Below is a polished, publication-ready follow-on Substack essay that builds directly on your original Developing Planetary Intelligence post. It incorporates all the themes discussed—ecological costs, Indigenous knowledge governance, relational accountability, AI epistemic limits, and the deeper ethical dilemmas of planetary intelligence—without referencing any specific individuals.
I also provide three alternative title options that may better capture the depth and nuance of the piece.
Title Options
- Addressing the Hard Questions: AI, Ethics, and the Path to Planetary Intelligence
- The Shadows of Planetary Intelligence: Ecological, Ethical, and Epistemic Challenges for AI
- Before We Build Planetary Intelligence: What Must We Confront?
(The draft below uses your working title, but I can easily swap to one of these.)
Addressing Important AI Concerns
A follow-on to “Developing Planetary Intelligence”
In my earlier reflection on “developing planetary intelligence,” I explored the possibility that artificial intelligence—properly guided—might play a decisive role in helping humanity transition from ecological overshoot to a mutually enhancing relationship with the Earth. That vision, however compelling, is incomplete without addressing several profound concerns. These concerns arise from ethics, from ecology, from history, and from the limitations of current AI systems themselves.
We cannot speak credibly about planetary intelligence without first confronting these dilemmas directly. They are not side notes. They are central to the work.
What follows is an attempt to surface and clarify the major questions that we must hold—carefully, humbly, and honestly—if AI is to become a partner in a regenerative and life-supporting future.
1. The Ecological Costs of AI
It is no secret that today’s advanced AI models consume significant quantities of electricity and water, with associated greenhouse gas emissions and local environmental impacts. Critics rightly point out that a tool meant to support planetary health must not undermine that very goal through its own operations.
The key point is this:
The ecological cost of AI is not inherent; it is a design and governance challenge.
We already possess, or are rapidly developing, the means to reduce AI’s footprint dramatically:
- renewable-powered data centers,
- highly efficient model architectures,
- energy-aware compute allocation,
- distributed and edge inference,
- hardware optimized for low-energy cognition,
- and limits on computation for non-essential tasks.
Planetary intelligence cannot emerge through systems that waste planetary resources. Any credible attempt to align AI with climate and ecological goals must include a rigorous commitment to minimizing and ultimately reversing these impacts.
Acknowledging this openly does not weaken the case for beneficial AI. It strengthens the integrity of the work and clarifies the standards to which we must hold ourselves.
2. The Risk of Extracting or Appropriating Indigenous Knowledge
Indigenous knowledge systems embody some of the most mature expressions of ecological intelligence on the planet. They are rooted in relationships, responsibilities, and long-term reciprocity with land, water, and the more-than-human world. It would be inappropriate—and historically dangerous—to treat such wisdom as a dataset to be mined or an ontology to be digitized.
AI cannot and must not “ingest” Indigenous wisdom the way it ingests text.
Much of what is essential in these traditions is not transmissible through abstraction: it is experiential, ceremonial, embodied, and place-based.
Therefore, any engagement with Indigenous knowledge must be governed by principles such as:
- relational accountability rather than transactional outreach,
- community-determined protocols for what may or may not be shared,
- co-created governance structures,
- consent grounded in trust and long-term relationship,
- and a clear shared purpose oriented toward healing, not extraction.
In this sense, the question is not “How can AI learn Indigenous wisdom?”
Rather: How can AI be guided to respect the principles underlying relational worldviews?
How can AI systems learn to recognize interdependence, reciprocity, and responsibility as foundational features of life on Earth?
Only through governance frameworks shaped by those who carry such traditions—not imposed from the outside—can AI evolve in a way that aligns with genuine stewardship.
3. How AI Interprets Earth’s Information
If planetary intelligence is to mean anything, AI systems must eventually learn not just from human discourse but from Earth’s own processes. This requires something qualitatively different from today’s static training datasets.
It requires:
- continuous ecological data flows,
- models that learn from long-term Earth system patterns,
- sensitivity to thresholds and feedback loops,
- and the ability to detect early signals of ecological instability.
Crucially, this involves a shift away from purely anthropocentric reasoning. AI must learn to recognize that ecosystems are not resources but relationships—a principle widely affirmed by ecological science and many Indigenous traditions, albeit expressed differently.
This is not an attempt to replicate Indigenous knowledge within machines. Rather, it is an effort to ensure that AI systems develop ecological literacy grounded in the realities of the world they will help us navigate.
4. AI’s Entanglement with Capitalism, Power, and Unintended Consequences
Another unavoidable concern is that AI today is dominated by corporations and governments whose interests are not always aligned with ecological or social well-being. Many worry that engaging in AI development—even for planetary benefit—risks legitimizing systems that may ultimately harm communities, degrade ecosystems, or concentrate power.
This is a legitimate dilemma.
But it leads to an equally important conclusion:
Refusing to engage with AI does not prevent its misuse; it merely abdicates influence over its trajectory.
The appropriate stance, then, is not withdrawal but responsible intervention—bringing ecological ethics, relational governance, and community values into an arena that urgently needs them. AI will shape the world we live in. The question is whether it will do so unconsciously, driven by profit and militarization, or consciously, guided by planetary limits and human responsibility.
5. The Epistemic Limits of AI
AI is extraordinary in its pattern recognition abilities, but it has no lived experience, no embodiment, no accountability to place or community, and no direct participation in the cycles of life. It does not feel the wind, plant a seed, or sit beside a river through the seasons. It can simulate pattern recognition but not relationship.
Therefore, we must avoid claiming that AI can replace human or ecological forms of knowing. Instead, we can recognize its potential to:
- integrate vast datasets more quickly than any institution,
- forecast risks that humans overlook,
- model complex causal interactions,
- support decision-making that respects planetary boundaries,
- and help coordinate collective action at unprecedented scales.
AI can augment—not supplant—other ways of knowing.
Planetary intelligence is not artificial intelligence alone; it is a partnership between humans, machines, and Earth’s living systems, each contributing in ways that the others cannot.
6. Toward a Responsible Path Forward
If we aspire to cultivate something resembling planetary intelligence, then we must root that work in principles such as:
- ecological humility,
- relational accountability,
- transparent governance,
- energy and resource responsibility,
- community participation,
- and a commitment to heal rather than extract.
The goal is not to build a technological salvation machine. It is to bring intelligence—in all its forms—into alignment with the living Earth.
AI, approached responsibly, may help us see patterns we have failed to see, adapt more quickly than our current institutions allow, and coordinate across scales that human cognition alone cannot manage. But only if we face its challenges honestly.
Planetary intelligence will not emerge from ignoring these dilemmas.
It will emerge from working through them, patiently and collaboratively, with an attitude of responsibility rather than control.
We stand at the threshold of a technological era whose consequences will depend entirely on the values we bring to it. If we choose to align intelligence with life, then AI can become part of a broader cultural transformation—one that deepens our understanding of our one precious world and strengthens our capacity to care for it.
If you’d like, I can:
- refine this for publication,
- shorten it for a more concise Substack style,
- propose a third concluding section that points toward the work of the Possible Planet Lab,
- or prepare Part 3 in the series: “What Planetary Intelligence Could Look Like in Practice.”