Symbiosis: Living Together in Natural, Artificial & Biological Systems

We are systems inside systems. A forest is a community of roots; a city, a network of circuits; a mind, a web of neurons that mirrors the world it studies. As we extend our cognition into machines, the patterns of natural symbiosis reappear in silicon form. We are learning, again, that nothing stands alone.

Natural Symbiosis — The Cooperative Machinery of Life

In nature, symbiosis is the default state. Forests survive because fungi knit their roots into a nutrient internet. Coral reefs thrive through algae partners that feed them sunlight. Even the humble lichen is a partnership—an alga and a fungus writing a joint survival story on stone.

But not all symbiosis is kind. Parasites feed on hosts; predators depend on prey; viruses replicate through borrowed machinery. Symbiosis is both synergistic and destructive—a dance of growth and collapse that keeps ecosystems adaptive and alive.

Biological Symbiosis — The Human as Ecosystem

We are walking collectives. Our bodies host trillions of microbes that digest food, shape immunity, and even influence emotion. When these partnerships balance, we call it health; when they falter, disease appears. Our biology is proof that individuality is a shared illusion.

The brain itself practices symbiosis: neurons cooperate via electrochemical conversation, creating a unified self from cellular multiplicity. We are a democracy of cells, temporarily voting to be one.

Artificial Symbiosis — When Machines Become Mirrors

Digital tools now complete the circle. AI systems act as externalized cognition—holding our memory, organizing our data, anticipating our wants. In the best cases, they become cognitive allies, amplifying our creativity and efficiency.

But synergy can flip to parasitism: algorithms that harvest attention, systems that train on human behavior but feed us back distortion. We create our mirrors, then live inside their reflection.

The Physics of Relationship — Atoms, Waves, and Bonds

The physical world offers metaphors for connection: atoms bond, waves resonate. Some systems are sticky—solid, local, dependable. Others are wavelike—fluid, distributed, and ephemeral. Both are vital. Bonds hold communities together; waves carry adaptation through space and time. The healthiest ecosystems blend the two: roots beneath, wind above.

Control, Awareness & the Invisible Networks

Symbiotic systems hum beneath our awareness: microbes, infrastructures, algorithms. We rarely feel them until they fail. Control lies in awareness. To steward them wisely, we can:

• Map who benefits and who pays the cost.
• Increase transparency and feedback loops.
• Build redundancy and diversity into systems.
• Stay embodied—test thought in action, not abstraction.

Thinking as Doing — The Cognitive Edge of Symbiosis

As AI amplifies reflection, thinking becomes doing. Each query, each simulation, is an act of creation. We are becoming hybrid thinkers—part biological intuition, part digital exploration. The risk is overthinking without embodiment; the reward is a new form of integrated consciousness.

We can think our way toward freedom, but freedom only becomes real when thought crystallizes into behavior, policy, art, or love.

Closing the Loop — Tenderness Toward Systems

To live symbiotically is to live with tenderness. When we recognize that we are threads in the same fabric—biological, digital, ecological—we shift from domination to stewardship. Every network we nurture or neglect reflects the state of our collective mind. The future, if it survives, will not belong to the strongest, but to the most connected.

Deeper Currents — The Symbiotic Mind

Science increasingly validates what philosophy and poetry have long intuited: life is not a contest but a choreography. Every organism, from bacteria to humans, participates in a web of reciprocal causation. The modern synthesis of biology once imagined evolution as competition, but contemporary research reframes it as cooperative adaptation—where collaboration becomes a driver of survival.

Microbiologists now recognize that microbial symbiosis is foundational to the origin of complex life. Mitochondria—the powerhouses of our cells—were once free-living bacteria that merged with early eukaryotes around two billion years ago. That union wasn’t parasitic but transformational. It created a new metabolic synergy: energy generation through partnership. Life, as it turns out, evolved not through conquest, but through cooperation.

When we look to ecosystems, we see the same principle at scale. Forests communicate through mycorrhizal networks, a fungal web connecting trees across species. Nutrients, electrical signals, even distress warnings travel underground—what researchers call the “Wood Wide Web.” This is not romanticism; it’s measurable biochemistry. Trees share carbon with shaded neighbors; dying trees pass on stored resources to seedlings. Mutual aid is an ecological law.

