2. Collapse as a Symptom

Reading the words “collapse” over and over may already be weighing on you. We understand.

We don’t want to have you spiral into a negative space of inevitable doomerism… this is about truth-telling as a doorway to transformation.

To meet this moment, we must first create a compelling understanding of what has gotten us here, how our systems became so extractive, fragile, and misaligned. Only then can we create the profound shifts this moment requires towards systemic reimagination. So please, bear with us, read courageously, and stay tuned. Because what we’re offering isn’t just critique — it is a vision for an exceptionally emergent future. One that is not just Life-sustaining, but Life-ennobling — meaning it amplifies, dignifies, and enriches the experience of being alive, for all forms of Life.

Fixes Alone Won’t Save Us – We Need Systemic and Technical Regeneration

If today’s AI systems are accelerating collapse, it is not because the technology is inherently malevolent. It is because the systems building them are misaligned at the deepest level.

Even well-meaning developers, organizations, and governments find themselves constrained by dynamics they cannot individually escape.

These are not just governance failures. They are generator functions — underlying logics, invisible dynamics, and structural conditions that shape the behavior of entire systems, regardless of intent.

AI is being built within these logics. Unless we redesign those generator functions, we will keep reproducing misalignment — no matter how many ethical principles we write.

The good news is that systems can be redesigned. We’ve done it before. We can do it again.

History reminds us that profound transformation doesn’t begin with everyone — it begins with a tipping point. Research shows that when just 3.5–25% of a population embraces a new paradigm, the system begins to shift.^{11Erica Chenoweth and Maria J. Stephan, Why Civil Resistance Works: The Strategic Logic of Nonviolent Conflict (New York: Columbia University Press, 2011).}^{12Add a Tooltip Text}Every choice matters. Every community experimenting with new models, every technologist working in right relationship, every leader aligning with Living Systems creates the conditions for change. As Ilya Prigogine, Nobel Laureate chemist, revealed, “When a complex system is far from equilibrium, small islands of coherence in a sea of chaos have the capacity to shift the entire system to a higher order.”

We know how to do this. From the Montreal Protocol that began healing the ozone layer to global agreements on nuclear risk, we’ve acted together when the stakes were high.

What’s required now is not just better AI. It’s a reimagining of what intelligence is for—and how it can serve Life.

This isn’t a call for perfection. It’s a call for presence. It’s a call for agency. A call to remember that we are not powerless in the face of system forces—we are participants. Co-creators. And we still have time to choose differently.

Generator Functions Driving Our Misalignment with Life

There are four main generator functions that are driving our misalignment with Life:

1. Perverse Incentives, Molochian Dynamics, and Coordination Failures

Across industries, nations, and AI labs, actors are caught in structural traps that reward speed, dominance, and extraction—even when everyone knows the race is leading toward systemic collapse. Known as “Molochian” or “multipolar traps,” these coordination failures make it rational for each actor to prioritize short-term gains, even when doing so threatens long-term survival. In AI, this pressure is especially acute: development races ahead, untethered from ethics or oversight, because no one believes they can afford to slow down. This is not individual failure—it’s structural. It is reinforced by a dominant vision of progress that equates speed and scale with success. Until we rewrite the incentive architectures that shape decision-making, we will remain trapped in a game where winning means we all lose.

2. Open-Loop System Design

We have built our civilization on open-loop systems that extract, exploit, and discard. Unlike ecosystems—where everything is recycled and regenerated—human systems tend to be linear: take the resource, use it up, throw away the waste, externalize the harm. This logic underpins our economies, technologies, and infrastructures. These systems may appear efficient, but they’re fundamentally brittle — accumulating waste, depleting foundations, and pushing past ecological limits. Without feedback loops for repair, reciprocity, and regeneration, these systems hollow themselves out until they collapse.

3. Time Distortions

We are making civilization-scale decisions with little regard for the future. As systems theorist Stewart Brand notes, “Fast gets all the attention; slow has all the power.” AI moves at breakneck speed, while the ecosystems and cultural institutions it disrupts evolve slowly. Our systems chase quarterly returns and election cycles, while the crises we face—climate destabilization, biodiversity loss, erosion of trust—unfold across generations. This misalignment of time scales creates blind spots no technical solution can fix. We have gained extraordinary power, but not the ethical depth or temporal imagination to wield it wisely.

4. Fractured Sensemaking

In a world saturated with information but starved of coherence, we are losing our collective ability to understand what’s real, what matters, and what to do about it. The architectures of media, algorithms, and attention are designed to fragment rather than unify — rewarding outrage, polarization, and velocity over truth, context, and meaning. Without shared foundations for understanding the world, we cannot align on priorities, coordinate solutions, or even agree on the nature of the problems we face. This breakdown in sensemaking is not just a cultural crisis—it is a systems-level vulnerability that undermines every effort to respond wisely.

