Connecting AI Governance, Ant Colonies, and European History
The author, Timothy Gieseke, has granted permission to reproduce this article from the original on LinkedIn. For an introduction to Timothy’s software GADGET the article: Enhancing AI with Eco-wisdom, offers links to a sample evaluations.
Author note: As a youth I spent many hours on our farm observing ants — different species, different colonies, how they managed day-to-day life and responded to adversity — not knowing they were one of just a handful of superorganisms on the planet. I later wrote about the superorganism concept in my third book, Collaborative Environmental Governance Frameworks: A Practical Guide (2019), where I observed that “the superorganism exists at a level of biological organization between the organisms and the ecosystems, in much the same manner as collaborations exist between organizations and society.”
This blog reopens up the conversation that governance is an instinctive biological trait that humans understood a century ago – and instinctive is not always good.
What I had been watching was how an ant colony governs itself, that is its modes of coordinating decision-making and action-taking; top-down, incentives, and community motivated. Governance is the instinctual architecture that runs below strategy, below culture, below deliberate choice that keeps the ants alive or the superorganism, a term coined by Harvard’s myrmecologist, William Morton Wheeler in the early 20th century.
Abbott Lawrence Lowell, Harvard’s president (1909-1933) the governance empiricist of his era conferred an honorary degree on William Morton Wheeler. In presenting the degree, Lowell said that Wheeler’s life’s work had demonstrated something that no governance theorist had yet put into words:
“Ants, like human beings, can create civilizations without the use of reason.”
Wheeler had spent decades proving it in the field. Lowell recognized, in that sentence, what it meant for everyone who studied human coordination. If governance was instinctual in the colony — if half a million individuals could allocate labor, manage risk, and make collective decisions without deliberation, without law, without reason — then the question for anyone studying human institutions was not whether governance required reason. It was what governance actually ran on when reason was absent. And what it ran on, in the colony and in the human civilization, was architecture.
Lowell knowledge began decades earlier when he completed his six-country survey in 1880–1889 traveling through France, Italy, Germany, Austria-Hungary, England, and Switzerland, interviewing political leaders. Essentially do the work as Elinor Ostrom did a century later.
Lowell recognized these countries did not predetermine how they would coordinate governance logics to meet their objectives — they did it without reason. These configurations emerged through historical pressure, cultural inheritance, military victory, institutional inertia, and the accumulated weight of centuries. The countries Lowell visited were living inside governance architectures they had not chosen any more than the army ant chose its colony.
To better understand his work and their conclusion on human and ant civilizations, I applied, GADGET, a governance assessment and design model based on hierarchy, market, and network logics.
• Hierarchy (H): Coordination through authority, rules, and formal structures. Decisions flow through established chains of command. Legitimacy derives from position, expertise, or legal mandate.
• Market (M): Coordination through competition, incentives, and exchange. Actors pursue self-interest; coordination emerges through price signals and contractual relationships.
• Network (N): Coordination through relationships, trust, and shared values. Decisions emerge through consensus and mutual adjustment. Legitimacy derives from community recognition and relational capital.
Lowell’s countries’ governance footprint (H/M/N ratio) map on the triad as shown based on the countries’ descriptions below.
Lowell’s Field Notes: Six Countries through the H/M/N Governance Triad
Germany Bismarckian Empire · 1871–1890
H:72 M:20 N:8 FOOTPRINT H: Hierarchy is not merely the dominant logic — it is the cultural substrate. Decision authority flows through the official chain with no operational role for civic negotiation or market competition in public domains.
France Third Republic · 1870–1940
H:58 M:32 N:10 FOOTPRINT H:The Third Republic sits firmly in Hierarchy dominance, with Market logic growing alongside industrialization but structurally subordinated to state direction. .
Austria-Hungary Dual Monarchy · 1867–1918
H:62 M:18 N:20 FOOTPRINT HN: The HN footprint is not designed — it is the structural tension between imposed Hierarchy and irrepressible Network logic that the empire could never fully suppress. Imperial Hierarchy provided the formal architecture: throne, army, bureaucracy, common foreign policy.