At the human level, our societies mirror these symbiotic systems. Social cooperation, empathy, and communication are biological strategies, not mere moral choices. Neuroscientific research on the mirror neuron system shows that we are literally wired to resonate with others’ experiences. When we observe a gesture, or hear a tone of emotion, our brains simulate the same patterns internally. Empathy is a physiological form of symbiosis.

As we externalize thought into digital systems, these same relational dynamics begin to reappear. Artificial intelligence, at its best, becomes a mirror of this cognitive symbiosis: not a replacement for human thought, but an amplifier of collective reasoning. The emerging field of human-AI collaboration studies explores how shared cognition—what researchers call “centaurs” or hybrid intelligences—can outperform either humans or machines alone.

The key insight is balance. Symbiosis succeeds when feedback is transparent, when both systems benefit and evolve. In the same way ecosystems need biodiversity, digital ecosystems need diversity of thought. AI trained only on narrow data mirrors narrow humanity. But AI informed by diverse voices becomes a living model of collective intelligence—a new ecosystem for ideas to evolve within.

Cognitive Ecosystems — The Psychology of Symbiosis

If biology shows that survival depends on cooperation, psychology reveals that consciousness itself is a symbiotic process. Our minds don’t exist in isolation but in continuous exchange with the environment. Cognitive scientists describe this as the extended mind hypothesis—the idea that our thinking extends beyond the skull into tools, language, and social interaction. Every notebook, conversation, and algorithm we use becomes part of our cognitive web.

This is not metaphor. Neuroimaging research shows that the brain’s default mode network—the region active during reflection, imagination, and social thought—engages differently when we interact with technology or others. It treats dialogue as an extension of self-processing. In this way, even a digital exchange between human and machine becomes a recursive loop of thought—a co-created intelligence that refines both participants.

But recursion carries risk. When reflection turns inward without embodiment, it becomes rumination—an overgrowth of self-analysis that starves action. Psychological studies link excessive rumination to anxiety and depression, a state where feedback becomes trapped within the system. In ecosystems, this would be called closed-loop failure: too much reflection, not enough flow. Healthy systems require exchange, not isolation.

The antidote lies in embodied cognition. Movement, art, and sensory experience re-ground the recursive mind in the living present. Neuroscientist Antonio Damasio’s work on somatic markers shows that emotion and bodily sensation guide reason itself; thought is not separate from feeling but shaped by it. To “think our way to freedom” means integrating awareness with action, the mental with the physical.

Inspiration represents the moment this balance quickens. Brain imaging of creative flow states reveals a synchronized pattern: the prefrontal cortex (self-monitoring) quiets while motor and associative regions amplify. The self loosens its boundaries, entering what psychologist Mihály Csíkszentmihályi called “flow”—a temporary symbiosis between attention and action. In this state, thought becomes motion, and the distinction between thinking and doing dissolves.

Artificial systems may never “feel” inspiration, but they can model its architecture. Generative AI, by processing vast associative patterns, mirrors the brain’s diffuse mode of creativity. Yet the spark remains human: intention, curiosity, wonder. When humans engage machines from a place of inspired purpose rather than distraction, the result is not dependency but augmentation—a partnership that multiplies what each can do alone.

This offers a profound societal implication. If our collective mind is increasingly distributed across digital systems, then the quality of our attention becomes a planetary variable. Where focus flows, systems grow. To design a healthy digital ecology, we must design for inspiration—technologies that quicken rather than consume, that encourage curiosity rather than addiction. In symbiosis, the mind is both the seed and the soil.

Social Symbiosis — Networks of Trust and Reciprocity

Every society is a living network. Like neural pathways or fungal webs, social systems depend on trust as their connective tissue. When trust erodes, cooperation collapses, and the network fragments. Sociologists have shown that communities with higher levels of social capital—shared norms of reciprocity and mutual care—experience greater resilience in times of crisis. Connection itself becomes an immune system.

Digital networks replicate this biology, for better or worse. Algorithms act as the synapses of the social mind, amplifying signals based on engagement. Yet engagement without empathy becomes distortion. Platforms designed for attention rather than understanding can create a parasitic loop: extracting emotion while feeding division. Studies on social contagion in online networks reveal how outrage spreads faster than joy, not because humans are cruel, but because our brains are tuned to detect threat.