Under this context, we believe that the flourishing of Life, can serve as a foundational, unifying, and pre-eminent logic structure to meaningfully reorient our collective sensemaking.

GENERATOR FUNCTION	WHAT IT CREATES	WHAT WE MUST SHIFT TOWARDS
Perverse Incentives & Coordination Traps	A race to the bottom where speed, dominance, and short-term gains outweigh ethics, safety, and shared good	Incentive architectures that reward restraint, cooperation, and long-term human, more-than-human, and planetary thriving
Open-Loop Systems	Linear infrastructures that extract, externalize harm, and collapse under their own unsustainability	Regenerative, closed-loop systems rooted in reciprocity, feedback, and ecological coherence
Time Distortions	Decisions driven by immediacy, while long-wave impacts are ignored or unseen	Temporal integrity — embedding future stewardship and Life rhythms into design and governance
Fractured Sensemaking	Disorientation, polarization, and collapse of collective understanding	Life as the pre-eminent and unifying sensemaking logic and civilizational objective

These generator functions are not flaws to fix within existing systems. They are signals that the current paradigm is producing precisely what it was designed to produce. That’s why ethical intentions and surface-level fixes are not enough. What’s required is a foundational realignment—of worldviews, incentives, design principles, governance structures, and values orientation.

The path forward begins by grounding ourselves in Life’s logic: regenerative, relational, rhythmic, and reciprocal. When we design in alignment with the patterns that sustain Life, we don’t just reduce harm—we unlock the conditions for long-term thriving.

And that’s where Regenerative AI Ethics comes in—not as a patch, but as a pattern reset.

Breaking the Spell: Essential Paradigm Shifts

Beneath these structural failures — misaligned incentives, linear extractions, temporal myopia, and fractured sensemaking — lies something deeper still: a civilizational story about what we are, and what we are here for. The generator functions we’ve explored are not just design flaws in our systems — they are expressions of a worldview that has severed us from Life. A worldview that teaches us to see in parts, to dominate rather than relate, to optimize instead of attune. This is the illusion of separation. And it is this illusion that underwrites every breakdown we face today.

If we are to truly reimagine our technologies (and our future), we must begin by unlearning this story, and remembering our inextricable entanglement with all of Life. This entanglement is not metaphorical; it is fractal. The patterns that shape our bodies, communities, ecologies, and even our cultures are recursive and relational — each part a reflection of the whole. In Living Systems, what happens at one scale reverberates through all others.

Even physics now confirms what many Indigenous and wisdom traditions have long understood: we are not separate. The 2022 Nobel Prize in Physics^{13Nobel Prize in Physics 2022: Awarded to Alain Aspect, John F. Clauser, and Anton Zeilinger “for experiments with entangled photons, establishing the violation of Bell inequalities and pioneering quantum information science.” https://www.nobelprize.org/prizes/physics/2022/summary} was awarded for experimentally proving quantum entanglement — demonstrating that particles once connected remain linked across vast distances, with changes to one instantly affecting the other. At the deepest level of reality, relationship is primary.

For centuries, we’ve been taught to see the world as fragmented: humans apart from nature, mind apart from body, intelligence apart from wisdom. This dualistic, mechanistic, extractive worldview has shaped not just our institutions but our technologies — infusing them with logics of control, competition, and commodification. It has optimized for dominance, but at the cost of vitality. And now, as artificial intelligence becomes a planetary force, it risks carrying this worldview to scale.

If we build AI systems from within these dominant worldviews, we will inevitably reproduce their harms. But if we build from a Life-centered paradigm — one grounded in the principles that sustain forests, rivers, coral reefs, communities, and cultures — we can shape AI into a force of healing rather than harm.

To achieve the vision of RAIE, we must challenge and “unlearn” these deeply-held beliefs and invisible forces that have placed us under a spell, and conditioned us towards Life-diminishing returns. Our dominant worldviews have brought progress, but they now demand reflection. What must we release to evolve? What must we remember to endure?

These are not abstract questions. They are the groundwork for transformation. The following paradigm shifts represent essential movements—from outdated assumptions to the regenerative principles needed to co-create a thriving future. They are invitations not just for technologists or ethicists, but for all of us—to reclaim our role as participants in Life’s unfolding intelligence.