England Victorian Britain · 1837–1901
H:38 M:50 N:12 FOOTPRINT HM: Victorian Britain is the most Market-dominant major power in Lowell’s survey — the only country where Market logic exceeds Hierarchy in the overall governance footprint. Laissez-faire capitalism was not merely policy but ideology: the deliberate minimization of state apparatus was understood as a governance virtue rather than a governance failure
Italy Kingdom of Italy · 1861–1946
H:42 M:35 N:23 FOOTPRINT HM: The HM footprint reflects the north’s industrializing political economy more than the actual nationwide configuration — which is why Italy carries the highest Network score of any HM country in Lowell’s survey, reflecting the south’s persistent community and family governance traditions that the state hierarchy had formally subordinated but operationally never reached
Switzerland Federal Republic · 1848–present
H:22 M:18 N:60 FOOTPRINT N:The N:60 reading is the highest Network score in the entire survey — higher than any country Lowell visited and higher than the USA’s founding configuration of N:37. Direct democracy, cantonal autonomy, and civic participation as the primary coordination mechanism produce a governance architecture where authority flows upward from the community rather than downward from the center.
Lowell’s Six Countries
Abbott Lawrence Lowell’s principle was simple and radical in equal measure: the real mechanism of a government can be understood only by examining it in action.
The triad illustrates where countries can migrate within the scope of the H/M/N Triad. Governance footprints, once seen, often seem like common sense of where they should reside. Humans have a common sense for governance, or better said, a common sense for their governing logic. One would imagine that Lowell as a traveled governance practitioner recognized the proximity and migration of countries with this governance space.
The take-away is that governing logics are used to manage society by adopting a ratio of H/M/N coordinating logics of “how” to solve problems.
Two American configurations are included as reference points — not countries Lowell visited, but the governance context he was writing from and writing for. They show where the American governance trajectory stood at the moment of Lowell’s survey.
United States Founding Configuration · 1789
H:38 M:25 N:37 FOOTPRINT HN: Network logic nearly equal to Hierarchy, Market logic present but structurally subordinated to civic frameworks. The Bill of Rights as protection against Hierarchy excess. The extraordinary civic association density — the voluntary committees, town meetings, religious communities, and mutual aid networks — as the primary coordination mechanism for most of what the country needed done. On the triad, this configuration sits closer to Switzerland than to any country Lowell visited.
United States Gilded Age · 1889
H:40 M:45 N:15 FOOTPRINT HM:The founding Network logic had been in decline for two decades as the Gilded Age converted civic community life into industrial wage labor. Market logic — railroad trusts, industrial monopolies, robber baron capitalism — was approaching dominance. Network logic had dropped from N:37 at the founding to N:15 by the time Lowell was writing. The regulatory Hierarchy that would arrest this trajectory was still forty years away. The 1889 configuration has migrated away from the founding HN position toward England’s Victorian HM position — the country whose governance architecture, with its laissez-faire ideology and deliberately minimal state, most closely resembled where America was heading.
One Country Did It with Reason
The founding Americans were the exception to everything Lowell observed. They read Locke and Montesquieu. They studied the Haudenosaunee Great Law of Peace. They looked at every European governance failure around them and deliberately built something different — a Network-dominant architecture where civic association was the primary coordination mechanism, where the Bill of Rights was a protection against Hierarchy excess, where Market logic was present but structurally subordinated to civic frameworks.
Tocqueville, a French aristocrat, arrived in America fifty years later in 1831. He came from the country Lowell would later describe as the most administratively centralized state in western Europe, where the Napoleonic prefectural system meant that when something needed to be done collectively, you waited for the state to do it, or it didn’t get done.
What he found in America was the opposite of everything his European experience had prepared him for. When a road needed building in France, citizens petitioned the prefecture and waited. When a road needed building in an American township, ten men met on a Tuesday evening, formed a committee, assessed themselves a contribution, and had it built by spring. Tocqueville watched this pattern repeat across every domain he observed — fire response, schooling, political decision-making, care for the sick — and found himself unable to stop writing about it. Nothing in his experience had prepared him for voluntary coordination at continental scale without authority directing it.
“Americans of all ages, all conditions, and all dispositions constantly form associations. … I have often admired the extreme skill with which the inhabitants of the United States succeed in proposing a common object for the exertions of a great many men and in inducing them voluntarily to pursue it.” — Alexis de Tocqueville, Democracy in America, 1835
Ant Colonies, like Human Settlements, Adopt a variety of Governance Footprints
An ant or bee colony has no CEO.
No governance committee. No strategic plan. No one in charge of deciding when to forage, when to defend, when to abandon a failing nest and build a new one three hundred meters east. And yet — a colony of half a million individuals coordinates with a precision that embarrasses most Fortune 500 companies. It allocates labor dynamically. It manages existential risk. It adapts in real time to signals no individual ant fully understands. It has survived, largely unchanged, for 130 million years.