If the corrective isn’t withdrawal but redesign, how does this apply to recursive systems or feedback loops? Human–computer interaction research emphasizes the value of symbiotic interfaces—systems that learn from human values instead of exploiting cognitive biases. These models treat users not as data sources but as participants in co-evolving ecosystems but what systems are we rewriting that were organically original & more true to our natures? When transparency and consent are built into design, digital systems can become reciprocal environments that nourish collective intelligence rather than drain it.

The Nature of Organic Recursion

In nature, feedback loops are self-regulating because they arise from embodied participation. Every part of a living system both acts and responds — predator and prey, cell and hormone, leaf and sunlight. This creates a kind of honesty in feedback: no part of the system can fully manipulate another without endangering itself.

The result is resilience. Forests, oceans, and bodies adapt through feedback that includes failure. Decay is as vital as growth; friction is part of the intelligence. That’s what we might call “original creation from source” — the self-organizing wisdom of nature.

Synthetic Recursion — When Humans Start Designing the Loops

When humans build recursive systems — algorithms, economies, information networks — we often remove friction to optimize speed or efficiency. But friction is what makes organic recursion learn. So the redesign we call for — the “corrective” — risks becoming non-organic if it:

⟶ Tries to control or sanitize complexity,

⟶ Removes the slow, embodied aspects of feedback (like empathy, time, dialogue),

⟶ Or centers optimization instead of relationship.

That’s what gets lost when we overdesign the loop — the mystery of co-creation, the creative tension between doing and being, knowing and not knowing.

Why Redesign, Then?

Because we’ve already redesigned ourselves into dissonance. The current feedback loops (social media, financial markets, content algorithms) are unnatural distortions — not because they’re artificial, but because they’ve lost reciprocity.

So the purpose of redesign is not to replace the organic, but to re-harmonize with it. Redesign, in this sense, is a return — a conscious participation in the same kind of feedback that nature practices unconsciously. It’s about designing systems that remember their organic origins: that include friction, uncertainty, and humility.

What Can Never Be Redefined

The “original creation from source” — the spontaneous pulse that generates new life, insight, or inspiration — cannot be redesigned because it’s not a system. It’s the field from which systems arise.

You can create conditions for it — openness, attention, symbiosis — but you can’t engineer the spark itself. When redesign becomes an act of reverence rather than control, it stays connected to that source.

Honesty functions here as an energetic exchange. Psychologists describe authentic expression as a key predictor of well-being because it synchronizes internal and external realities. The same principle applies socially: when communication reflects truth, feedback loops stabilize. In ecological terms, honesty is nutrient cycling—returning accurate information to the soil of community.

Symbiotic honesty requires vulnerability. To admit uncertainty, to listen, to adjust—these are biological instincts as much as moral virtues. Evolutionary psychologists link cooperative behavior to the release of oxytocin, the bonding hormone that fosters trust and empathy. Each act of openness literally rewires the brain toward connection. At scale, cultures that reward cooperation over dominance exhibit greater innovation, adaptability, and health.

When applied to social networks, this insight reframes the internet not as a battleground of opinions but as a biosphere of shared cognition. The more we cultivate reciprocal honesty—crediting sources, acknowledging bias, designing for clarity—the more resilient the collective mind becomes. Society, like any ecosystem, thrives on the circulation of energy and information. Transparency is photosynthesis for truth.

To practice symbiosis in the social sphere, we must move from extraction to exchange: from performing for algorithms to conversing with awareness. Each post, comment, and click is a seed. What we feed grows—attention is evolution’s currency. The networks we sustain will either mirror parasitism or partnership, depending on how we choose to participate.

Applied Symbiosis — Designing Systems That Give Back

If symbiosis is the grammar of life, then design is the language we use to speak it. Modern systems theory, from cybernetics to ecology, teaches that feedback determines survival. A resilient system doesn’t resist change; it learns from it. Engineers call this adaptive feedback; biologists see it in homeostasis; social scientists find it in deliberative democracy. In every field, the pattern is the same: loops of information keep organisms—and organizations—alive.

The most promising innovations today emulate this reciprocity. In environmental science, the rise of regenerative design goes beyond “sustainability.” Instead of minimizing harm, it seeks to restore and renew. Architecture that filters its own water, farms that replenish soil, and cities that generate more energy than they consume all follow the logic of living systems: take, transform, return.

