Tag Archives: Bitcoin

What is the core purpose of money/currency and value exchange?

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Copyright © 2025 Michael Herman (Bindloss, Alberta, Canada) – Creative Commons Attribution-ShareAlike 4.0 International Public LicenseWeb 7.0™, TDW AgenticOS™ and Hyperonomy™ are trademarks of the Web 7.0 Foundation. All Rights Reserved.

At the level of human society—not just markets—the real purpose of currency and value exchange isn’t money itself. It’s coordination.

Currency is a social technology that solves a deep, ancient problem:
How do millions of people who don’t know or trust each other still cooperate at scale?

Here’s what that really means.


1. The core function: enabling large-scale cooperation

Before money, exchange depended on:

  • Barter (which rarely matches needs),
  • Reputation inside small tribes,
  • Or coercion.

Currency replaces all three with something more powerful:
a shared belief system that lets strangers coordinate effort, resources, and time.

At a societal level, money allows:

  • A farmer to feed a software engineer,
  • A nurse to support a miner,
  • A poet to live in a city built by people they’ll never meet.

Not because they trust each other — but because they trust the system of exchange.

So the real purpose is:

To turn individual labor into collective civilization.


2. Value exchange is how society answers one question

“What matters enough that we will allocate our lives to it?”

Every society must constantly decide:

  • What gets built?
  • Who gets rewarded?
  • What work is considered worthy?
  • What future we are steering toward?

Currency is the mechanism that turns those abstract choices into concrete incentives.

Money doesn’t just move goods.
It moves human attention, time, and creativity.

Where value flows, society flows.


3. Money is not wealth — it’s a memory system

At a deep level, currency is a distributed memory of contribution.

It records:

  • Who gave value to society,
  • In what amount,
  • And stores the right to claim value later.

In this sense, money is society’s way of saying:

“You helped before. You can draw from us now.”

That’s why when currencies collapse, societies don’t just lose purchasing power — they lose trust, continuity, and social coherence.


4. The moral dimension: money as a proxy for meaning

In healthy societies, value exchange roughly tracks:

  • Contribution,
  • Skill,
  • Effort,
  • Risk,
  • Social benefit.

In unhealthy societies, it drifts toward:

  • Power,
  • Rent-seeking,
  • Manipulation,
  • Extraction.

So at a civilizational level, currency is also a moral instrument.
Not because money is moral — but because what it rewards defines what a society becomes.

Tell me what a society pays for, and I’ll tell you what it worships.


5. The deepest purpose: reducing violence

Before reliable exchange systems:

  • Resources were taken by force.
  • Status was enforced through dominance.
  • Survival meant conflict.

Currency allows societies to replace coercion with consent.

Instead of:

“I take what I need.”

We get:

“I earn what I need by giving value.”

This is one of humanity’s greatest civilizational upgrades.

Money is, in a very real sense,
a technology for peace.


6. Where this is heading

As societies evolve, the purpose of value exchange is shifting again:

  • From tracking labor → tracking impact.
  • From rewarding extraction → rewarding regeneration.
  • From scarce tokens → to trusted coordination systems (reputation, data, access, participation).

Currency is slowly becoming less about money
and more about governance of attention, trust, and collective direction.


In one sentence

At the level of human society, the real purpose of currency and value exchange is:

To transform individual effort into collective civilization by enabling trust, cooperation, and coordinated meaning at scale.

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Interplanetary Blockchains: Fact or Fiction?

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Short answer: Bitcoin and Ethereum, as is, cannot function as a single, strongly consistent global blockchains across interplanetary distances. The speed of light breaks their assumptions.

Below is how this likely evolves.


1. The fundamental constraint: light-speed latency

Even at light speed:

  • Earth ↔ Moon: ~1.3 seconds
  • Earth ↔ Mars: ~3–22 minutes (one-way)
  • Earth ↔ Alpha Centauri: ~4.3 years

Bitcoin:

  • Block time ≈ 10 minutes
  • Global propagation already struggles on Earth

Ethereum:

  • Slot time ≈ 12 seconds
  • Finality ≈ 12–15 minutes

➡️ Interplanetary latency makes real-time consensus impossible.


2. What breaks first

Bitcoin

  • Massive fork rates between planets
  • Mining becomes planet-local
  • Long reorgs when chains reconnect
  • “Longest chain” rule becomes meaningless across light-minutes

Ethereum

  • Validators can’t attest in time
  • Finality stalls or fragments
  • Slashing becomes unfair (latency ≠ fault)

Result: chain fragmentation


3. Likely evolution: a multi-layer, multi-chain reality

Instead of “one chain to rule them all,” we get hierarchical and federated systems.

🪐 Planetary chains (Layer 1)

Each planet runs its own sovereign chain:

  • Earth Bitcoin
  • Mars Bitcoin
  • Titan Ethereum
  • Orbital habitat rollups

Consensus remains local, fast, and fair.


