N.J.: Princeton U, 2008. Print. Chapter on “Global Governance of the Internet.”
http://press.princeton.edu/titles/8422.html. Also see Drezner, D. (2004). The Global Governance of the Internet: Bringing the State Back In. Political Science Quarterly, 119(3), 477-498. doi:10.2307/20202392

[2] The change from IANA to ICANN resulted in the successful stewardship transition in 2016, transferring oversight of critical Internet functions from the US government to a global, decentralized, multistakeholder model. These changes reflected the Internet’s growth, the need for more inclusive governance, and ongoing efforts to address security, accessibility, and internationalization challenges. As the Internet continues to innovate, the management of DNS will likely adapt to meet new demands and challenges in the digital landscape.

Note: Chat GPT was used for parts of this post. Multiple prompts were used and parsed.

Citation APA (7th Edition)

Pennings, A.J. (2025, Sep 22) The International Politics of Domain Name (DNS) Governance, Part 3. apennings.com https://apennings.com/digital-geography/the-international-politics-of-domain-name-dns-governance-part-3/

Share

Tweet

© ALL RIGHTS RESERVED

Not to be considered financial advice.

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: artificial intelligence, democratic political economies, digital geography, intellectual property, technology management, telecom policy and net neutrality
Tags: Domain Name System (DNS) > Internet Assigned Numbers Authority (IANA) > Internet Corporation for Assigned Names and Numbers (ICANN) > Jon Postel > Paul Mockapetris > top-level domains (TLDs)

Situating Gold in the Substitution-Computational-Telecom Stack of Global Finance

Posted on | September 20, 2025 | No Comments

Gold prices have increased substantially in the last few years from hovering continuously around $2,000 to $3,647/oz on September 19, 2025. As an appreciating asset, gold has become popular for many individual and institutional investors. It has also become a substantial holding of reserves for many central banks worldwide. When a central bank or an investor buys gold on the modern grid, they are rarely taking physical delivery. Instead, they are buying the symbol XAUUSD.

Crucially, the symbol is priced in US dollars, which means gold now functions as a special class of asset within the dollar-anchored system, not as a competitor outside of it. Gold is reduced from a material commodity to a symbolic inscription in a Bloomberg terminal or a central bank spreadsheet.

This post examines how gold currently operates within the semiotic-computational-telecom (SCT) stack of spreadsheet capitalism. Gold currently functions not as a direct currency, but as a potent semiotic anchor for ‘safe-haven’ value.[1] Its symbolic representation is priced and managed through sophisticated computational models that are synchronized across the global telecom grid. Gold operates as an alternative anchor that represents historical memory, geopolitical hedging, and systemic counterweight.

Gold in spreadsheet capitalism is an inscribed number (semiotic substitution), a variable in financial formulas (symbolic computing), and a globally synchronized price stream (telecom infrastructure). Gold today is no longer the official “cell anchor” of the global financial spreadsheet (as it was under the Bretton Woods system when priced at $35/oz and other countries required to peg their currencies to the dollar within a 1-3% band).[1] However, it still operates within the semiotic–computational–telecom stack of spreadsheet capitalism as a special “actant,” carrying symbolic weight, computational functions, and networked circulation across terminals and inducing trading actions.

Gold as Symbolic Substitution Token

The foundational step is the semiotic substitution of the physical gold bar with a universally recognized ticker symbol: XAUUSD. This symbol no longer represents a medium of exchange, but rather a set of powerful, abstract concepts. These include safety, history, an inflation hedge, and a non-sovereign store of value.

When a central bank or an investor buys the gold symbol it is usually a purchase of “financial insurance” against geopolitical risk, currency debasement, or systemic instability. However, recent price increases have also made it a profitable trade.

Gold substitutes for a range of meanings. It is a hedge against inflation (e.g., “XAU/USD” formula cell), a geopolitical “insurance” asset that substitutes for trust in the USD system, and a cultural signifier of permanence and stability across millennia. These substitutions enable gold to circulate in financial systems as numbers and formulas, rather than as physical bars. Its semiotic power rests in its ability to represent non-dollarized value.

Formulating Power with Gold

XAUUSD is given life and integrated into the global financial system through formulaic, symbolic computation. This is where its price is determined and its risk characteristics are modeled. Gold is deeply embedded in the functions and formulas of spreadsheet capitalism. It is an important component of risk formulas that utilize gold prices as inputs to calculate portfolio volatility. It is also used in hedging strategies such as option pricing formulas and swap functions. Correlation matrices also compute gold’s correlation to USD, oil, or Treasury yields.

The vast majority of gold trading occurs in the derivatives market, particularly futures on the COMEX (Commodity Exchange). The price of a gold futures contract is a purely computational product, derived from formulas that factor in the spot price, the risk-free interest rate (SOFR), storage costs (“cost of carry”), and time to expiration.

The most popular way for investors to hold gold is through Exchange-Traded Funds (ETFs) like GLD and GOLY. The price of a GLD share is a formula based on the net asset value (NAV) of the physical gold held in trust, minus fees.[2] This formulation allows the symbol of gold to be traded with the liquidity of a stock.