It governs instinctively via coordination logics that evolved to meet their societal needs. The coordination architecture is the organism.
Army Ants — H:80 M:12 N:8 · Footprint: H
Army ant colonies (100,000 to 700,000 individuals with no permanent nest) are the most hierarchy-dominant superorganism in nature. The queen’s reproductive monopoly is absolute. Caste differentiation is fixed from birth — soldiers, workers, and queens have no ability to renegotiate their role. Foraging raids operate as coordinated military sweeps, with pheromone trails functioning as command signals rather than market incentives.
Army Ants — H:80 M:12 N:8 · Footprint: H
Army ant colonies (100,000 to 700,000 individuals with no permanent nest) are the most hierarchy-dominant superorganism in nature. The queen’s reproductive monopoly is absolute. Caste differentiation is fixed from birth — soldiers, workers, and queens have no ability to renegotiate their role. Foraging raids operate as coordinated military sweeps, with pheromone trails functioning as command signals rather than market incentives.
Leafcutter Ants — H:50 M:35 N:15 · Footprint: HM
Leafcutter colonies (one to eight million individuals) are hierarchy-dominant colony running the most sophisticated internal market in the superorganism world. Rigid caste arcrmanent nest) are the most hierarchy-dominant superorganism in nature. The queen’s reproductive monopoly is absolute. Caste differentiation is fixed from birth — soldiers, workers, and queens have no ability to renegotiate their role. Foraging raids operate as coordinated military sweeps, with pheromone trails functioning as command signals rather than market incentives.
Weaver Ants — H:15 M:10 N:75 · Footprint: NH
Weaver ant colonies (100,000 to 500,000 individuals living across networks of trees) are the most network-dominant superorganism in the colonial insect world. Their territory — spanning multiple trees, managed through continuous pheromone communication and physical contact — is governed without permanent command authority. No individual ant knows the full structure. The colony’s collective intelligence emerges entirely from the network of relationships.
Honeybee Colony — H:50 M:10 N:40 · Footprint: HN
The honeybee colony (20,000 to 80,000 individuals in a single hive) is the most sophisticated governance architecture in the biological record. The queen provides clear reproductive hierarchy. But foraging decisions, resource allocation, and — most remarkably — nest relocation are governed through collective decision-making that functions as swarm democracy. Scout bees present alternatives through waggle dances. Other scouts evaluate and endorse. The colony reaches a quorum. The queen follows the swarm.
Fire Ants — H:45 M:45 N:10 · Footprint: HM
Fire ant colonies (100,000 to 500,000 individuals) represent the H-M hybrid configuration at its most aggressive. Hierarchical caste structure provides clear authority. But foraging and resource competition operate through market logic: colonies compete intensely for territory, recruit labor toward high-return foraging opportunities through competitive pheromone signaling, and eliminate competitors with coordinated force. Structured enough to coordinate at scale. Flexible enough to exploit any environment they enter.
Bumblebee Colony — H:20 M:20 N:60 · Footprint: NH
Bumblebee colonies are the governance counterpoint to army ants: minimal hierarchy, dynamic role negotiation, and coordination through relationship and reciprocity rather than command. Colony size is small — rarely more than a few hundred individuals — which means the governance architecture must be adaptive rather than rigid. Roles are not fixed at birth. Workers negotiate task assignment in real time through direct interaction. Network logic is the primary coordination mechanism.
Slave-maker Ants — H:55 M:40 N:5 · Footprint: HM ⚠
Slave-maker ant colonies (a few hundred to a few thousand individuals who do almost none of their own colony maintenance) raid other colonies — typically species with strong network-logic governance architectures — capture pupae before they have formed adult behavioral patterns, and raise those individuals within the slave-maker colony. The captured ants arrive with encoded instincts for cooperation, reciprocity, and network coordination — and those instincts fire in service of the slave-maker colony’s hierarchy-market logic. The slave-maker colony does not need to build its own foraging network, its own care-giving systems, or its own cooperative architecture. It captures the encoded instincts of other species and redirects them. The exploitation is architectural: it is the governance logic of one species running on the instincts of another.
Nature’s Superorganisms
Governance is not a human institution. It is a biological capacity — older than language, older than law, older than civilization itself. The evidence has been accumulating for 500 million years. We just haven’t been reading it as governance.