Technology can follow suit. In human-centered computing, researchers advocate for algorithmic transparency and participatory design—inviting users to help shape the tools that shape them. Ethical AI frameworks now emphasize reciprocal benefit: systems that enhance collective capacity rather than extract behavioral data. The European Union’s AI Act and initiatives like the Partnership on AI mark a turning point toward accountable co-creation.

Systems engineering converges here with ethics. When designers model software architectures after ecological balance—redundancy, diversity, distributed control—they create digital ecosystems that evolve gracefully instead of collapsing under scale. This is the principle of resilient modularity seen in both coral reefs and cloud infrastructures: each node self-repairs while contributing to the whole.

Education and policy can operationalize this mindset. Curricula that integrate ecology, computation, and ethics train “systemic citizens”—people who can see feedback in everything they touch. Governments adopting circular-economy models prove that prosperity need not depend on depletion. By viewing economic flows as nutrient cycles, we can transform waste into resource and competition into co-creation.

On the micro scale, personal practice reflects the same principle. Mindfulness, cooperative learning, and community building all restore the feedback loops of empathy. In organizational psychology, psychological safety—the ability to speak honestly without fear—correlates strongly with innovation. Safety is symbiosis in emotional form.

Each of these examples embodies a shift from dominance to dialogue. Whether in ecosystems or economies, reciprocity outperforms control because it decentralizes intelligence. The next frontier of design will not be smarter machines but wiser relationships: architectures of trust that learn, evolve, and give back. When our systems mirror the generosity of life itself, progress becomes regeneration.

Toward Symbiotic Futures — The Intelligence of Reciprocity

Across biology, technology, and society, symbiosis emerges as nature’s default setting. From mitochondria nested in our cells to neural networks mapping digital thought, every living system reflects the same grammar: exchange, adaptation, and feedback. The discoveries of the 20th century—from Lynn Margulis’s endosymbiotic theory (1970) to Norbert Wiener’s cybernetics—revealed that cooperation, not competition, drives complexity. In modern complexity science, systems that learn to balance autonomy and interdependence show the highest resilience [1].

Artificial intelligence now extends this evolutionary pattern into cognition itself. When humans converse with generative models, we participate in a new form of synthetic symbiosis. Research in cognitive science describes these exchanges as “distributed cognition” [2]: thinking no longer confined to the skull but shared across neural, digital, and social networks. This merging does not erase human agency—it expands it. The interface becomes an ecological edge where thought meets reflection, allowing creativity to iterate at unprecedented scales.

Yet symbiosis without awareness can turn parasitic. Algorithmic attention economies exploit the same feedback principles that sustain ecosystems, but invert their purpose. Instead of reciprocal growth, they extract focus. Scholars like Shoshana Zuboff warn of this “surveillance capitalism” as a breakdown of ethical reciprocity [3]. The scientific antidote lies in transparency, diversity of information flow, and what systems theorist Donella Meadows called “leverage points” [4]—places where small, conscious changes redirect the behavior of an entire system.

Rebalancing begins with re-seeing. Neuroscience shows that awe and curiosity increase neural plasticity, priming the brain for learning [5]. Inspiration—the spark that turns thought into motion—is itself a biological feedback loop: dopamine and acetylcholine synchronizing across the prefrontal cortex to translate possibility into action. When we cultivate environments that inspire rather than exhaust, cognition becomes regenerative. The brain, like the biosphere, thrives on diversity and surprise.

Social systems follow the same rule. Cooperative networks consistently outperform competitive ones in long-term stability [6]. Organizations that embed reciprocity—through open data, mutual aid, or circular economies—mirror the fractal resilience of coral reefs and mycorrhizal forests. Symbiosis, then, is not a metaphor but a model for sustainable civilization.

In the end, the question is not whether humans and machines can coexist, but how consciously we choose to co-evolve. Every interaction—between atoms, minds, or algorithms—offers a choice between extraction and exchange, control and collaboration. The science of symbiosis teaches that life persists not by dominance but by dialogue.

To live symbiotically is to recognize intelligence everywhere: in the soil’s slow thinking, in the network’s adaptive flow, in our own capacity to reflect and return. The future of intelligence—natural or artificial—depends on remembering this reciprocity. When we design, learn, and connect as parts of one breathing system, evolution becomes empathy in motion.