Gold’s symbol is a critical input for global risk models. Formulas constantly calculate its correlation to other assets (stocks, bonds, currencies), and its Value at Risk (VaR) formula is used by institutions to manage portfolio-wide exposure.

Gold plays a crucial role in ‘computing’ systemic anxieties. When confidence in fiat (especially USD) wavers, models shift weight toward gold as an input into hedging formulas. This underscores the importance of gold in managing systemic anxieties, making the buyers appreciate its function in the financial system.

Central banks also use computational inscriptions that include gold. Their reserve composition spreadsheets include gold holdings, with formulas that track percentage shares of gold versus USD/Euro reserves.

Gold in the Gridmatic Telecom Stack

The telecom grid of interlinked terminals and exchanges synchronizes all of this symbolic and computational activity into a single, globally recognized, real-time price for gold. Bloomberg, Reuters LSEG Workspace, and Wind terminals log second-by-second spot and futures prices. Clearinghouses (CME, LBMA) record gold futures, ETFs, and swaps. Gold-backed ETFs (GLD, etc.) synchronize millions of spreadsheet cells across retail and institutional portfolios.

The key nodes in this grid are the London Bullion Market Association (LBMA), which sets the benchmark spot price, the COMEX in New York, which drives futures pricing, and the thousands of financial terminals (Bloomberg, LSEG) that distribute this data.

Digital infrastructures (COMEX servers, LBMA vaulting systems, Shanghai Gold Exchange) operate as networked actants stabilizing the semiotic and computational layers. This telecom synchronization enforces a single global price of gold, regardless of whether it is traded in London, Shanghai, or Chicago.

The telecom stack ensures that a price change in a COMEX futures contract is reflected in the price of the GLD ETF and the XAUUSD spot price on every trader’s screen from Seoul to Frankfurt in microseconds. This creates one unified and constantly updated “fact” — the global price of gold — making it a perfectly liquid, globally fungible asset within the digital architecture of spreadsheet capitalism.

Gold’s Role in Time-Space Power

Gold creates time-space power within the stack of spreadsheet capitalism by being transformed from a heavy, physical object into a weightless, placeless (XAUUSD) digital symbol.[2] This symbol’s future value can be computationally priced and traded, with all actions now synchronized globally by the telecom grid, allowing actors to exert influence across vast distances and into the future.

Semiotic substitution is the foundation of gold’s space-compressing power. A physical gold bar sitting in a vault in London or New York is replaced by the universal ticker symbol XAUUSD on a terminal screen. This act disembeds the value of gold from its physical location. A central banker in Seoul doesn’t need to arrange for the costly and slow physical transport of gold bars to rebalance reserves. Instead, she can trade the symbol XAUUSD instantly. This substitution makes gold’s value placeless and perfectly mobile, allowing it to be controlled and reallocated anywhere on the grid at the speed of light. This substitution is the SCT’s power to collapse space.

The computational stack also gives gold its power over time. The XAUUSD symbol is fed into complex formulas, primarily for pricing derivatives like futures and options. A gold futures contract is a formulaic promise to buy or sell gold at a predetermined price on a future date. By trading these contracts on an exchange like the COMEX, a mining company or a jeweler can lock in their costs or revenues months in advance, protecting themselves from price volatility. An option on gold provides the right, but not the obligation, to trade at a future date.

These computational instruments allow actors to stretch their influence and decision-making forward in time. They are using formulas to manage future risk and make binding commitments about the future, today. This symbolic computation is the power to colonize and control future economic possibilities.

The telecom stack is the grid that synchronizes these activities globally, creating a single, unified arena where time-space power is exercised. When a major fund in New York executes a large trade in gold futures, the price change is not a local event. The telecom grid of networked exchanges, servers, and terminals ensures the new price is reflected instantaneously on the screens of every other participant, from a bank in London to a sovereign wealth fund in Tokyo.

This instant synchronization means that power is transmitted across the globe without delay. An action taken in one financial center has an immediate and unavoidable consequence in all others, forcing real-time adjustments and reactions. The grid creates a single, global “present” for the gold market, enabling instantaneous coordination and control of capital across planetary distances.

Gold currently anchors emerging-market attempts at monetary independence (e.g., BRICS discussions of gold-linked settlement). In this sense, gold acts as a shadow spreadsheet cell — not the central one, but one always available to be “activated” when the dollar grid weakens.

Gold no longer synchronizes the world’s money clock (as it did under gold convertibility) but now operates as a counter-clock. It ticks against the USD and eurodollar grid, rising when trust in dollar formulas falters.

Summary and Conclusion

Sophisticated computational formulas price gold derivatives and ETFs, while modeling their risk characteristics. The global telecom grid synchronizes this data across financial terminals, creating a single, real-time price. This process transforms gold into a weightless, placeless asset, granting actors who trade its symbol the “time-space power” to exert financial influence instantly across the globe and into the future.

Gold in spreadsheet capitalism is an inscribed number (semiotic substitution), a variable in financial formulas (symbolic computing), and a globally synchronized price stream (telecom infrastructure). It does not displace the USD as the dominant central cell, but its persistence ensures that the global financial spreadsheet always has a non-dollar column available for gold. It serves as an alternative anchor, representing historical memory, geopolitical hedging, and a systemic counterweight.