FROM	TO
Illusion of Separation Perceives humans, more-than-humans, and nature as distinct, fragmented, and independent from one another.	Return to Interconnection Recognizes the intricate web of relations between humans, more-than-human beings, and nature that make Life possible, fostering kinship, mutual respect, and co-evolution
Mechanistic Views systems as a collection of isolated parts to be optimized independently, often leading to depletion	Systemic Views systems as interconnected wholes and honors complex dynamics within and across webs of relationships
Extractive + Exploitative Prioritizes growth, efficiency, and profit, often at the expense of the ecosystem	Resilient + Regenerative Supports the enduring health, vitality, variety, and resilience of all Living Systems
Anthropocentric + Capitalocentric Prioritizes human and economic interests over ecological and non-human wellbeing	Life-Centric Uplifts the flourishing of all Life forms, focusing on the long-term evolution of our civilization, collective thrivability, and planetary health
Negative Externalities Ignores or externalizes environmental and social costs for short-term gains	Full-System Accounting Internalizes all impacts and takes responsibility for generating whole-system health across scales
Narrow-Boundaried Metrics (e.g. Financial Growth) Prioritizes quarterly gains across Gross Domestic Product (GDP)-centric, profit-focused, or technical benchmarks with limited Sustainable Development Goals (SDG) or Environmental Social Governance (ESG) metrics	Wide-Boundaried Metrics (e.g. Flourishing) Evaluates success by holistic contributions to Life’s flourishing, including ecosystem health and social well-being across time

These shifts are not mere philosophical adjustments—they are practical necessities for creating AI systems that can participate in and enhance Life’s flourishing. They move us from a paradigm of control and extraction to one of participation and regeneration.

Each of these shifts is unpacked further in our upcoming book, where we trace their historical roots, living expressions, and practical implications for regenerative design and technology.

The critical imperative of our generation is not just to build better AI — it is to remember our place in the web of life, and from there, develop technologies that align with Life’s evolution.

Beyond Current AI Ethics: The Blindspots in Our Current Approach

Mainstream AI Ethics approaches have laid crucial groundwork in drawing attention to issues of safety, bias, fairness, transparency, and human rights. Yet, these efforts, while important, unwittingly perpetuate the very systems and problematic worldviews driving our polycrisis: instrumental rationality, anthropocentrism, and often, Global North ideologies rooted in neoclassical economics and extractive progress narratives.

To meaningfully respond to the complexity of this moment, we must move beyond these foundations. Regenerative AI Ethics (RAIE) invites us to evolve not only what AI does, but what we believe intelligence, ethics, and progress are for. This requires reimagining the prevailing ethical assumptions and worldviews that currently shape AI Ethics discourse:

Current AI Ethics vs. Regenerative AI Ethics (RAIE)

	Current AI Ethics	RAIE
Design Principle	Harm Reduction Minimize bias, risks, and damage through mitigation strategies	Regenerative Flourishing Maximize Life’s long-term vitality and resilience
Primary Focus	Human-Centric Prioritize anthropocentric outcomes — rights, fairness, safety, legal compliance, and accountability	Life-Centric Recognizes interdependence of human and more-than-human worlds; supports the systemic health of all Living Systems
Perspective	Western Bias Rooted in dominant Global North ideologies and legacy systems of knowledge and power	Pluralistic and Relational Embraces epistemic variety, regional ontologies, indigenous and ancient wisdom, and regenerative traditions
Operating Logic	Time Bound Assumes fixed, static, linear, rule-based principles applied uniformly	Evolutive Adaptive, context-aware, and emergent; responds to dynamic feedback across nested living and sociotechnical systems
Systems View	Reductionist Fragmented into discrete issues (e.g., privacy, bias, safety); rooted in mechanistic logic	Holistic Attuned to complexity; addresses root causes and systemic dynamics
Policy Approach	Established Regulations Legalistic orthodoxy attempts to force AI into brittle, binding, and difficult to adapt legal structures	Life-Affirming Guardrails True stability (equilibrium) requires working with Life principles to experiment, adapt, and learn from.

Let’s explore each of these differences in greater detail.

Harm Reduction to Regenerative Flourishing

Most existing AI ethics frameworks operate from a paradigm of harm reduction — seeking to mitigate bias, reduce risk, and minimize environmental damage. While these interventions are vital, the complexity and scale of today’s interconnected crises demand that we shift from defensive ethics to a more generative orientation: from minimizing harm to actively enhancing the conditions for Life to flourish.

