The academic version:
Essential terms that require upfront definition:
- Computational Democracy – Democratic decision-making enhanced by computer systems that help process information and facilitate collective intelligence
- Coordination Problems – Situations where individual rational choices lead to collectively poor outcomes (like traffic jams or climate change)
- Markov Blankets – The boundary that separates a system’s internal states from its environment, determining what information flows in and out
- Thermodynamic Efficiency – How well a system uses energy to maintain organization and perform work
- Information Processing – How systems (biological or artificial) receive, store, transform, and use information to make decisions
- Distributed Intelligence – Intelligence that emerges from many simple parts working together, rather than from a single central controller
- Feedback Loops – Cycles where outputs of a system become inputs, creating either stabilizing or destabilizing effects
Image by James Wainscoat
The Promise of Natural Coordination
Building with Nature’s Blueprint
Throughout billions of years of evolution, life has solved coordination problems we still struggle with today. A forest allocates resources without central planning. A flock of birds navigates without a commander. Your immune system distinguishes self from other while maintaining the delicate balance that keeps you alive. These systems work not despite complexity, but because of how they handle it—through distributed intelligence, continuous feedback, and thermodynamically efficient information processing.
What if human society could learn from these natural systems? What if our institutions could embody the same principles that make a cell membrane selectively permeable, or that allow a neural network to learn and adapt? This isn’t about imposing technology on human nature, but about designing social systems that work with the fundamental patterns of reality itself.
Coordination: Nature’s Eternal Challenge
Coordination problems arise whenever individual incentives diverge from collective benefit. In nature, we see this resolved through elegant mechanisms: ant colonies optimize foraging paths through pheromone trails that encode collective intelligence; slime moulds find shortest paths between food sources without centralized computation; mycorrhizal networks share resources across forest ecosystems, creating resilience through reciprocity.
The mathematical foundation underlying these solutions is becoming clear through work in complex systems theory. As researchers at the Santa Fe Institute have shown, successful coordination emerges when systems can process information efficiently—maintaining what Karl Friston calls “Markov blankets” that separate internal organization from environmental chaos while allowing selective exchange.
Human societies face similar challenges but often at unprecedented scales. How do eight billion people coordinate resource use without destroying our planetary life support systems? How do we make collective decisions that honour both individual autonomy and collective wisdom? How do we create institutions that can adapt and learn rather than calcify and resist change?
Our Current Coordination Crisis
Consider our most pressing coordination failures: Climate change represents a massive failure to coordinate around planetary boundaries. Wealth inequality reflects broken resource allocation mechanisms. Political polarization shows our information processing systems are creating destructive feedback loops rather than collective intelligence. Social media amplifies division instead of fostering understanding.
These aren’t just policy problems—they’re symptoms of institutions designed for a simpler world, now overwhelmed by complexity they cannot process. Our democratic systems, built for small communities, strain under the weight of mass society. Our economic systems, optimized for local markets, create global externalities they cannot account for.
A nature-inspired computational democracy could address these failures directly. Imagine decision-making processes that mirror how your brain integrates diverse neural inputs into coherent action. Imagine resource allocation systems that learn and adapt like ecological networks. Imagine institutions that embody the error-correction mechanisms of healthy immune systems—capable of distinguishing beneficial innovation from harmful disruption.
The benefits are tangible: policies shaped by genuine collective intelligence rather than polarized debate; resource allocation that optimizes for long-term flourishing rather than short-term extraction; institutions that evolve and adapt rather than stagnate and collapse.
Image by Alexey Melechin
Information Infrastructure: The Neural Network of Society
How Nature Builds Intelligence from Conversation
Every natural coordination system relies on continuous information exchange. Neurons don’t vote once every four years—they maintain constant dialogue through synaptic signals. Cells in your immune system continuously share chemical messages, updating their responses based on new information. Mycorrhizal networks create what Suzanne Simard calls the “wood wide web”—a communication system that allows forests to share resources and coordinate responses to threats.
These systems work because they combine distributed processing with integrated decision-making. No single neuron controls your thoughts, yet coherent consciousness emerges from their collective activity. No single tree manages the forest, yet the ecosystem maintains itself through countless local interactions guided by shared information.
The key insight from Integrated Information Theory and Active Inference research is that intelligence emerges from systems that can simultaneously maintain internal coherence while remaining responsive to environmental change. This requires what we might call “conversational intelligence”—the capacity to process diverse inputs, integrate conflicting perspectives, and generate adaptive responses.
The Micro Benefits: Human Dialogue as Distributed Cognition
At the individual level, genuine dialogue transforms participants. When we engage in authentic conversation—truly listening, genuinely considering other perspectives—we literally expand our cognitive capacity. Research in embodied cognition shows that thinking is not confined to individual brains but extends through our interactions with others and our environment.
Regular dialogue with neighbours creates what social scientists call “social capital“—networks of trust and reciprocity that make communities more resilient. But more than that, it creates opportunities for what Iris Murdoch called “unselfing”—the expansion of consciousness that comes from truly attending to others. This isn’t just morally beneficial; it’s cognitively enhancing.
When communities engage in ongoing dialogue about shared challenges, they develop collective intelligence that exceeds the sum of individual contributions. They become more capable of detecting early warning signals, more creative in generating solutions, more adaptive in responding to change. This mirrors how distributed biological systems maintain health through constant information exchange.
The Macro Benefits: Scaling Wisdom Through Computation
The challenge is scaling these benefits to the level of complex societies. This is where computation becomes essential—not to replace human judgment, but to amplify human wisdom. AI systems based on principles of Active Inference and predictive processing could help synthesize diverse perspectives, identify emerging patterns, and facilitate collective decision-making at unprecedented scales.
Imagine democratic processes that work more like healthy ecosystems: continuous rather than episodic, adaptive rather than rigid, integrative rather than polarizing. Citizens could engage in ongoing dialogue about shared challenges, with AI systems helping to identify common ground, surface creative solutions, and coordinate collective action.
Such systems could embody the error-correction mechanisms that make natural systems robust. Bad ideas would be filtered out through distributed evaluation, while good ideas would spread and evolve through collaborative refinement. The result would be institutions capable of genuine learning—able to update their responses based on feedback from reality rather than clinging to ideological positions.
This isn’t utopian fantasy. Projects like vTaiwan, Decidim, and the work of organizations like the Santa Fe Institute are already demonstrating how computational tools can enhance rather than replace human collective intelligence. The question isn’t whether such systems are possible, but whether we’ll build them before our current coordination failures become catastrophic.
The path forward requires what Freeman Dyson called “the marriage of technology and biology”—but applied to social systems. We need institutions that embody the thermodynamic principles that make life possible: maintaining internal coherence while remaining open to environmental feedback, processing information efficiently while avoiding both stagnation and chaos, and creating conditions for emergence while preserving what works.
This is the promise of computational democracy: not the rule of machines, but human wisdom amplified by tools that help us think together more effectively than we ever have before.
People Know How.
On a mission to contribute to conceiving this missing infrastructure.