In the modern financial system, gold no longer functions as a currency but as a powerful symbolic asset within the dollar-anchored framework of “spreadsheet capitalism.” Its physical form is replaced by the digital symbol XAUUSD, which represents abstract concepts like “safe-haven,” “inflation hedge,” and “geopolitical insurance.” This symbol is integrated into the global economy through a Semiotic-Computational-Telecom (SCT) stack.

The analysis reveals that gold has become a paradoxical actor in the global financial grid. While it is traded and priced entirely within the US dollar’s computational system, its symbolic meaning is rooted in being the ultimate alternative to that system. It functions as a dormant “shadow cell” in the global spreadsheet, a counter-clock ticking against the main dollar-based mechanism.

Gold’s modern power, therefore, comes not from its potential to replace the dollar, but from the ever-present threat, inscribed in every financial formula, that it could be activated if trust in the current system fails. With substantial price increases over the last two years, is it reasonable to conclude that global finance is facing deep-seated systemic issues, or unwarranted lack of faith in the USD centered global grid?

Citation APA (7th Edition)

Pennings, A.J. (2025, Sep 20) Situating Gold in the Substitution-Computational-Telecom Stack of Global Finance. apennings.com https://apennings.com/how-it-came-to-rule-the-world/digital-monetarism/situating-gold-in-the-substitution-computational-telecom-stack-of-global-finance/

Notes

[1] I wrote my MA thesis on the Bretton Woods system and how deregulation and technology created a new system in the 1970s.
[2] Gold is a chemical element with the chemical symbol Au. It is an orange-yellow metal that is dense and heavy, yet soft, and malleable. Historically, this made it an excellent store of wealth, and medium of exchange. Gold does not rust or chip. It can be melted down and reformed in alternative shapes that maintain their form over long periods of time. Historically this has made it the preferred medium for bullion to be stored or coinage that can circulate widely, facilitating economic exchange. But that has changed over time.

Disclaimer: LLMs were used in researching this topic and the content of this post should not be considered investment advice.

Share

Tweet

© ALL RIGHTS RESERVED

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI/broadband policy & engineering/financial economics. From 2002-2012 he taught comparative political economy, digital economics, macroeconomics, and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: artificial intelligence, data analytics and meaning, democratic political economies, digital media economics, digital monetarism, digital spreadsheets, financial news, financial technology, geopolitical risk, smart new deal, sustainable development
Tags: Bretton Woods system > gold > SCT Stack > spreadsheet capitalism > XAU/USD

USD Centrality and Network Effects in the Global Economy

Posted on | September 15, 2025 | No Comments

Discussions about replacing the US dollar as the world’s dominant reserve and transacting currency have diminished recently, as the BRICS rhetoric has weakened. However, the issue remains on the global agenda, as the world often suffers from significant dollar shortages, and fintech continues to innovate. Although its role as a reserve currency has diminished to roughly 60%, roughly 80–90% of global trade invoices are still priced in USD, even when neither party is American.

This post addresses the USD in the context of spreadsheet capitalism and its representational, formulaic, and networking techniques. It uses its central logic (substitution – symbolic computing – telecom infrastructure) to explain the USD/eurodollar’s centrality and network effects. It shows that the USD and its eurodollar shadow retain centrality because they are not just monetary units but cells at the center of the global spreadsheet, reproduced and reinforced daily by formulas running on Bloomberg, Aladdin, Workforce, and Wind terminals operating worldwide.

The standard definition of network effects is that the more people who use a medium, the more valuable it becomes. In this case, the more actors (banks, corporations, central banks, exporters/importers, and remitters) use the USD, the stronger the need for dollar-denominated assets, such as US Treasuries, repos, and eurodollars. The SWIFT (Society for Worldwide Interbank Financial Telecommunication) network is particularly valuable because it is used globally to transfer funds from one bank to another.

This means that USD/eurodollar retains dominance not just because of US economic size, but because its spreadsheet centrality as a reference cell, formulaic operator, and synchronized node element. These combine to create powerful network effects. These effects continuously reproduce the dollar’s role as the world’s reserve currency, invoicing unit, and liquidity solution, creating unique time–space power over globalization and trade.

Currently, the USD/eurodollar is the absolute reference cell ($USD$1) in global spreadsheet finance. Formulas in financial terminals (NPV, IRR, discounting, FX, VaR, repo haircuts, and swap resets) are constantly calculated relative to this cell, forcing alignment to the USD. In the global balance sheet “spreadsheet,” central banks, sovereign wealth funds, and corporates hold reserves in cells denominated in USD and eurodollars. [1]

This process is daily, recursive, and performative. The centrality of the USD is not given; it is produced and reproduced every time a formula is run. The USD/eurodollar isn’t just the dominant currency; it is the spreadsheet cell through which the world makes its financial calculations, continuously recomputed by formulas that lock global finance into its orbit. This makes the USD, global finance’s universal semiotic anchor, reinforced daily.

Network Effects of the Spreadsheet Stack

The USD’s global power is not just about US GDP or military strength; it’s also about network effects built into the financial infrastructure, where the dollar sits at the center cell of the global spreadsheet, anchoring liquidity, collateral, and pricing. Strong network effects are one of the primary reasons the USD remains the dominant reserve, funding, and transaction currency. These calculations are global, synchronized by terminals and telecom infrastructure.