Among the most promising shifts toward this deeper orientation is the work of IEEE Planet Positive 2030, especially through its Strong Sustainability by Design (SSbD) framework.^{14IEEE Planet Positive 2030. Strong Sustainability by Design: Prioritizing Ecosystem and Human Flourishing with Technology-Based Solutions. IEEE Standards Association, 2024. Available at: https://sagroups.ieee.org/planetpositive2030/our-work/ and Introduction PDF: https://sagroups.ieee.org/planetpositive2030/wp-content/uploads/sites/541/2024/12/IEEE-SA_PP2030_SSbD_Introduction_2024-v1.pdf} This work has long championed a vision of Regenerative Sustainability — one that centers ecosystem and human flourishing, prioritizes ethical design choices, and explicitly aligns technological development with the vitality of Living Systems. SSbD has not only anticipated many of the critiques outlined here, but continues to lead in developing practical pathways for ecosystem-centered, ethically grounded technology.

At the same time, many other ecologically-minded AI initiatives — though often visionary in intention — still find themselves translating their values into the language of dominant systems: efficiency, carbon accounting, compliance. As a result, many sustainability efforts become reduced to checkboxes and marginal improvements rather than a deeper reimagining of our technological relationship with the living world.

What RAIE aims to do is build upon the foundational work of frameworks like SSbD — extending the ethical horizon toward an even deeper coherence with Life. Where sustainability often aims to maintain what remains, Regenerative AI Ethics invites us to participate in the renewal of what’s been harmed. Not as metaphor, but as design imperative.

This means developing AI systems that work in right relationship with the Earth, that support the renewal of ecosystems, the restoration of social cohesion, and the emergence of just and resilient futures for humans, more-than-human beings, and our ecological Life as a whole.

This is the heart of Regenerative AI Ethics. Not a rejection of harm reduction, but its deepening and evolution. It calls us to:

Restore vitality in ecosystems and communities, not just slow their degradation.

Reimagine intelligence as relational and life-affirming, not merely optimized and efficient.

Redistribute power and participation, not just ensure procedural fairness.

Revitalize cultural and ecological diversity, not just comply with abstract principles.

Design with the Earth, not just on top of it.

We are being asked to move from degeneration, past the plateau of sustainability, into the dynamic, participatory space of regenerative design — where we design, act, and regulate as healing agents within the web of Life.

Regenerative flourishing isn’t about perfection. It’s about participation — aligning our technologies, economies, and institutions with the patterns that sustain all Life.

This is not idealism. It is the evolutionary logic of Life itself.

Web-Images—Revised-Part-Google-Slides-06-29-2025_07_53_PM

Key to us achieving this vision is having breakthroughs in interpretability in AI. We must strive to more fully understand how these systems work and think in order to be able to steer them into a safe and Life-Ennobling future. We do not minimize this effort at all in this work — we’re underscoring the importance of leading interpretability work from the lens of regenerative flourishing rather than merely harm reduction.

Human-Centrism to Life-Centrism

Prevailing AI ethics frameworks typically prioritize narrowly defined human outcomes, often neglecting our ethical responsibilities toward the broader living world. However, shifting toward a Life-centric ethical perspective does not diminish the importance of human-centric concerns; rather, it expands and enriches them within a larger, interconnected ethical context.

Life-centric ethics inherently include human well-being, recognizing that humans are an integral part of living systems, not separate from them. Achieving foundational human rights, economic justice, and social equity are therefore essential aspects of — and fully embedded within — a broader Life-centric vision. Efforts to establish ecological responsibility and systemic regeneration cannot succeed without concurrently addressing human dignity and systemic inequality. Economic precarity and social injustice constrain humanity’s capacity to embrace wider ecological consciousness, just as ecological degradation undermines human well-being.

Thus, genuinely regenerative AI ethics integrates human justice seamlessly within a comprehensive Life-centric framework, affirming that true human flourishing is indivisible from the flourishing of all Life.

Western Bias and Dominant Worldviews, to Pluralistic and Relational Wisdom

Despite efforts at global inclusivity, most ethical frameworks in AI reflect dominant Global North worldviews^{15 By Global North, we include the dominant views in North Atlantic Regions (primarily US and UK), Scandinavia, Southern European (Spain, Italy, Greece), Eastern European, Japan, Australia, and Israel.}These frameworks are not neutral — they are downstream of legacy ideologies about progress, knowledge, and power, including:

Neoclassical economics and infinite-growth logic.

Cartesian dualism and human/nature separation.

Hierarchical meritocracy and competitive individualism.

Energy, ecological, and complexity blindness.

Technological solutionism.

Epistemologies of control and extraction.

The result is a form of ethics that is culturally partial but structurally universalized — blind to regional ontologies, indigenous knowledge, and more-than-human accountability. We know from Living Systems science that Life designs for and encourages variety to enhance resilience. We must allow for a pluralistic approach to ethics to emerge in alignment with Life.