🌌 Interplanetary settlement layers

Slow, high-latency chains act as settlement and reconciliation layers:

  • Checkpoint summaries
  • State commitments
  • Merkle roots exchanged every days/weeks/years
  • Disputes resolved asynchronously

Think:

“SWIFT, but cryptographic and trust-minimized”


⚡ Local execution, delayed finality

  • Payments on Mars finalize instantly on Mars
  • Interplanetary transfers finalize only after long delays
  • Time becomes a first-class protocol parameter

4. Ethereum adapts better than Bitcoin

Ethereum’s roadmap already points here:

  • Rollups
  • Data availability layers
  • Modular consensus
  • Validium / Sovereign rollups

Future Ethereum ≈ coordination layer, not a monolithic chain.

Bitcoin, by contrast:

  • Extremely conservative
  • Likely remains local digital gold
  • Used as planetary reserve asset
  • Interplanetary BTC ≈ wrapped, bonded, or escrowed representations

5. Money becomes relativistic

In a galactic civilization:

  • “Finality” is contextual
  • “Now” differs by planet
  • Markets price latency risk
  • Contracts include light-delay clauses

Example:

“Funds release 42 minutes after Martian confirmation unless Earth chain disputes.”


6. Human + agent governance will matter more than protocol purity

In a post-anthropocentric and agent-rich society (your recurring theme):

  • AI agents arbitrate interplanetary disputes
  • Economic zones negotiate trust frameworks
  • Protocols encode principles, not absolutes
  • Blockchains become constitutional layers, not absolute truth machines

7. The likely end state

Bitcoin and Ethereum don’t die — they evolve:

  • From global ledgerslocal truth + delayed reconciliation
  • From synchronous consensusasynchronous trust
  • From one chaindiversified civilizational layers

In short:

There will be no “galactic blockchain” — only a constellation of ledgers, stitched together by math, time, and shared principles. 🚀

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Decentralized Identifiers (DIDs) as Barcodes for Secure, Trusted Digital Communication

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Copyright © 2025 Michael Herman (Bindloss, Alberta, Canada) – Creative Commons Attribution-ShareAlike 4.0 International Public License

Abstract


The invention of the barcode transformed retail and supply chains by providing a universal, machine-readable identifier that ensured accuracy, efficiency, and interoperability across diverse systems. Similarly, Decentralized Identifiers (DIDs) represent a foundational innovation for digital ecosystems: a universal, cryptographically verifiable identifier that enables trusted communication across domains and platforms. This paper explores the analogy between DIDs and barcodes, examining how both enable end-to-end interoperability, reduce friction, and unlock new models of value creation.

Copyright © 2025 Michael Herman (Bindloss, Alberta, Canada) – Creative Commons Attribution-ShareAlike 4.0 International Public License


1. Introduction

In 1974, a pack of Wrigley’s gum was scanned at a Marsh supermarket in Ohio, marking the first use of the Universal Product Code (UPC). That moment marked the beginning of a transformation in retail, logistics, and global commerce. By providing a standardized identifier, barcodes automated inventory management, accelerated checkout, reduced human error, and laid the foundation for today’s global supply chains.

Digital ecosystems in the 21st century face an equivalent problem: how to create universal, secure, and machine-readable identifiers that work across organizations, platforms, and jurisdictions. While domain names, IP addresses, and UUIDs serve as identifiers, none are self-sovereign, portable, and verifiable across trust boundaries. Decentralized Identifiers (DIDs) aim to solve this.

This paper argues that DIDs are the barcodes of digital trust: a universal, machine-readable system for identifying entities in secure communications, enabling a new end-to-end supply chain of digital trust.


2. The Barcode Revolution

2.1 Before Barcodes

  • Manual price tags and clerical data entry.
  • Inventory tracking prone to human error.
  • Inefficient supply chains with frequent stockouts and overstocking.
  • Lack of standardization across retailers and manufacturers.

2.2 With Barcodes

  • Universal identifiers: UPC and EAN standards.
  • Machine readability: fast, automated scanning reduced labor costs and errors.
  • End-to-end traceability: from manufacturer → distributor → retailer → checkout.
  • Scalability: millions of products, billions of transactions.

Impact: Barcodes enabled just-in-time inventory, global retail expansion, and precise supply chain optimization [Brown, Inventing the Barcode, 2010]. The key insight: a universal, interoperable identifier unlocks systemic efficiencies across the value chain.


3. DIDs: A Digital Barcode for Trust

3.1 What are DIDs?

Decentralized Identifiers (DIDs) are globally unique identifiers that are self-sovereign, verifiable, and resolvable without reliance on centralized registries. Defined by the W3C, DIDs point to DID Documents, which contain public keys, service endpoints, and metadata necessary for establishing secure communication.