In the semiotic–computational–telecom stack of spreadsheet capitalism, three major factors converge to generate USD network effects. These entrench dollar dominance and project financial time-space power to shape global liquidity rhythms and constrain the monetary policy space of other states. These are semiotic substitution, symbolic computing, and gridmatic network structure at a global scale.

Semiotic substitution makes USD the symbolic unit of global equivalence. In the reigning spreadsheet logic, USD is the universal cell of value. Every financial instrument — from Treasury bonds to repos, FX swaps, or commodities is denominated, quoted, or can be translated into US dollars. The USD substitutes for local currencies, creating a standard unit of account that translates heterogeneous values into a single unit of equivalence. The more instruments priced in USD, the more necessary it becomes for others to use it. Liquidity consolidates in the dollar. Actors anywhere in the world can instantly benchmark value in USD, binding local markets into a shared temporal rhythm (Fed policy cycles, Treasury auctions) producing time-space power.

Symbolic computing in spreadsheet capitalism ties global instruments into formulas that recalculate from a USD central cell. Through the mechanism of spreadsheet logic – formulas for discounting, swaps, or collateral haircuts are built around dollar benchmarks (SOFR, Fed Funds, Treasury yields).

The semiosis (meaning-making) effect is that USD benchmarks function as symbolic operators. Change one cell, like the Fed rate, and the recalculations ripple globally. This symbolic centrality means that dollar instruments are self-reinforcing: hedging, risk modeling, and valuation all “speak the language” of dollar pricing, reinforcing network effects. The USD wields time-space power because symbolic recalculations of global liquidity are temporally synchronized to its own monetary calendar.

Gridmatic infrastructure provides a networked visual interface as data digitizes and transmits those substitutions and recalculations at scale. It provides the digital plumbing of dollar circulation through SWIFT, CHIPS, CLS, and Fedwire. These form the computational-telecom backbone that routes and clears dollar transactions. Eurodollar markets add offshore balance sheets, while Bloomberg terminals, Alladin, and LSEG Workspace supply real-time spreadsheet overlays. The infrastructure itself becomes a representational grid where financial messages (such as MT103/202 in SWIFT, repo trade tickets, and swap confirmations) serve as symbolic substitutions, which are processed computationally.

Network effects are produced as each new participant increases the value of the system by extending the reach of USD liquidity, locking in path dependence, and raising switching costs. The telecom infrastructure makes dollar liquidity instantaneous across geographies while anchoring it in US jurisdictional time (New York business hours, Fed settlement deadlines). The gridmatic infrastructure enforces the wiring of payments in USD. Even offshore markets (eurodollars, petrodollars, Hong Kong’s dim sum bonds) need this grid to clear settlements.

Together, these factors combine to generate network effects that entrench dollar dominance and project temporal and spatial power. One factor is the collateral gravity of US Treasuries that concentrates balance-sheet activity around itself. When stress spreads globally, the network effects flip into liquidity gravity. Capital seeks the safety of USD, regardless of where it originates. The Dollar Milkshake Theory is an especially clear illustration of the network effects of the USD within spreadsheet capitalism.

Brent Johnson’s “Milkshake Theory” highlights the USD as a liquidity magnet. Because dollars are the most liquid, they remain the cheapest to hedge and easiest to transact. The Milkshake Theory is a vivid way of explaining why the USD attracts liquidity, and it aligns closely with our framework of spreadsheet capitalism and USD network effects.

Conclusion: Formulaic Reinforcement

The USD and eurodollar retain centrality because they are not just monetary units but cells at the center of the global spreadsheet, reproduced and reinforced daily by formulas running on Bloomberg, Aladdin, Workforce, and Wind terminals. A “global spreadsheet” grid — with USD as the absolute $A$1 reference cell, and formulas showing how FX trades, repos, and swaps would visualize this argument.

When we say the USD/eurodollar is a cell at the center of the global spreadsheet, we mean every balance sheet in the world, whether in New York, London, Shanghai, or São Paulo, has at least one column denominated in USD. A loan in yen, a bond in euros, or a derivative in pesos ultimately references the USD cell through conversions, swaps, or collateral rules.

The formulas running on Bloomberg, Aladdin, Wind, and similar terminal systems constantly recalculate this cell into action. FX conversions such as =Amount * FXRate(USD/JPY) ensure that any yen trade is mapped back to USD. Discounting/valuations like =NPV(SOFR, Cashflows) run collateral and swaps priced off USD benchmarks.[2] Risk models use Aladdin’s VaR and stress-test engines to run simulations with USD Treasuries as the safest anchor cell. In eurodollar transactions, Bloomberg’s repo haircuts and collateral flows formulaically reference US Treasuries, reinforcing USD liquidity. Every recalculation pulls other currencies, assets, and risks back into alignment with the USD reference cell.

Because markets operate like spreadsheets set to “auto-recalculate,” they continually reproduce the dollar’s centrality. Overnight repos reset collateral values daily. SOFR fixes are also computed and published daily, re-anchoring the time value of USD-denominated money. Swap resets adjust every three or six months, recalculating obligations in USD terms. Central bank operations (e.g., Fed swap lines) enter the sheet as “inputs” that cascade across the grid. Each recalculation doesn’t just measure — it re-performs the dollar’s centrality, turning semiotic substitution into lived liquidity.

