How rural economics led me to the nanoeconomics of AI

I grew up in a village, where we raised livestock: pigs, goats, geese, chickens, ducks, rabbits, a dog, and many cats. We had a large garden with apples, beans, tomatoes, and other produce. In the fall, I would dig over the garden, working in cow manure as a natural fertilizer. Fall was also for harvesting plums, apples, pears, and many other delicious fruits. The nearby forest was another source of food for the winter.

We would then make plum jam and apple juice, preserve all sorts of fruits from the garden and the forest, and store the jars in our cellar. This was supplemented by potatoes, wood, coal, onions, and everything else a big family needs for the winter.

It wasn't until much later that I realized how profoundly this experience had shaped my worldview.

My family was always concerned about making the most prudent decisions possible. How many rows of bush beans and pole beans should we plant? How many plots for potatoes, for strawberries, and all the other fruits and vegetables?

Theory Meets Reality

Later, I studied economics in three countries, on three continents, in three languages. I grew up in a planned economy, entered the market economy after adolescence, and for my thesis, I studied a third type: the Argentinian economy, which has been described as socialism without a plan and capitalism without a market.

Yet, it is my childhood experiences that dominate my economic thinking and research to this day.

During my studies, I was fortunate to have a professor of the philosophy of science who introduced us to the theories of Nobel laureates in economics. In every lecture, he would power through a new highly sophisticated model. This was the most rigorous intellectual training of my life. Two sentences have stuck with me:

"Nothing is as practical as a good theory" (Kurt Lewin)

"All models are wrong, but some are useful" (George E.P. Box)

Drawing on this background, I developed the nanoeconomic framework, a holistic economic model, to capture and understand the impact of AI on the real economy and the business world.

The nanoeconomic framework is strictly based on microeconomics, since microeconomics has already uncovered all relevant economic mechanisms and principles.

However, due to its confinement to idealized conditions and assumptions, microeconomics is unable to model the granular effects of AI in business and the economy. While data-driven, it has so far failed to incorporate information as a factor in its models.

Information overwhelms microeconomic models because it depends on the recipient and the context.

Information is relative, subjective, and therefore not measurable. In this respect, it closely resembles the economic variable of utility. We cannot objectively measure subjective utility either, yet we readily work with a utility function using metric variables—one of the many conundrums in economic theory.

The Kitchen Insight

So, where to start with building an appropriate economic model to capture AI and its impacts?

It started in the kitchen, really.

I remember it vividly: the mountains of fruit we processed every September and October, the specialized equipment, the long evenings gathered around the big table, and the vast, wood-fired stove we used to preserve the precious harvest. I realized that the kitchen is a self-contained microsystem—a primal production hub where, from the beginning of mankind, we created everything needed to sustain ourselves. At its heart was something simple: the fire, the source of all light and warmth.

From that realization, it was a small step to see the larger picture: the fruit had to come from somewhere, the energy to fuel the fire had to come from somewhere, and the tools themselves had to come from somewhere. That was the genesis of the nanoeconomic framework.

(This kitchen analogy proved so powerful that I've made it the foundational model for my new book, Kitchen AI: An easy way to understand and use the real power of AI.)

Building the Framework

Nobel laureate Kenneth Arrow was the first to use the term in 1987, yet he applied it only narrowly within institutional economics and never explored it further. This proved to be a blessing in disguise: his endorsement gave me the confidence to pursue my own ideas and cleared a path for further discoveries.

And discover I did.

To my astonishment, I found that—contrary to all expectations—nanoeconomics could be derived directly from the essential microeconomic concepts on a one-to-one basis.

So my next step was to use the microeconomic agents, mechanisms, principles, relationships, and causal chains, to delve deeper—to the decision-making level of individual agents and their specific contexts, the so-called nano-level.

By delving deeper, we can map microeconomic variables with atomic granularity and—at long last—properly account for information as the critical factor it is in economic decision-making.

Equipped with this realistic, holistic, and information-sensitive Nanoeconomic Framework, we can now explore how AI affects and alters the relationships between economic variables, agents, their activities, and processes, and how the use of AI could eventually transform the entire economic system.

Closing the Circle

While developing this framework, I was repeatedly struck by how seemingly self-assuredly I classified and evaluated fundamental concepts and relations without consulting the vast literature to see if someone had already proposed or contradicted them.

My professor, with his intellectual detours and wisdom, gave me confidence. But my childhood experiences were my greatest aid. The people around me made their economic decisions quickly, relying on simple rules of thumb or heuristics.

Examining their decisions more closely with hindsight, I can, however, recognize the microeconomic principles guiding their everyday behavior:

• The efficiency principle
• The opportunity cost principle
• Competition (for the sweet fruit jars from the cellar)
• Diminishing marginal utility
• Marginal return, marginal productivity, marginal costs
• And, of course, entropy (again in the cellar, this time the potatoes).

For this reason, I would like to thank my professors for navigating me through the depths and shoals of economic science – microeconomics, macroeconomics, and business administration.

Above all, I thank my family, neighbors, and community for their care and support as I grew up in such a "down-to-earth" environment.

Without all of them, my nanoeconomic framework would never have come into being.

Sources:

Gerlach, S. (2025). The Simple Nanoeconomics of AI: An Economic World Model for Exploring AI Impacts. Available at SSRN 5394649. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5394649