3.2 Core Features

  • Universality: A DID can represent a person, organization, device, or digital asset.
  • Machine readability: DIDs are structured and resolvable by software.
  • Cryptographic trust: Integrity and authenticity are verifiable through signatures and key material.
  • Decentralization: No single issuing authority required; anyone can create a DID.
  • Extensibility: Support for multiple DID methods (blockchain, ledger, peer-to-peer).

3.3 Why It Matters

Just as barcodes freed retail from manual, siloed processes, DIDs free digital ecosystems from centralized identity silos (e.g., social logins, proprietary identity providers).


4. Mapping the Analogy: Barcodes vs. DIDs

Barcode PropertyDID EquivalentImplications
Universal product identifierUniversal decentralized identifierEnables global recognition of digital actors
Machine-readableMachine-resolvable DID DocumentAutomated verification by software agents
Standardization (UPC/EAN)W3C DID Core standardCross-platform interoperability
Scannable at every point in supply chainResolvable across trust domainsEnd-to-end verifiable identity
Facilitates inventory managementFacilitates trust managementEnsures secure digital transactions
Enables retail efficiencyEnables digital trust ecosystemsReduces cost, friction, and fraud

5. Benefits of the Barcode Analogy

  1. End-to-End Traceability
    • Barcodes track goods from origin to checkout.
    • DIDs enable trust from authentication through data exchange to audit.
  2. Automation and Efficiency
    • Barcodes eliminated manual entry; DIDs eliminate manual trust establishment.
  3. Interoperability
    • Any barcode scanner can read a UPC; any DID-compliant system can resolve a DID.
  4. Scalability
    • Barcodes scaled to billions of products; DIDs can scale to billions of devices, people, and services.
  5. Systemic Transformation
    • Barcodes reshaped retail; DIDs could reshape finance, healthcare, IoT, and governance.

6. Limits of the Analogy

  • Centralization vs. Decentralization: Barcodes are managed by centralized registries (GS1), whereas DIDs are inherently decentralized.
  • Trust Layer: Barcodes encode only identity (the product number), not integrity or authenticity. DIDs add cryptographic verifiability.
  • Complexity: Scanning a barcode is simpler than resolving a DID, which requires cryptographic operations and network lookups.
  • Adoption: Barcodes achieved rapid, global retail adoption; DIDs remain in early deployment phases.

7. Strategic Implications

7.1 Identity and Access

DIDs could serve as the UPC of digital identity, enabling universal, interoperable identity across organizations.

7.2 Supply Chain and IoT

DIDs can extend barcodes’ logic into digital-physical convergence, providing secure digital twins for physical assets.

7.3 Finance and Governance

DIDs provide the foundational layer of trust for verifiable credentials, smart contracts, and cross-border compliance.

7.4 The “Barcode Moment”

Just as retail only transformed once barcodes were widely adopted, the digital trust economy will require a tipping point of DID adoption to realize systemic benefits.


8. Conclusion

The barcode transformed retail by enabling universal, machine-readable product identification across the supply chain. DIDs can do the same for digital ecosystems by enabling universal, machine-readable, and verifiable identity.

If DIDs achieve broad adoption, they could serve as the universal identifiers of digital trust, enabling secure, scalable, and interoperable communication across the global digital economy — much as barcodes enabled the rise of global retail supply chains.


References


Inspired by the book Reshuffle by Sangeet Paul Choudary.

Produced as the outcome of a conversation between Michael Herman and ChatGPT. October 1, 2025.

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Tokenize Every Little Thing (ELT)

[Since first writing this article in January 2018, I’ve concluded that Ethereum is not capable of being a platform for Tokenizing Every Little Thing. Ethereum is a one-trick pony x 1500 when it comes to creating large-scale decentralized applications (i.e. Ethereum/Solidity smart contracts are best for creating single, simple entities like alt-coins). Checkout slide 56 of this presentation: NEO Blockchain Vancouver 20180315 Meetup. The NEO Blockchain and NEO Smart Economy is the best available 3rd generation distributed application platform on the planet and improving every day. Michael Herman, March 17, 2018]

[Also checkout the webcast The NEO Smart Economy, Smart Processes, and Smart Data. Michael Herman, April 9, 2018]


 

Just over one year ago, I introduced the concept of graphitization and talked about #Graphitization of the Enterprise. I opened the article with the challenge:

Move beyond digitalization of the enterprise to graphitization of the enterprise.

For 2018 and beyond, the challenge is simpler but more difficult:

Tokenize Every Little Thing (ELT)

To provide more context, let me first quote from the introductory paragraphs of the #Graphitization article.

