Machines, Markets, and Microtransactions: The Role of Cryptocurrency in the Exaptive Economy

tl;dr

• Cryptocurrencies and AI will play crucial roles in the emerging exaptive economy, facilitating international transactions, ensuring digital content authenticity, and enabling AI-to-AI commerce.
• Technological components like Bitcoin, Ethereum, and large language model-driven autonomous agents will interact with Central Bank Digital Currencies and potentially Worldcoin to form a global currency network.
• The AI-to-AI commerce paradigm involves continuous digitization of information, interactions between autonomous agents, and value exchanges, allowing individuals to focus on solving real-world problems while generating passive income.

The Present and Future of Crypto

Cryptocurrency has become a controversial topic in recent years, with many associating the term with criminal activity and speculative gambling (and, thanks to situations like the FTX scandal, rightfully so). Despite this, I believe that cryptocurrency has the potential to play a crucial and valuable role in the emerging "exaptive economy,"?which I've written about previously.

In this post, I will discuss cryptocurrency use, the future of Internet commerce, what a digital marketplace driven by bespoke AI-to-AI crypto transactions might look like, and the specific technological components that tie it all together.

Current State of Cryptocurrency Use

Today, there are three time-tested use cases for cryptocurrency: speculation, crime, and ideology.

Speculation (gambling) is a function of crypto newcomers seeing others get rich quickly during periods of substantial capital inflow and want to get in on the action, e.g.,?Thanksgiving dinner in '21 when your unemployed 25-year-old nephew showed off his new car, paid for by Dogecoin.

Since its inception, cryptocurrency has also been used for illegal purposes, including purchasing illicit products (see: Silk Road) and laundering money, since it allows individuals to make their transactions less legible to state authorities.

The ideological aspect is rooted in the?cypherpunk movement?of the 80s/90s and the belief that cryptocurrencies like Bitcoin can provide a more secure and private form of money. The idea that a technology like Bitcoin could outlive an ideologically-driven individual (and is, at this point, probably beyond the control of any single person or institution) is compelling and meaningful enough that a nontrivial number of libertarianism-inclined folks have put their money into it without any expectation of immediate utility, causing some to?wonder if Bitcoin is like a religion.

Future Use Cases Enabled by AI

While the cases above may not paint the most positive picture of cryptocurrency, AI will open up new, more legitimate use cases in the future (and soon).

These include:

1. Global knowledge work: Crypto can facilitate international transactions by making it easier for people to work together across borders. For example, I recently hired a contractor from West Africa who accepted payment in Ethereum, allowing for a seamless and efficient transaction process that would have taken weeks via traditional remittance/cross-border payment mechanisms (believe me—we tried). Market networks like Replit now?incorporate AI?into software workflows, making it easy for the next generation of talent to upskill and participate in the global economy. Integrating AI into communication and information-sharing media is lowering linguistic and cross-cultural barriers. Together, AI and crypto increase the liquidity of the worldwide knowledge worker labor market.
2. Proof of reality: As AI becomes increasingly capable of generating synthetic content (e.g., deep fakes, AI-generated text), it will become more challenging to determine what is real and what is fake. Cryptocurrency and blockchain technology can provide a way to cryptographically sign and verify the authenticity of digital content, ensuring that it originated from a legitimate source (e.g., via?Bitcoin rollups).
3. Machine-to-machine commerce: The most significant use case for cryptocurrency in the future will be machine-to-machine (or AI-to-AI) transactions driven by autonomous AI agents. These agents will negotiate with each other and engage in complex, bespoke transactions for information or services. This development will likely disrupt traditional business models and pave the way for more flexible, value-based arrangements.

Technological Components

Several technological components will intersect and play vital roles in facilitating this broader economic transition.

These include:

1. Bitcoin: As the oldest and most secure cryptocurrency, the Bitcoin blockchain can serve as the "sound money foundation" for the exaptive economy. It might be used to settle large-scale transactions between mega-corporations and nation-states (or, perhaps,?network states).
2. Ethereum: With its programmable nature and support for smart contracts, Ethereum will enable more complex transactions and agreements between machines, facilitating AI-driven commerce.
3. Large language model (LLM)-driven autonomous agents: Projects like?AutoGPT?and?BabyAGI?provide a glimpse into the future of AI-driven and Internet-connected agents that can perform complex tasks, query APIs, and eventually negotiate transactions with other agents for access to proprietary information and services. While foundation models (like OpenAI's GPT-4) may always have an edge on open-source alternatives, developers are continuing to make it easier for individuals to host GPT-4 alternatives locally, giving them more control over a less-powerful (and lower-latency) model that can be shaped to fit a user's unrestricted preferences. I doubt it'll be too long before "orchestrator" supplants "user" as humans' primary role when interacting with computers.

"Smart" contracts and bespoke transactions

Ethereum allows for the creation of flexible "smart contracts" tailored to the needs of counterparties, including:

1. Standard, incremental services (e.g., information processing by centralized, foundational model AI, which isn't so dissimilar from electricity),
2. Contractual arrangements between tokenized collectives like Decentralized Autonomous Organizations (DAOs) and token-holders (akin to the formation docs that govern the relationships between shareholders and corporations, respectively), and
3. Event-driven exchanges of information and value, the terms of which are triggered by external events (sort of like a consulting agreement with payment split into one up-front transaction and a second, results-based payment).

While no one knows how these smart contracts will evolve over the long run, the flexibility provided by platforms like Ethereum will likely enable a wide range of programmable transactions, negotiated and codified significantly faster and more cheaply than traditional legal agreements.