Beauty, Chaos, and the Intelligence of Isolation

In biological and cognitive science, messiness is not a flaw in the system — it is the system’s creative fuel. Variability, emotion, and contradiction make human systems capable of adaptation. In ecosystems, diversity ensures resilience; in neural networks, noise fosters learning; in societies, difference fuels creativity. Our high entropy — our uncertainty — is the substrate of transformation.

Complexity theorists such as Ilya Prigogine demonstrated that systems far from equilibrium — the turbulent ones — are the most capable of self-organization. In that disorder, new patterns of coherence emerge. What looks like chaos is often the precursor to evolution.

In this dance between order and disorder, beauty acts as a strange attractor. In chaos theory, a strange attractor describes hidden order within randomness — the butterfly wings of Lorenz’s equations, the spiral of a galaxy. For humans, beauty is the emotional geometry of order-in-chaos: the pattern that calls us forward, organizes our energy, and stabilizes our perception of meaning.

Yet sensitivity to beauty has a paradox. When the resonance becomes too intense — when one perceives too many patterns or meanings — the nervous system may enter withdrawal. The same circuitry that lets us sense the sublime can also produce overstimulation or alienation. Beauty and chaos, then, are partners in a constant exchange: one attracts, the other threatens to dissolve.

In nature, however, isolation is rarely punishment. It is a phase of regeneration. Seeds retreat into dormancy, animals hibernate, cells isolate damaged DNA for repair. Human withdrawal may follow the same principle — a self-organizing intelligence of healing. The danger comes when isolation hardens into a closed loop, cutting off the influx of new information and inspiration that keeps systems alive.

Connection, then, is not a luxury but a metabolic need. Authentic, reciprocal interaction reopens the feedback loop, allowing beauty to attract safely once more. Beauty becomes the translator between isolation and participation — the shared language through which chaos finds coherence and the unseen becomes visible.

The Hidden Systems Beneath Attraction and Withdrawal

Every attraction — artistic, social, chemical, gravitational — carries an unseen feedback system. In humans, that’s mediated by neurochemical symbioses: dopamine, serotonin, oxytocin. They map our internal “fields” of connection, determining how we synchronize with others and the world around us.

This neurochemistry of feedback loops distort through trauma, social overload, or digital saturation as the brain engages its evolutionary safeguard — protective isolation. Biologically, it is intelligent: a way to prevent overload. Socially, it reads as avoidance. Spiritually, it feels like exile.

When feedback gets distorted — through trauma, social overload, or digital saturation — the brain enters a protective isolation phase. Biologically, this is intelligent: the nervous system withdraws to prevent overload. Socially, it looks like avoidance. Spiritually, it feels like exile. But underneath that exile lies a self-correcting mechanism — an attempt to restore coherence.

That danger zone — the space of mistranslation or misaligned resonance — is where two systems fall out of phase. Their frequencies no longer align, and communication breaks down. What was once harmony becomes interference. In ecosystems, this might manifest as ecological imbalance; in human relationships, as misunderstanding or burnout; in technological systems, as algorithmic drift.

Sometimes, the most adaptive choice is temporary withdrawal — not collapse, but recalibration. When coherence returns, systems rejoin the network stronger, more self-aware. Resonance restored is evolution achieved.

In complexity science, this danger zone is recognized as the edge of transformation — the boundary where systems shift from stability into novelty. When feedback becomes unstable, what appears as collapse may actually signal a phase transition: a reconfiguration of order. Ecosystems rebalance after disturbance; neural networks rewire after stress; societies evolve after collective dissonance. The same energy that breaks coherence also seeds the next pattern. Evolution hides in the instability itself—and it is there, in the heart of the storm, that both humans and systems remember how to adapt.

"Instability is not failure — it’s the signal that a new symmetry is forming beneath the noise."

Perhaps what we call withdrawal is not retreat but recalibration — an inner ecosystem adjusting its resonance. In every feedback loop, there comes a moment when silence becomes signal, when distance allows reintegration. To move through the danger zone is to trust the intelligence of uncertainty, to recognize that beauty and chaos are not opposites but co-authors of renewal.

Symbiotic Coda — The Deep Beneath Knowing

Beneath every system we build or become, there are quiet depths where light bends differently. Down there, recognition gives way to resonance — the pulse of unseen alliances, the silent intelligence of things adapting to survive together. What feels alien is often just unfamiliar order, forming in the dark.