This process makes the USD/eurodollar cell the universal denominator — the reference column against which all other rows and columns reconcile. It’s the pivot cell. If Excel had one “absolute reference” ($USD$1), that’s what the dollar is. Future USD challenges will face the prospects of “tippy” network effects that could shift centrality quickly if the right conditions occur.[3]

Citation APA (7th Edition)

Pennings, A.J. (2025, Sep 15) USD Centrality and Network Effects in the Global Economy. apennings.com https://apennings.com/dystopian-economies/electric-money/usd-centrality-and-network-effects-in-the-global-economy/

Notes

[1] An absolute reference in a spreadsheet, such as ($USD$1), is a formula element that uses dollar signs ($) to lock a cell’s reference so it doesn’t change when a formula is copied to other cells. In ($USD$1), the “USD” is not a standard column reference; a true absolute reference would be $A$1, where the dollar signs lock both the column (A) and the row (1).
[2] Examples like “=Amount * FXRate(USD/JPY)” and “=NPV(SOFR, Cashflows)” are illustrative but may oversimplify complex terminal calculations. They are simplified proxies in this case.
[3] In discussing the weaknesses of USD network effects, Amy Shuen in Web 2.0: A Strategy Guide suggested that network effects can be “tippy” and cause disruption such as the rapid user transition from MySpace to Facebook. Can the USD tip quickly to another currency?

Share

Tweet

© ALL RIGHTS RESERVED

Not to be considered financial advice.

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: artificial intelligence, data analytics and meaning, democratic political economies, digital spreadsheets, electric money, enabling frameworks
Tags: eurodollars > Network effects > USD

APEC Presentation: Healing the COP (Common Operating Picture) with AI and APIs for Disaster Management

Posted on | September 13, 2025 | No Comments

Edited remarks from an invited presentation at the Asia-Pacific Economic Cooperation (APEC) meeting on July 31, 2025. Due to a family responsibility in New York at the same time, I invited a former PhD student to work with me on the slides and give the presentation. My deepest gratitude goes out to Dr. Saebom Jin for her collaboration, insights, and excellent presentation.

Good afternoon, distinguished participants at APEC’s SDMOF, the 18th Senior Disaster Management Officials’ Forum. My name is Saebom Jin, from the National AI Research Lab at KAIST. It is my true privilege to be here today at this important dialogue on strengthening disaster leadership in the Asia-Pacific region.

Together with Prof. Anthony Pennings of SUNY Korea, we prepared this presentation, studying how emerging technologies like AI can enhance existing disaster information platforms. In particular, drawing on the Remediation Theory from media studies, we attempted to examine how AI might be integrated into traditional information systems used in disaster management. Our particular concern was the Common Operating Picture (COP) used in disaster management control rooms. Our aim is to better understand the deeper implications of such integration in supporting effective and trustworthy leadership in times of crisis.

As you might have heard many times, we live in a VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) world. And it is more and more difficult to predict something in the future, even in the near future, as historical data is incapable of predicting the future – especially when it comes to the changing climate and its disaster implications.

I would say “the odds of odd things happening are increasing” – we have just witnessed very tragic disaster outbreaks in Texas, 3 years ago when a winter storm caused widespread electricity blackouts, and also just a few weeks ago, when flash floods washed away the Camp Mystic summer camp, taking the lives of more than 27 young girls.

It is not a matter of data scarcity. In fact, we have encountered a proliferation of data from a variety of sources – from satellite imagery to IoT sensors and social media. In this situation, the challenge we face is not the lack of data but the overwhelming complexity of making sense of it.

In such environments, leadership must innovate — not only in decision-making but also in navigating these multi-layered information environments of crucial information. In this presentation, I would like to suggest that effective leadership must embrace three qualities:

Data-driven decision making using insights from complex systems to guide action.

Anticipatory response by identifying patterns and taking proactive measures (Typhon monitoring and warnings)

Adaptive systems moving beyond static command structures to dynamic and interface-enabled leadership.

This shift requires more than technology. It demands a rethinking of how we design information platforms to support human judgment.

Here is where Remediation theory offers us insight. According to the famous media theorist Marshall McLuhan, the content of any medium is always another medium. Following up on this observation, Jay David Bolter and Richard Grusin described remediation as the process by which new media refashion and incorporate older media forms. In this remediation theory, new technologies, like spreadsheets, are designed to improve upon the prior technologies to mediate a more authentic sense of reality.[2]

In other words, this isn’t about simply replacing old technological systems with new ones, but adopting and adapting the functions of the existing systems to help leaders better perceive, interpret and act through media. Drawing on the Italian roots of the word remediari it is about “healing” the media’s access to an authentic reality.

Here are the key concepts of this theory:

The logic of Immediacy is the idea that technology should closely reflect the real world in order to create a sense of presence and realism, as seen in movies, television news, and day-time soap operas or live video streaming. Relevant examples are real-time video-conferencing and live data feeds. Drawing on first person video from the affected zones often provides the transparent immediacy of authentic experience. Television reporters for example often go out into water and wind to dramatize the weather events.