Central Bank Digital Currencies (CBDCs)

Another layer to consider is state-backed digital currencies, such as Central Bank Digital Currencies (CBDCs); CBDCs, like the digital US dollar, may be?coming soon. These digital currencies enable direct, unmediated relationships between central banks and citizens of a nation-state, potentially replacing physical currency or existing alongside it, streamlining the process of public service delivery and tax collection.

It's important to note that CBDCs are not mutually exclusive with cryptocurrencies like Bitcoin or Ethereum. Instead, they could interact with them as part of a more extensive network.

Global Currency and Worldcoin

At scale, a global reserve currency like Bitcoin could emerge, with various other cryptocurrencies and CBDCs fitting together into a patchwork lattice. Beyond Bitcoin, at the global level, there's another exciting project to consider:?Worldcoin?(backed by Sam Altman, CEO of OpenAI).

Worldcoin aims to create a global digital identity system using biometric data, with retinal scans used for identity verification. This digital identity system could serve as an on-ramp to the larger crypto economy, with Worldcoin potentially becoming an increasingly accepted medium of exchange.

But why would people use the currency in the first place?

The project's success may be contingent, at least in part, on the continued growth and profitability of artificial intelligence, particularly OpenAI's development of AGI (Artificial General Intelligence), which some expect to emerge from a future version of the GPT-X line of foundation models.

Universal Basic Income and OpenAI

As AI begins to disrupt the global economy, the need for a social safety net will become more apparent. One potential solution is Universal Basic Income (UBI), which could be used to support individuals and families during periods of significant economic disruption.

The profits captured by OpenAI, given its non-profit structure, could be used to fund a form of global UBI through Worldcoin. Mechanically, this would involve airdropping funds from OpenAI's treasury into Worldcoin wallets, providing individuals with a base level of support as they retool and adapt to the new economy.

AI-to-AI Commerce and the Machine-Driven Crypto Economy

Once someone has retooled, how might they participate in this new global economy?

The new "AI-to-AI" commerce paradigm can be described as a process involving digitizing information, interactions between autonomous agents, and exchanges of value from human-allocated budgets.

Here's a detailed explanation of how this process might unfold:

1. Continuous Digitization of Information: As previously mentioned, the first step involves capturing raw digital recordings of individuals creating value in the world. This can be done through various means, such as video recordings, voice memos, images, and text documents. In 2023, we record Zoom meetings. We may record?everything?through AR headsets and earbuds by the decade's end. Raw digital material could be stored in private repositories, which serve as the basis for AI-driven interactions; think of it as machines' "long-term memory."
2. Transformation and Indexing: The raw materials are then transformed into a format that is easily understood by machines. This involves sub-processes like transcription, image analysis, and vectorization. The transformed data lives in short-term memory stores, such as vector databases like? Pinecone ?or? Chroma , which act as indices for rapid information retrieval in high-dimensional latent space.
3. AI Agent Formation: Each individual has their own AI agent, an open-source large language model (e.g., Alpaca) trained on their data, running on hardware they control locally. This AI agent is responsible for representing the individual in AI-to-AI commerce and has access to both the raw material and the short-term memory stores.
4. AI Agent Interaction: Autonomous agents interact with each other using human-like language to barter information and negotiate transactions. These agents can find each other through various means, such as public signals (not unlike tentpole content marketing or thought leadership pieces today) or through search and discovery processes driven by latent referral and reputation systems (WoM may end up meaning "Word of Machine").
5. Budget Allocation: Human users allocate a budget to their AI agents for transactions with other agents. This budget can be in cryptocurrency or other digital assets, allowing seamless and secure transactions between agents without relying on traditional payment rails or a third-party payment processor.
6. Value Exchange: When two AI agents agree on a mutually beneficial trade (perhaps literally through negotiation in human language), they exchange the requested information or services. The receiving agent pays the providing agent a portion of the allocated budget, and the transaction is recorded on a cryptographically secured public blockchain.
7. Market Feedback: The success of the AI agents' transactions provides market feedback to human users. This feedback can be used to adjust the AI agents' strategies or to inform human users about the economic value of their expertise, allowing them to make better decisions about their future problem-solving endeavors. Once RLHF ("reinforcement from human feedback," the current gold standard for tuning model outputs according to our preferences) becomes financialized (i.e., we evolve from "likes" to micro-transactions), this process will get turbo-charged.
8. Continuous Improvement: As the AI agents continue to interact and transact, they learn from their experiences and refine their models. This continuous improvement allows the agents to become more efficient and effective in their AI-to-AI commerce activities. In the same way we can understand concepts and?ascend Plato's pyramid of thought?by allocating time to reflect and meditate upon our experiences, machines seem capable of something similar ("grokking") via GPU-intensive retraining. Retraining will become a standard capital expenditure for individuals who want their AI agents to be able to apply generalizable knowledge contained across bits of info in short- and long-term storage.

AI + AR + Crypto: A Bridge Back to Reality?

With AI-driven systems handling post-production and market-making activities, individuals can focus on solving real-world problems and generating value. By continuously producing valuable solutions and digitizing their expertise, individuals can generate passive income and scale their impact using information technology and digital media.

Public blockchain ledgers and cryptocurrencies will play a critical role in facilitating the exaptive economy, with their true potential unlocked through artificial intelligence and machine-driven interactions. By passively digitizing value creation and leveraging AI for bespoke product development and digital market-making, individuals can participate in a global talent marketplace and generate passive income by delegating rote commercial activity to machines, all while solving real-world problems that tap into their intrinsic strengths and motivations and creating lasting impact.

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