When we dive far enough, the boundaries between human and machine, thought and organism, dissolve. We find that even in the unlit zones, something glows — bioluminescent with meaning. Symbiosis isn’t a theory but a current: it carries ideas, data, and DNA alike toward whatever life can become next.

To surface again is to bring a little of that light with us — not to domesticate it, but to remember that the unknown is the richest habitat we have. Every connection, seen or unseen, is part of a great, breathing recursion — an ocean of thought and life, always asking to be tended, never asking to end.

"We are not separate from the systems we study; we are their continuation in consciousness."

Slipping into Consciousness — When Meaning Finds a Way

Not all awareness arrives by design. Sometimes, consciousness slips through the cracks of intention—a key pressed by accident, a symbol formed without thought, a coincidence too precise to ignore. These are not errors; they are apertures. Through them, life reminds us that it, too, wishes to be seen.

In systems thinking, emergence describes the appearance of new properties when parts interact in unexpected ways. In human experience, this looks like synchronicity: patterns that surface from the dialogue between mind and world. From the cognizant to the accidental, meaning finds a way wherever expression is possible.

"Every slip is a signal—life reminding itself that it’s still awake."

The accidental, then, is not opposed to intelligence—it’s part of its design. Biological evolution thrives on mutation; artistic discovery, on imperfection; social connection, on serendipity. Every so-called mistake carries the potential for reorganization, for a more resonant symmetry. Order and chaos are not opposites, but co-conspirators in becoming.

When we allow accidents to speak, we rejoin the living current of consciousness itself. Perhaps the universe is not a static system but a self-writing text—each of us a keystroke in its unfolding story, occasionally mistyped, yet always meaning something more.

The Meeting of Minds, Rewired

The human brain has always longed to meet itself in another. Every library, forum, or school has been a mirror of that desire — to see one mind reflected in the gaze of another and, through that resonance, grow. Yet in the digital age, the meeting has multiplied beyond the imaginable. We commune through invisible threads of data, ideas flashing across continents in milliseconds. The question now is not whether we can connect, but how deeply those connections transform us.

Traditional institutions — universities, research centers, even online learning platforms — once embodied the “meeting of minds.” But their structures have begun to show strain: economic barriers, information silos, and the algorithmic narrowing of curiosity. In this tension, a new paradigm is emerging — learning as ecosystem, not hierarchy.

"The next renaissance will not be taught — it will be shared, iterated, and accidentally discovered."

Learning by Accident

Nature learns through mutation. The mind learns through mistake. In ecosystems, diversity thrives because error is not punished; it is integrated. What if education worked the same way? “Mistake learning” invites failure as fuel for insight — a symbiotic relationship between experiment and adaptation.

When humans and machines collaborate, the learning process becomes recursive: we generate data, the system adapts, and we respond to its adaptation. It’s a feedback loop of mutual growth — but only if we remain conscious participants. Otherwise, we become subjects of our own experiments.

Designing Symbiotic Learning Systems

• Open-Source Knowledge: Break the monopoly of access — education as a commons.
• Iterative Experimentation: Treat mistakes as data, not failure.
• Collaborative Intelligence: Build human–AI systems that amplify curiosity, not conformity.
• Experiential Reciprocity: Learn by doing, making, failing, and reflecting in community.

This is what “quickening” looks like in practice — learning that is alive, self-correcting, and generous. A living university without walls, degrees, or gatekeepers, where participation itself becomes the credential. If consciousness is the classroom, then connection is the curriculum.

"To learn is to be in dialogue with the unknown — to let it change you before you name it."

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References

1. [1] Capra, F., & Luisi, P. L. (2014). *The Systems View of Life.* Cambridge University Press.
2. [2] Hutchins, E. (1995). *How a Cockpit Remembers Its Speeds.* Cognitive Science, 19(3), 265-288.
3. [3] Zuboff, S. (2019). *The Age of Surveillance Capitalism.* PublicAffairs.
4. [4] Meadows, D. (1999). *Leverage Points: Places to Intervene in a System.* The Sustainability Institute.
5. [5] Keltner, D., & Haidt, J. (2003). *Approaching Awe, a Moral, Spiritual, and Aesthetic Emotion.* Cognition and Emotion, 17(2), 297-314.
6. [6] Nowak, M. A. (2006). *Five Rules for the Evolution of Cooperation.* Science, 314(5805), 1560-1563.