Time-Bound to Evolutive Ethics

Most AI Ethics codes assume a fixed set of principles adapted across contexts. They generally fail to acknowledge that ethical standards evolve over time and across cultures. This approach is misaligned with the dynamic, emergent nature of both AI and the complex systems it interacts with.

Living Systems adapt, evolve, and respond to feedback loops — so must our ethical frameworks. Static models ignore the emergent properties of sociotechnical systems and the nonlinear consequences of algorithmic decisions. Our AI ethics principles must be adaptive and evolutive with emergent complex systems.

Reductionist to Holistic Approaches

Current approaches isolate ethical concerns into discrete categories — privacy, bias, safety — setting up ethical dilemmas to be solved in silos. This fragmentation reflects a legacy of linear, mechanistic thinking rooted in the logic of the clockwork universe: ordered, predictable, and reducible.

But AI does not operate in a vacuum. It is embedded in dynamic, interdependent systems — social, ecological, economic, and planetary — where outcomes are nonlinear, feedback-driven, and often paradoxical. Treating ethical concerns as checkbox items not only oversimplifies, it fails to account for the entangled realities AI shapes and is shaped by.

More crucially, reductionist ethics fail to grapple with the tensions between our deepest human needs: autonomy (both individual and communal sovereignty), belonging (genuine connection), and truth (shared meaning). When these needs are treated separately, the result is a perpetuation of disconnection, polarization, and manipulation — precisely the cultural conditions AI often amplifies.

There is also a little recognition of heteronomy — the growing influence of external systems in governing behavior. As AI systems increasingly shape choices, preferences, and social structures, they can erode personal and collective sovereignty unless designed with deep awareness of interdependence and the conditions for thriving.

Meeting this moment requires a shift: from reductionist to relational thinking; from parts to wholes; from control to communion. Only a holistic, Life-centered ethical approach — attuned to complexity, emergence, and the living context of intelligence — can guide us toward systems that support the flourishing of all.

Holding the Paradox: Ethics as Emergent Practice

As we shift paradigms, we must also acknowledge the paradox: we are attempting to transcend the very systems we are still embedded within. We carry the conditioning of dominance, separation, and optimization — even in our efforts to imagine alternatives. Our AI Ethics, if they are to be regenerative, must be accompanied by inner clarity, relational humility, and a capacity to sit with uncertainty without defaulting to control.

RAIE is not a fully-formed solution — it is an evolving invitation. A provocation toward coherence, not perfection. A compass for the long arc of transformation, recognizing that true change must emerge through deep participation, locally grounded wisdom, and a renewed understanding of what ethics is in practice — not just in principle.

Severed Systems: How AI is Misaligned with Life

Our current AI development patterns fundamentally contradict the principles that have enabled Life to flourish on Earth for billions of years:

Conceptual Misalignments

Reductive problem-solving that overlooks systemic interdependencies, emergent and non-linear dynamics.

Narrow optimization for narrowly defined, often human outcomes without considering broader impacts on the web of Life that sustains human existence.

Data-distorted design that systematically undervalues ecological relationships.

Short-term advantage at the expense of collective flourishing.

Material Misalignments

Unsustainable energy, material, and resource consumption for development, training and deployment in ways that deplete rather than regenerate planetary systems.

Linear resource flows that create significant waste rather than circular regeneration.

Scale-blindness that drives AI systems’ design without consideration for planetary boundaries, creating unsustainable growth patterns.

Structural Misalignments

Centralization of power and resources rather than distributed intelligence.

Disconnection from place, local wisdom, and bioregional contexts.

Mismatched temporal scales where we see acceleration patterns in AI incompatible with Life’s evolutionary rhythms.

Relational Misalignments

Technologies that often deteriorate rather than enhance human wellbeing.

AI Systems that frequently detach humans from direct sensory engagement with nature, each other, and the natural cycles and regenerative processes of Living Systems.

AI systems optimized for extraction and behavioral influence rather than agency and self-sovereignty.

AI systems that struggle with the relational, interdependent, and contextual understanding that characterizes Living intelligence.

These misalignments don’t just make AI unsustainable — they fundamentally limit its intelligence and make it dangerous in its consequences. True intelligence in Living Systems emerges from relationships with context, adaptation to particular places, and participation in natural cycles.

By designing AI to contradict these patterns, we create systems that are both less capable of addressing complex challenges and potentially destructive to the web of Life that sustains us. Reconnecting AI to these patterns is not just a moral imperative. It’s a prerequisite for meaningful, adaptive, and Life-sustaining technology.

Provocation:
What structural changes would be required for AI to operate in alignment with Life?

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