Hypermediacy indicates multiple representations within a heterogeneous space. It is a layered, often windowed interface with GIS informatics and multichannel communications to combine images, sounds, text, and video. This approach offers an augmented, quantitative view of the world, drawing on the power of numeracy and remediating tools like graphics and maps.

The most radical concept in remediation refers to the transformation of prior media into a new framework, creating a more authentic, interactive, and actionable experience. In this concept, we do not just replace the legacy systems that leaders and practitioners have long relied upon, but transition from one to another by integrating new media forms into the COP.

In practice, we have witnessed how media have been transformed or remediated to better convey valid information out of a vast amount of data – from printed material to radio and television, from TV news to social media updates, and so on. In such an environment, crisis communication and disaster leadership involves navigating various types of digital interfaces rather than issuing directives alone.

Among the various mechanisms and tools, we focused on the Common Operational Picture (COP) as a mediation tool that can incorporate novel technologies using as AI and APIs, and create value for disaster leadership in response to climate variance and data variance.

COP is a shared, real-time view of operational data for decision-makers, teams, and agencies involved in multi-agency disaster risk reduction operations. By providing up-to-date information through dashboards and alerts, COP supports situational awareness and coordinated action.

Let me present the idea of how COPs can be remediated with AI and APIs. First, APIs act as bridges, integrating and normalizing diverse data streams into a hypermediated, yet unified operational view. APIs incorporate various data streams and make them available for the COP.

Next, AI processes and analyzes this massive and disparate data in real-time dynamic media environments. While APIs serve as the infrastructure for remediation, AI acts as the operating system for the remediated COP. By utilizing NLP, computer vision, and predictive analytics with machine learning algorithms, AI-remediated COP simplifies the data and facilitates interpretation and prediction.

It helps build transparency and enhance leaders’ ability to act confidently under pressure. In summary, AI enables the COP to transition from a static display of information to a dynamic intelligence platform with crucial mediated information on demand.

Another notable feature of the remediated COP is the development of Personalized Operational Pictures (POPs). While COPs used to be confined to control rooms, they are now evolving into POPs that provide individualized pictures based on roles within the command room and out in the field. With APIs and AI, these personalized mobile platforms can provide role-specific and actionable intelligence into the hands of leaders and practitioners during times of crisis. In complex disaster environments, this means leaders see only what matters, empowering faster, more focused decisions without being overwhelmed by irrelevant data.

This chart illustrates data flow of the suggested model.

Now then, let me move on to the design principles in order to achieve effective leadership with this remediated system in practice. As technology alone does not guarantee the success of this system, how to apply the theory into practice in a way to enhance trust and leadership is key.

The first principle is about data curation and visualization. When in crisis, more data does not necessarily lead to a better decision. However, this does not mean the complexity of a disaster should be ignored. The key feature of the suggested platforms is, therefore, providing remediated visuals to help leaders grasp the full picture of a disaster with contextualized and curated data. AI-assisted COPs can summarize trends of multiple data streams.

This remediated platform must be designed to build trust through a transparent yet effective explanation of complexity. Rather than simply being exposed to the increasing volume and variety of data, users need to be able to make sense of it through effective platforms.

The next principle regards communication. Using official websites or applications is recommended, but also, the hypermediated platforms should support users with targeted messages based on their roles and location, for example.

A technical feature for two-way interaction through the platform and advanced dashboards is also recommended for clear and credible communication within teams and with the public.

Effective COPs balance the two logics of remediation: 1) Hypermediation reveals data-richness, layered complexity, and enables tailored views for different roles. Transparent Immediacy involves delivering real-time clarity and minimizing cognitive load in urgent situations. Together, they ensure that leaders are not overwhelmed by data, but empowered by insight.

This design philosophy extends beyond control rooms. Public-facing dashboards showing real-time rainfall, river levels, or evacuation orders foster institutional trust and transparency — key components of effective disaster leadership.

As these systems evolve, leaders must also evolve. Effective disaster leadership today means:

– Championing user-centered design
– Ensuring interoperability across media systems
– Training not just on using technology but on interpreting complex information environments. In short, leadership is becoming interface-native.

In this presentation, AI is not just as a processor, but as a media theorist in action. AI is the operating core of the modern COP, serving as an intelligent media system that delivers clarity for responders, in-depth insights for analysts, and trust for the public.

Guided by Remediation Theory, AI-enabled COPs become more than tools or information repositories — they are strategic tools for decision-making, trust-building, and narrative construction during crises.
AI-assisted COPs empower responders, inform the public, and bring more order to chaotic disaster scenarios. Still, we need to ensure that the balance between immediacy and accuracy, as well as between simplicity and integrity, remains in the AI-assisted COP. That is why remediated COPs is more than technology.

Lastly, let me leave you with this quote by Bolter and Grusin:

“Our culture wants both to multiply its media and to erase all traces of mediation.”

As leaders, we must balance these tensions — embracing complexity without losing clarity, and ensuring that our technologies remain tools for human judgment, not barriers to it.

Thank you for your attention. I look forward to discussing how we can co-create smarter, more trusted disaster information systems that empower leadership across the Asia-Pacific region.