Superorganisms and Human Civilization Lessons
The Mirror Configurations
An interesting finding is how precisely some country-superorganism pairs align when plotted through the same triad.
1880s Germany (H:72 M:20 N:8) and the Army Ant (H:80 M:12 N:8) are effectively the same governance configuration. The N:8 reading is identical. Both run extreme hierarchy with Market logic subordinated to state direction and Network logic suppressed to near-zero. Both coordinate at massive scale through command and pheromone-equivalent signals — in Germany’s case, bureaucratic authority flowing through official chains. Both achieved extraordinary operational effectiveness. And both are brittle in the same way: Army ant colonies fail catastrophically when the queen is lost; Germany’s governance architecture collapsed in 1918 when the hierarchy lost its legitimacy. The biological parallel was not a metaphor. It was the same configuration running in two different media.
Switzerland (H:22 M:18 N:60) and the Bumblebee Colony (H:20 M:20 N:60) are almost identical — the ratios match to within a few points across all three logics. Both are small-scale, network-dominant, highly adaptive, with role negotiation happening through direct interaction rather than fixed caste assignment. The bumblebee colony is the smallest superorganism in the survey. Switzerland is the smallest major democracy in Lowell’s survey. This is not coincidence — it may reflect a structural constraint: Network-dominant governance requires relationship density that doesn’t scale easily. The biological world has not produced a Network-dominant superorganism at army ant scale.
Kingdom of Italy (H:42 M:35 N:23) aligns with the Leafcutter Ant (H:50 M:35 N:15) —. The Market score is identical. The Hierarchy score within eight points. The Network score accounts for most of the remaining gap, and the gap is analytically meaningful: Italy’s N:23 reading reflects the persistent southern community governance traditions that Rome’s constitutional hierarchy had formally subordinated but operationally never reached — the same communities where Elinor Ostrom later found the commons governance she was looking for. Both the leafcutter colony and the Kingdom of Italy run a Hierarchy-leading HM configuration: a structural H foundation that holds the architecture together, a real and functionally significant M mechanism allocating resources within it, and an N component present but subordinated — in the leafcutter, cooperative worker behavior that is caste-determined rather than voluntarily negotiated; in Italy, regional civic governance traditions that the national state formally claimed but never operationally displaced.
The USA 1789 founding configuration (H:38 M:25 N:37) maps closely onto the Honeybee Colony (H:50 M:10 N:40). The honeybee is the only superorganism in the survey that practices genuine collective decision-making: scout bees present alternatives through waggle dances, other scouts evaluate and endorse, the colony reaches a quorum, and the queen follows the swarm. The founding Americans were the only civilization in Lowell’s survey that chose their governance architecture deliberately through collective design. Both are HN hybrids. Both have hierarchy as structural backbone and Network logic governing the most consequential decisions. And both Tocqueville and entomologists independently identified their respective subjects as the most remarkable governance achievement they had ever observed.
The USA 1889 Gilded Age (H:40 M:45 N:15) matches the Fire Ant colony (H:45 M:45 N:10) with near precision. Fire ants are the most aggressive, competitive, and ecologically disruptive superorganism in the survey — notorious for displacing native species wherever they enter. The Gilded Age USA was in its most aggressive expansionist phase, displacing indigenous governance systems and competing for global resource dominance. The configuration is nearly identical. The behavioral signature is identical.
The Slave-maker Insight — The Most Significant Finding
This is the comparison the article should dwell on, because it reverses the intuitive assumption about which governance configurations are most vulnerable.
Slave-maker ants raid Network-dominant colonies specifically. The biological record contains no documented slave-maker raids on H-dominant army ant territories or M-dominant leafcutter colonies. The exploitation requires a target with strong cooperative, reciprocal, trust-based instincts — which is exactly what Network-dominant governance runs on. The slave-maker exploit only works against the colonies with the richest civic architecture.
Applied to the country survey: the governance configurations most vulnerable to slave-maker exploitation are Switzerland (N:60) and the USA founding configuration (N:37) — the two most admired governance architectures in Lowell’s entire survey. The configurations least vulnerable are Germany (H:72) and France (H:58) — the two most administratively oppressive. Cooperative instincts are the exploit surface. Hierarchy and Market logic, precisely because they don’t rely on trust, are structurally resistant to trust-exploitation.
This has an implication is countries are like superorganisms: the countries and institutions most committed to democratic, collaborative, civic governance are structurally the most vulnerable to actors who learn to present in Network logic while running a different logic underneath.
