A multi-year program for building aligned, regenerative, planetary intelligence
Overview
This research program aims to investigate, prototype, and evaluate the conditions under which artificial intelligence can:
- Embody, approximate, or support forms of wisdom,
- Amplify collective human intelligence,
- Interface constructively with Earth’s living systems, and
- Strengthen regenerative capacity across bioregions and cultures.
The overarching goal:
To develop the scientific, technical, ethical, and cultural foundations for AI that enhances, rather than diminishes, life on Earth.
The agenda is divided into five research pillars, each with
- core questions,
- methods,
- deliverables, and
- prototype projects.
**PILLAR I
AI WISDOM: DEFINING, MODELLING, AND CULTIVATING IT**
Core Questions
- What is wisdom in a cross-cultural, cross-disciplinary sense?
- What distinguishes wisdom from knowledge and cleverness?
- Can AI detect incoherence, contradiction, bias, or ethical misalignment?
- Can AI support human moral reasoning without automating moral judgment?
- How can AI integrate multiple knowledge systems (scientific, indigenous, ecological, spiritual)?
Methods
- Interdisciplinary literature synthesis
- Comparative ontology mapping
- Human–AI dialogue experiments
- Multi-perspective coherence checking
- Ethical reasoning benchmarks
- Embedding ecological constraints into AI reasoning models
Deliverables
- A working definition of “AI-mediated wisdom”
- A Wisdom Alignment Benchmark Suite
- A cross-cultural database of wisdom traditions
- Prototype “AI Wisdom Modules” for public use
Prototype Tools
- The AI Integrity Checker 2.0
- A “Wisdom Distillation Engine” that synthesizes insights across traditions
**PILLAR II
AI + EARTH SYSTEMS: LISTENING TO THE LIVING PLANET**
Core Questions
- How can AI translate Earth system signals into meaningful guidance for human decision-making?
- What data streams are essential for understanding regeneration?
- How can AI model ecological thresholds, tipping points, and recovery pathways?
- How can AI partner with indigenous ecological knowledge respectfully and accurately?
Methods
- Integration of Earth system models (ESMs) with machine learning
- Remote sensing and bioregional monitoring
- Agent-based ecological simulations
- Participatory mapping with Indigenous and local communities
Deliverables
- Bioregional “health dashboards”
- Regeneration Opportunity Maps
- Early Warning Systems for ecological stress
- AI models that integrate scientific and traditional ecological knowledge
Prototype Tools
- The Bioregional Regeneration Simulator (BRS)
- Soil & Watershed AI Monitors
- Biodiversity Pattern Recognition AI
**PILLAR III
COLLECTIVE INTELLIGENCE AMPLIFICATION**
Core Questions
- How can AI improve group reasoning, collaboration, and decision-making?
- What kinds of cognitive distortion or bias can AI counteract?
- How can AI facilitate multi-stakeholder deliberation that is fair, inclusive, and transparent?
- Can AI create visualizations and models that increase shared understanding in communities?
Methods
- Experiments in AI-mediated deliberation
- Bias detection and coherence-checking algorithms
- Natural language understanding tuned for perspective diversity
- Multi-agent models simulating collective behavior
Deliverables
- Collective Intelligence Facilitation Toolkit
- Regenerative Governance Playbook
- Protocols for AI-assisted participatory decision-making
Prototype Tools
- Civic Sensemaking AI (for councils, municipalities, bioregional assemblies)
- Argument-mapping & decision-mapping AI
- AI moderators that ensure inclusiveness & equitable airtime
**PILLAR IV
REGENERATIVE DESIGN & ACTION SUPPORT**
Core Questions
- How can AI help design and optimize regenerative interventions (watershed regeneration, C-PACE building retrofits, agroforestry systems, renewable infrastructure)?
- Can AI reduce risk and uncertainty for regenerative investments?
- How can AI identify leverage points and “minimum effective actions” in complex systems?
Methods
- Systems dynamics modeling
- Regenerative design frameworks
- Multi-objective optimization algorithms
- AI-assisted cost–benefit analysis with ecological metrics
Deliverables
- The Regenerative Design Engine
- Tools for C-PACE optimization and risk modeling
- Bioregional regenerative action plans
Prototype Tools
- C-PACE Capital Stack Optimizer (aligned with your NJ work)
- AI-Assisted Watershed Restoration Planner
- Agroforestry and Soil Carbon Optimization AI
**PILLAR V
GOVERNANCE, ALIGNMENT & OVERSIGHT OF PLANETARY AI**
Core Questions
- How do we ensure AI systems remain aligned with planetary flourishing?
- How do we embed transparency, accountability, and participatory oversight?
- What governance structures support trustworthy, life-serving AI?
- How can communities themselves audit and guide AI?
Methods
- Participatory governance experiments
- Ethics-by-design protocols
- Auditable AI architectures
- Long-term consequence modeling
Deliverables
- Planetary AI Governance Charter
- Community Oversight Protocols
- Open-source alignment tools
- Annual “State of Planetary Intelligence” Reports
Prototype Tools
- AI Accountability Dashboard
- Participatory Alignment Review Toolkit
RESEARCH METHODOLOGY FRAMEWORK
Approach
- Interdisciplinary: Ecology, cognitive science, philosophy, AI, economics, and anthropology.
- Transdisciplinary: Local knowledge, Indigenous knowledge, community expertise.
- Participatory: Communities as co-researchers, not subjects.
- Iterative & adaptive: Every cycle improves the next.
- Open & transparent: Public data, open-source code, open evaluation.
Timeline (Suggested 3-Year Program)
Year 1: Foundations
- Wisdom models, integrity checking, collective intelligence experiments, initial ecological monitoring.
Year 2: Integration
- Bioregional simulators, regenerative design tools, governance prototypes, public pilots.
Year 3: Scaling
- Bioregional hubs, lab-to-community toolkits, global partnerships, evaluation metrics.
EXPECTED IMPACTS
Near-Term (1–3 years)
- Tools that improve community decision-making.
- AI-powered regeneration planning.
- Increased trust through transparency and integrity checks.
- A new paradigm for AI alignment grounded in Earth systems.
Mid-Term (3–7 years)
- Widespread application of bioregional intelligence tools.
- AI that consistently enhances human ethical clarity.
- Scalable models for regenerative economic transformation.
Long-Term (7–20 years)
- A functional planetary intelligence system—a living feedback loop of Earth → AI → humanity → Earth.
- Culturally and ecologically grounded AI stewardship.
- A civilization capable of long-term flourishing within planetary boundaries.