Citation APA (7th Edition)

Pennings, A.J., Jin, S. (2025, Sep 13) APEC Presentation: Healing the COP (Common Operating Picture) with AI and APIs for Disaster Management. apennings.com https://apennings.com/crisis-communications/apec-presentation-healing-the-cop-common-operating-picture-with-ai-and-apis-for-disaster-management/

Notes

[1] APEC stands for Asia-Pacific Economic Cooperation. It is a regional economic forum that promotes trade, investment, economic growth, and cooperation among its 21 member economies around the Pacific Rim. The group aims to foster prosperity, sustainable economic development, and more resilient economies in the Asia-Pacific region.
[2] Bolter, Jay David, and Richard Grusin. Remediation: Understanding New Media. Cambridge, MA: MIT Press, 2000.

Share

Tweet

© ALL RIGHTS RESERVED

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and holds a joint Research Professor position for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: crisis communications, disaster risk management, journalism, media strategies, mobile technologies, sensing technologies, space systems, technologies of meaning, visual literacy and rhetoric
Tags: and Ambiguity) > APEC > Asia-Pacific Economic Cooperation > Complexity > COP (Common Operating Picture) > Hypermediation > Jay David Bolter > Remediation > Transparent Immediacy > Uncertainty > VUCA (Volatility

Equilibrium and the Turn from Political Economy to Economics

Posted on | September 7, 2025 | No Comments

This post looks at the historical turn from political economy to “economics,” when the concepts of equilibrium and marginal analysis transformed economics from logical reasoning, historical analysis, and philosophical arguments into a neutral science. This shift moved economics away from political economy, focusing instead on market mechanisms and consumer behaviors that could be represented in graphs, equations, and supply-demand modeling with mathematical connections.[1]

The Enlightenment (1685-1815) in Europe brought a new emphasis on reason, individual rights, natural law, and social progress. It began to replace the worldview dominated by absolute monarchy, mercantilism, rigid social hierarchies, and religious dogma. This shift in thinking had a profound impact on European societies, laying the groundwork for the development of modern democracies and our understanding of political economies.

Thinkers like Adam Smith, often considered the father of modern economics, and other classical political economists, such as David Ricardo, John Stuart Mill, and François Quesnay, developed their theories on political economy based on logical reasoning, historical analysis, observation, and philosophical arguments. They used illustrative examples rather than mathematical precision to argue their positions.

In an age before political arithmetic and the collection of national “state-istics,” began to create a numerical representation of the state, political economists sought to develop arguments that would influence merchants, monarchs, and other politicians, not just other scholars. They were “policy” oriented and sought to make society better.

However, economics would take a turn away from “normative economics” (what should be) to what are called “positive economics” (describing what is), due primarily to the work of the “marginalists” in the 1870s. This group included Carl Menger, William Stanley Jevons, and Léon Walras. Alfred Marshall gave visual legitimacy to the marginalists’ ideas by developing the graphical representation of supply and demand, which is taught in economics courses.

While they worked independently, these four economists converged on a revolutionary idea. They argued that the economic value of a good is not determined by the labor required to produce it (the classical political economy view) but by the “marginal utility” it provides to a consumer. What is the usefulness of one additional unit of that good? And how would that influence price? This “marginalist” perspective was born from a new philosophical and corporate environment that prized scientific positivism and individualism over the historical and social concerns of the Enlightenment’s early political economists.

There was a powerful drive to make the social sciences as rigorous and objective as the natural sciences, like physics. The goal was to discover universal, mathematical laws that governed human society, just as Newton had discovered laws that governed the planets. The language of calculus and equilibrium was seen as more scientific than the historical narratives of the political economists.

They were also under pressure to develop narratives that countered the growing interest in critical perspectives. The classical labor theory of value had been used by Karl Marx to argue that capitalism was inherently exploitative. The marginal utility theory provided a powerful counterargument, suggesting that if value originates from a consumer’s subjective desire, rather than from labor, then there is no inherent conflict between capital and labor. Instead, the market is a harmonious system where rational individuals all pursue their own self-interest, leading to a stable and efficient equilibrium.

Carl Menger (Austrian School) argued that value is not an inherent property of a good but exists in the individual who needs it. His focus was on human action and causality, explaining how individuals make choices based on their personal, ranked preferences. The subjective theory of value challenged the labor theory of value proffered by Adam Smith and Karl Marx.

William Stanley Jevons (British School) developed the theory of marginal utility and one price, arguing that the value of a good is determined by the satisfaction gained from consuming one more unit of it, not by the cost of production. Jevons sought to make economics a true science by applying mathematics. He framed economics as a “calculus of pleasure and pain,” arguing that a rational person would consume a good up to the point where the pleasure from the last unit (its marginal utility) equals the pain or cost of acquiring it.

His one price theory argued that prices would converge to one price where markets would clear was important in the development of supply and demand charts. William Stanley Jevons gave one of the first and most explicit formulations of the Law of One Price in his 1871 book, The Theory of Political Economy. It was a foundational component of his effort to build a scientific and mathematical theory of economics.

