From aspiration to action: how artificial intelligence can center human and ecological flourishing
Revisiting “AI for Good” as Intent and Movement
“AI for Good” is a phrase that has gathered institutional weight: the UN and other bodies host an “AI for Good Global Summit,” convening high-level actors to explore technology, ethics, and social impact. Yet, such platforms often remain at the level of dialogue, principle, and projection — not grounded delivery.
What does it mean to move from rhetoric to realization? AI for Good must become more than a banner or slogan; it must be a framework for concrete, accountable, scalable action — particularly in underserved communities and in service to ecosystems.
Your AI Diary post raises precisely this tension: how can organizations like CRCS / Possible Planet carve a niche — not competing with large institutions, but complementing them through grounded, place-based experimentation and narrative leadership? ppbook.shbn.net That question is at the heart of a mature “AI for Good” vision.
A Grounded Vision: “AI for Good” Reimagined
Instead of seeing AI for Good as a generic, catch-all category, we can reinterpret it with sharper axes of orientation:
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From global to bioregional: AI for Good should be rooted in place — aligned with local ecosystems, communities, and cultural contexts.
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From polished prototypes to iterative pilots: Focus on small-scale, high-leverage experiments you can deploy, learn from, and scale.
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From principle statements to integrity frameworks: Create and publish guardrails and accountability tools— e.g. an “AI Integrity Checker” to detect misuse or bias. ppbook.shbn.net
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From competition to collaboration: Position as a bridge and convenor, not a replicator of existing AI-for-good initiatives. You don’t need to reinvent global summits — you need to root them in soil.
When you reframe “AI for Good” this way, the role of CRCS / Possible Planet becomes clearer: the connector, incubator, and translator between high-level visions and grounded, regenerative practice.
Practical Directions & Use Cases
Below are some pathways that align with and expand on your diary’s proposals:
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AI for Regeneration
— A thematic niche: AI applied to ecological restoration, carbon drawdown, soil health, biodiversity, and resilient communities.
— Use cases: species mapping, forest recovery forecasting, regenerative agriculture planning. -
AI Integrity Checker
— An open-source tool or audit framework to assess potential harms, bias, or misuse in AI models. (Already in your pipeline.) ppbook.shbn.net
— This can act as a proof-of-concept that signals credibility, transparency, and trust. -
AI for Right Livelihoods
— Tools to help people discover and transition into sustainable, meaningful, regenerative work — matching skills, opportunities, regional needs.
— Could integrate with regenerative finance, local economies, and ecosystem restoration projects. -
Place-Based Pilot Projects
— Focus on your home region (Genesee/Finger Lakes, or another bioregion) to deploy prototypes.
— Partner with universities, community groups, or ecological organizations for real-world testing. -
Narrative & Convening Infrastructure
— Publish thought leadership (e.g. the “AI for Regeneration” 2-pager) as both outreach and framing device.
— Convene working groups, workshops, or symposiums that bring AI practitioners, ecologists, ethicists, and local communities into dialogue.
Ethics, Accountability, & Cultural Grounding
“AI for Good” cannot flourish without a tough ethical backbone. A few guiding commitments:
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Transparency & auditability: Every AI system built or promoted must be auditable — open to third-party review or human oversight.
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Participatory design: Communities and stakeholders should have agency in design, not be passive subjects.
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Precaution & humility: When outcomes are uncertain, default toward restraint rather than risk.
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Integration of indigenous and local knowledge systems: AI should not replace local wisdom but respect, learn from, and uplift it.
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Ecological metrics over profit metrics: The success of AI-for-Good projects must be judged by ecological and human well-being, not financial return alone.
These guardrails mirror the kind of integrity frameworks you mention in your diary — the “AI Integrity Checker” being one symbolic expression of this approach. ppbook.shbn.net
A Question for Every Project
Each new AI initiative should confront a simple but powerful question:
“Does this advance the flourishing of humans, more-than-human life, and restore the relational balance between them?”
If the answer is no — even if something is technically impressive — it shouldn’t be called “AI for Good.” The label must be earned by alignment with deeper values, accountability, and place.
About the Author
Jonathan Cloud is the co-author of Possible Planet: Pathways to a Habitable Future and a researcher in regenerative systems, AI ethics, and the intersection of technology and ecological renewal. Through CRCS / Possible Planet, he explores how AI can serve life on Earth, not exploit it.