Here’s a great diagram that explains this concept [graphitization]. (click on the diagram to enlarge it)

graphitization-new-world-of-it
Figure 1. The New Model of IT

Graphitization of not only all of your corporate information assets across all of your constituencies and stakeholders – at the data, application entity, and business object level – but also the graphitization of all of the interconnections between every business process, application system, infrastructure component, cloud service, vendor/service provider, and business role that uses, manages, or stores corporate information (Crossing the EA Chasm: Automating Enterprise Architecture Modeling #2).

Use graphitization to make your existing corporate information more available, more usable, and more informative. Graphitization enables you to “Keep Calm and Have IT Your Way“.

What is #Graphitization?

#Graphitization is a data science and enterprise architecture-inspired framework and process model for modeling, ingesting, organizing, analyzing, and visualizing any domain of endeavor by using graphs – networks of connected objects and relationships with each object and relationship annotated with additional descriptive information (metadata).

Why #Tokenization?

Given the burgeoning preoccupation of the world’s business, finance, government, and technology sectors with blockchain technologies, cryptocurrencies, and token-this and token-that, the buzzword for 2018 will be #Tokenization …the creation of tokens (multiple versions of tokens) to represent every thing on the planet …Every Little Thing (ELT).

While individuals, startups and larger organizations are trying to dream up the next big, one-off, token or crytocurrency, why not just admit that, “in the end”, everything will be represented by a token?

Why try to knock these off one at a time (e.g. Bitcoins, Ethers, altcoins, CryptoKitties, letters of credit, auctions, escrow agreements, electronic health records (EHR), electronic medical records (EMR), etc.) when the ultimate goal to to create a universal interconnected graph of ELT (Every Little Thing) in the universe?

Why #graphitize the enterprise when you can #tokenize the universe?

What is #Tokenization?

Let’s get a little computer-sciency for just a minute. A common task to to take an input stream (a string of characters, a stream of data, a data file or database table), analysis it, and convert it into a collection or sequence of higher-level tokens for further analysis (a process that can be applied recursively). Here’s an explanation from Wikipedia

In computer science, lexical analysis, lexing or tokenization is the process of converting a sequence of characters (such as in a computer program or web page) into a sequence of tokens (strings with an assigned and thus identified meaning). A program that performs lexical analysis may be termed a lexer, tokenizer, or scanner… [https://en.wikipedia.org/wiki/Lexical_analysis]

…and later in the same Wikipedia article…

Tokenization

Tokenization is the process of demarcating and possibly classifying sections of a string of input characters. The resulting tokens are then passed on to some other form of processing. [https://en.wikipedia.org/wiki/Lexical_analysis#Tokenization]

Coming up for air… Why not represent ELT that happens in the universe as a stream of blockchain transactions?

  • the events in your life?
  • everything that occurs during a Presidential election?
  • the 24-hour cycle of one day changing into the next?
  • the activity-by-activity and task-by-task execution of a business process?
  • a stream of events from your Internet-of-Things (IoT) enabled car, toaster or refrigerator?

Jim Gray and TerraServer

In one of his several presentations on Scalable Computing (circa 1999), Jim Gray (relational database pioneer and Turing Award winner) describes the TerraServer project in the following way:

[Users navigate] an ‘almost seamless’ image of earth.

SkyServer was a similar project quarterbacked by Gray:

TerraServer allowed access to newly-available satellite imagery with resolution of 1.5 meters/pixel. SkyServer, a collaboration with Alexander Szalay and his colleagues at Johns Hopkins, allowed access to astronomical data from the Sloan Digital Sky Survey. SkyServer led to additional work with astronomical data, … [https://amturing.acm.org/award_winners/gray_3649936.cfm]

Tokenize Every Little Thing

With the advent of blockchain technologies (in particular, the Ethereum extensible blockchain platform), why can’t we embark on a grander mission to tokenize Every Little Thing? …and including all token-pair relationships (TPRs).

What will it take?

What needs to change in the Ethereum blockchain platform? Will Ethereum be able to scale to support modeling, ingesting, organizing, analyzing, and visualizing of Every Little Thing (ELT)?

On your mark, get set, …

Best regards,
Michael Herman (Toronto)

mwherman@parallelspace.net

Other Important References

  • Gordon Bell, MyLifeBits MSR Project (early 2000’s). I remember Jim Gray telling this story but I had trouble finding a proper reference because I thought it was Gray’s story instead of Bell’s.  I now know better but I’ve already finished the above article. A Wikipedia MyLifeBits reference can be found here. YouTube videos can be found here, here, and others over here. Channel 9 videos: Part 1 and Part 2. Computerworld article (2008). Business Inside article (2016).
  • Gordon Bell’s MSR web page.

 

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Filed under Architecture Reference Models, blockchain, Business Value, Data Science, Enterprise Architecture, Ethereum, Every Little Thing, graph database, Graphitization, How do we think, Nethereum