Jevons’ core argument was that a “perfect market” would naturally lead to a single prevailing price for any identical good. His famous statement on the matter is: “In the same open market, at any one moment, there cannot be two prices for the same kind of article.” His reasoning was based on the flow of information and the actions of rational traders. If two different prices for the same item existed, a trader could instantly profit by buying the good at the lower price and selling it at the higher price. This act of arbitrage, when performed by many traders, would increase demand for the lower-priced good (raising its price) and increase the supply of the higher-priced good (lowering its price) until the two prices converged into one.

Léon Walras (Lausanne School) argued markets must be “cleared” of any excess supply and demand to be in the state of equilibrium. The existence of excess supply in one market must be matched by excess demand in another market so that both factors are balanced out. Walras was the most mathematically ambitious of the group. He developed general equilibrium theory, creating a complex system of simultaneous equations to show how supply and demand across all markets in an economy could, in theory, reach a state of equilibrium. His work became the foundation for much of modern microeconomic modeling.

Alfred Marshall’s (Neoclassical Synthesis) landmark 1890 book Principles of Economics, blended the new marginalist ideas about consumer demand and utility with the classical economists’ focus on the costs of production. He created the famous supply and demand “scissors” diagram (seen above), which remains the most recognizable tool in economics. It was Marshall who popularized the term “economics” to replace “political economy,” cementing the discipline’s shift towards a social-neutral science.[2]

All four political economists were crucial in shifting economic thought towards marginalism and developing the theory of equilibrium.

Chronology of Major Works on Marginal Analysis

1862 – William Stanley Jevons presents his paper, “A General Mathematical Theory of Political Economy,” which first outlined his theory of marginal utility. It received little attention at the time but predated the major publications of the 1870s.

1871 – Carl Menger publishes Grundsätze der Volkswirtschaftslehre (Principles of Economics). This work established the Austrian School’s subjective theory of value, arguing that the value of a good is determined by the importance an individual places on its least important use. Also that year, William Stanley Jevons publishes The Theory of Political Economy. In this book, he fully developed his marginal utility theory using calculus, arguing that rational individuals consume until the marginal utility of a good equals its price.

1874 – Léon Walras publishes the first part of his Éléments d’économie politique pure (Elements of Pure Economics). Walras independently formulated marginal utility theory but, most importantly, integrated it into a comprehensive mathematical system of general equilibrium, showing how all markets could theoretically clear simultaneously.

1890 – Alfred Marshall publishes his highly influential Principles of Economics. This work did not introduce marginalism but synthesized it with classical economic thought. Marshall combined the marginalist theory of demand (utility) with the classical theory of supply (cost of production) to create the famous supply-and-demand analysis that became the foundation of neoclassical economics.

Walras provided the most complete framework for general equilibrium, while Jevons and Menger offered key insights into individual behavior and the subjective nature of value that underpin equilibrium conditions. Increased supply of something eventually decreases the value of it and demand will decrease. Jevons analyzed how individuals would purchase goods until their marginal utilities were proportional to the exchange ratios (prices).

This would lead to equilibrium in exchanges between consumers and suppliers of goods and services. Walras is known for developing the concept of general equilibrium and envisioned the economy as a system of interconnected markets, where the prices and quantities of all goods and services are simultaneously determined by supply and demand. Walras sought to express this theory mathematically, using equations to represent the equilibrium conditions across all markets. His work laid the groundwork for formal mathematical modeling in economics.

Alfred Marshall then popularized the charting of supply and demand in graphs that are still taught in economics courses. Walras invented the initial equations, and Marshall expanded on them to develop the concepts of equilibrium price and marginal analysis that could be visualized through supply and demand curves. Marshall developed a stunning representation of prices adjusting until the quantity of goods supplied equals the quantity of goods demanded. This visualization revolutionized how economists understood markets and its participants.

Subsequently, economics became more of a technical field, relying on graphs, equations, and models rather than moral and political philosophy. Jevons and Marshall showed that prices are not just determined by historical social forces but by individual consumer preferences and firm behavior in a market system. This shift would mark the decline of classical political economy (which focused on broad social and political factors) and the rise of modern economics. The new economics centered on mathematical modeling and allowed economists to study market mechanisms in isolation, ignoring broader social forces, including the centrality of labor.

Citation APA (7th Edition)

Pennings, A.J. (2025, Sep 7) Equilibrium and the Turn from Political Economy to Economics. apennings.com https://apennings.com/dystopian-economies/equilibrium-and-the-turn-from-political-economy-to-economics/

Notes

[1] This was an intriguing question for me in graduate school. When I taught macroeconomics, comparative political economy, and media economics at NYU, I had a chance to do additional research but lacked a good publishing opportunity.
[2] Sharma, S. (2020). The Death of Political Economy: A Retrospective Overview of Economic Thought. Economic Research-Ekonomska Istraživanja, 33(1), 1750–1766. https://doi.org/10.1080/1331677X.2020.1761854

Share

Tweet

© ALL RIGHTS RESERVED

---

Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Category: dystopian economies, science and technology studies, telegraphic political economy, the smith effect
Tags: Adam Smith > Alfred Marshall > Carl Menger > David Ricardo > equilibrium price > François Quesnay > Léon Walras > The Wealth of Nations (1776) > William Stanley Jevons

« go back — keep looking »