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AI, Compute, and Cryptocurrency

The last article discussed the impact of AI on diminishing productivity value in the current economy. If left unchecked, the long-term effect could drive the value of human labor towards zero. At the same time, it’s expected to produce an abundance of low-cost products.

Similar changes have occurred many times throughout history. For instance, after the invention of the printing press, the value of scribes dropped so drastically that they no longer exist as a distinct social class. The introduction of mechanical looms and weavers made textile production so inexpensive that the poorest quality of clothing we enjoy today would have only been reserved for the upper class in the past. These innovations reduced the value of weaving labor to such an extent that early textile workers, known as Luddites, vehemently opposed mechanical weavers. Even today, we use the term “Luddites” to refer to those who resist technology. The industrial revolution is filled with countless examples of labor-replacing machines that reshaped the economic landscape.

In this early age of AI, where Large Language Models (LLMs) and diffusion models have just started to yield significant productivity, something new is happening. Cognitive work is the first to be encroached upon. Despite the early focus on autonomous driving and robotics, it turns out that pure cognitive work, such as writing and painting, is an easier problem for AI to solve. This development presents a direct challenge to our understanding of intelligence and humanity, with potentially far-reaching implications. AI has already introduced a deluge of cognitive products, such as images and articles, and soon videos and music, at exponentially higher rates. Its economic impact will hit swiftly and intensely, particularly in economies relying on cognitive services.

Virtualization of The World

A more fundamental trend observable in the digital age is the virtualization of the world. In other words, the conversion of everything into pure information. This started with the conversion of text, images, and sound from their physical media of books, prints, and tapes/CDs to digital data on computers. The same can be observed in 3D printing, where physical objects are initially created as digital representations. The medium and the information content of the world, once inextricably intertwined, have now distinctly separated into data and material.

In the internet age, data are not static entities within hard drives but are continuously in motion, flowing and replicating within computer networks. One could argue that the economic value of data stems from their motion of being streamed and consumed. More abstractly, all economic value is derived from the actions of exchange, with digital data being the most fluid of all our inventions.

It seems only natural then, that one of the first applications of digital networks is currency. This first occurred in banking computer networks, and later within decentralized computer networks as cryptocurrency. The topic of cryptocurrency always sparks controversy. Its invention, however, is a logical eventuality of digital virtualization. It elicits divided opinions mainly because its value is fundamentally incompatible with the existing economic order, but this is about to change.

Virtualization of Labour

AI precipitates the virtualization of labor, be it physical or cognitive, though physical labor will likely be the last to transition.

Creating a generative AI model requires a vast set of information on possible outcomes, and an immense amount of compute. Encoded within a generative AI model is a bounded potential set of possible future work. Its application necessitates the exact context, provided as prompts, and compute.

As digital data, the value of an AI model derives from its execution, not from being static, as replication of its data bears no value. Deploying, executing, and transmitting AI data all require compute, making compute the fundamental unit of labor in the AI age.

In the feudal age, land was the basic unit of value, and people were the labor force that brought about productivity. In the industrial age, when machines replaced much of manual labor, energy became the basic value, needed to power machines. To make energy more fungible, currency became the basic abstraction layer representing potential future labor. Despite these changes, humans have always been part of labor value, whether it be operating machines or performing higher cognitive work.

The arrival of AI signals a real possibility that humans will be excluded from much, if not all, labor value for the first time in history. For those tasks that involve only AI, regardless of whether it controls machinery, the fundamental unit of labor is now compute. This significant shift in economics is swiftly approaching.

Cryptocurrency and Compute

When compute becomes the basic unit of labor, a currency to represent future potential compute is needed. Although it’s still challenging to predict what exactly this currency will be, a few deductions can be made:

The currency should share the same abstraction layer as AI compute for the lowest friction of value conversion, i.e., within compute networks as pure information.
It should garner enough trust worldwide.
It needs to have a stable supply for value representation.

Gold is a good example. Traditionally, it represented future potential human labor, as mining and refining gold required a lot of human effort before the industrial revolution. Therefore, it represented distilled past labor and, by extension, potential future labor.

At present, the best digital compute equivalent to gold seems to be Bitcoin, which meets all the criteria:

It’s represented in a decentralized computer network.
It has a well-known, scarce, and stable supply.
Existing Bitcoins represent the global compute used to mine the coins since their inception, as well as the exponentially increasing future compute needed to mine the remaining coins.
Bitcoin has already gained much of the world’s trust and boasts a proven track record.

Of course, several other cryptocurrencies fit these criteria. Bitcoin, however, has the largest market cap and mindshare worldwide, making it the most likely candidate. Many countries will undoubtedly try to implement alternative competing currencies, and it will be a turbulent transition period for the world. But, decentralized cryptocurrencies like Bitcoin are likely to prevail in the long term due to their resilience and low friction of exchange with AI computing layers.

Ethereum is more complex. Its old supply curve was similar to Bitcoin’s, but it has since changed its supply algorithm to reduce gas cost. This means it has transitioned from being a store of value to a computing layer. Ethereum will likely emerge as the computing exchange layer between AI and Bitcoin. In this way, future data objects may shift their value representation towards data-compute hybrids, just as the value of physical books and paintings was once data-materially intertwined.

Predicting how long this shift will take is difficult. Now that AI has become productive non-trivially, this economic shift is already in motion. Given the current accelerated pace of change, it could happen in as little as 3-5 years. Like many things in the world, it will happen all at once over a short period of time. Regardless, we have a front-row seat for the transformation of our age.