The question is not whether AI will develop governance instincts. The question is which instincts we accidentally trained into it — and whether those instincts are appropriate for the coordination contexts it will actually face.
Adopting a Governing Logic for AI
The founding Americans chose their governance architecture deliberately, but at our 250th anniversary we don’t even know we are choosing AI governance architecture. We are building the next coordination system — AI agent ecosystems — without any knowledge of our governance footprint, the trajectory we are on, or the destination we want. We are occupying the governance of the AI landscape the way the six countries, and the ants and bees did, through momentum, not intention.
In the next few years, humanity will release millions of AI agents into the world. Not tools. Not search engines. Agents — systems that will interact with each other, negotiate with markets, interface with governments, and make decisions that affect human lives at a scale no individual human can supervise.
We have been calling this “AI deployment.” It is the creation of the next multi-agent coordination system. And we are building it inside a governance environment we have not diagnosed. We default to whichever logic feels native under pressure. Leaders who trained in hierarchy reach for control when coordination fails. Consensus-builders reach for more dialogue when the situation demands a decision. Negotiators try to find deals in contexts that require trust, not trades.
We call this leadership style. We call it organizational culture. We call it personality.
It is governance illiteracy.
And here’s where it gets dangerous: we are building AI in our own image. Not intentionally. Not maliciously. But unavoidably — because the data we trained it on is saturated with human governance patterns, human coordination failures, human defaults and overrides and compensations. The models learned from us. They absorbed our instincts along with our and the developers’ knowledge.
The question is not whether AI will develop governance instincts. The question is which instincts we accidentally trained into it — and whether those instincts are appropriate for the coordination contexts it will actually face.
The wrong questions dominate the conversations. “We need more control.” Build guardrails. Establish oversight. Maintain human authority in the loop. This is the hierarchy reflex — the instinct that good outcomes flow downward from centralized authority. It’s not wrong. It’s incomplete.
“We need more collaboration.” Multi-stakeholder processes. Participatory governance. Democratic input into AI development. This is the network reflex — the instinct that legitimacy flows from relationship and consensus. Also not wrong. Also incomplete.
Neither position is asking the question evolution already answered:
Does the system know which governance logic the situation calls for — and can it shift?
Into this environment, we are releasing AI. We are about to do this at civilizational scale, with agents that operate faster than human oversight can follow.
AI Governance on the Triad
The governance triad — applied to AI governance, reveals a trajectory and potential paths.
Where We Are Now: Wicked Configuration
Stakeholders are dispersed across all three logics with no coherent governance institution. AI labs cluster at the Market vertex. Regulatory bodies attempt Hierarchy from a distance. Civil society and affected communities are largely excluded from any formal governance position. No actor has the authority, the legitimacy, or the multi-logic fluency to convene the full stakeholder field.
Where We Are Headed: Tragedy of the Commons
Without deliberate intervention, all actors collapse toward Market logic. Regulators are outpaced or co-opted. International bodies remain advisory with no enforcement capacity. Civil society is excluded by the speed of development. Governance architecture dissolves entirely as market coordination becomes the de facto logic for every domain AI touches. This is not a prediction. It is the extrapolation of the current trajectory without countervailing force.
Where We Need to Go: The Ostrom Configuration
Hierarchy-Network hybrid zone. Market logic present but structurally subordinated. All actors and a dedicated governance institution aligned within a coherent configuration. Regulators hold clear authority with adaptive rules. AI systems operate with governance-aligned architecture. Civil society and affected communities have formal standing. A governance institution provides standards, accountability, and boundaries that no single actor can currently provide.
Humans as a AI-governed Superorganism
The header was a Sci-Fi topic not even a decade ago, and now people are scrambling to figure out if they fit in, want to fit, or can fit in a world that is being overwhelmed by AI. Regardless, history and nature as telling us we need to become governance literate to optimize AI governance. The consequences to leaving it up to chance are large.
About GADGET
GADGET is a framework for diagnosing and designing governance across multi-stakeholder environments, developed by Tim Gieseke at AGRS LLC. The framework extends Elinor Ostrom’s commons governance research into a universal design grammar for coordination challenges — including the emerging challenge of AI agent governance. The H/M/N triad and governance literacy methodology operationalize the insight that governance misalignment — not complexity — is the root cause of most coordination failures. GADGET generated much of the analysis and the graphics.