Opengea · AI Lab · Fig. 01
Meta-Globalium
A computable map of reality, for thinking and deciding without blind spots.
It is the Meta-Globàlium: a map of reality that lays out, in a single scheme, the dimensions, the objects, the relations and the flows that define it and make it intelligible. It builds on the Globàlium of Lluís M. Xirinacs (1932-2007), reformulating it, extending it and making it computable.
Why it is useful. Any view of a subject leaves parts of it out without noticing. The model makes those blind spots visible: it shows which dimensions of a question have been considered and which are still unexamined, and it lets you reconcile angles that looked incompatible.
Why we need it now. Because we think fast and each from our own corner: conversations stall when the parties are looking at different dimensions without knowing it, and we decide with half of reality out of sight. A shared scheme gives us a language to place any question, see what has been left out, and argue about the same thing. And it holds for machines too: artificial intelligence systems answer without saying where they are looking from. Only with an explicit map can we demand transparency and ethical alignment from them, instead of trusting them blindly.
- Origin
- The Globalium of Lluís M. Xirinacs (1932-2007)
- Contribution
- Reformulated, extended and made computable
- Use
- Holistic and systemic vision
We live surrounded by fragments
Each discipline sees its own piece, each chart highlights its own indicator, each algorithm optimises its own metric. Specialisation has given us enormous technical power, but it has left us without a common language to talk about the whole.
And most of today's challenges —climate, energy, politics, the economy, education— are systemic: they escape the silos and ask us to look at the whole again.
Every tool —a spreadsheet, an AI model, a digital infrastructure— encodes a view of the world. The question is not whether it encodes one, but which.
A map wide enough to place any question on it
It does not try to explain everything: it offers a frame where disciplines, knowledge and experience find their place and talk to each other. And it avoids two traps at once:
The fragment that thinks it is the whole
A single view that takes its part for the whole of reality.
The abstract whole
A view so general that it can no longer say anything concrete.
The dimensions it brings together
- Theory
- Practice
- Subject
- Object
- Phenomenon
- Noumenon
- Plasma
- World
Without opposing them or reducing one to another.
From the question to the whole picture
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01
Place
The question, project or debate is placed on the map.
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02
Go through
Each dimension is reviewed: what we know, what we do, where we are looking from.
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03
Detect
Blind spots appear: the dimensions that were left out. Often that is exactly where the problem lies.
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04
Reconcile
Each angle brings a part of reality: perspectives complement each other instead of clashing.
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05
Compute
With the Meta-Globalium, digital tools can reason with the map and show what they considered and what is still open. They do not replace human judgement: they guide it.
A tradition of thought, made computable
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1932–2007
Globalium
The life's work of Lluís M. Xirinacs: an integrative, pedagogical architecture of knowledge, designed to help us think rather than to give closed answers.
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Practice
Globalistics
The discipline of asking ourselves systematically which dimensions of a reality we are considering and which we leave out of the frame.
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2024
Meta-Globalium
Xirinacs conceived it as provisional and open to revision. We have reformulated it, extended it and made it computable, keeping its spirit.
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Application
Arkadium and Kosmos
Arkadium applies it to map human knowledge in a didactic and ethically aligned way; Kosmos, to organise real cooperation.
Where we use the model
A shared map of reality is useful wherever a question has to be seen whole: to think, to decide together and to demand transparency from machines.
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AI
AI alignment
An explicit map from which to demand transparency and ethical judgement from artificial intelligence systems.
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Analysis
Finding blind spots
Seeing which dimensions of a question have been considered and which are still unexamined.
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Governance
Deliberation and decisions
A common language so that all parties argue about the same thing and decide with the whole of reality in view.
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Relations
Conflict mediation
Placing each position on the map to reconcile angles that looked incompatible.
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Organisations
Strategy and evaluation
Reviewing a project or an organisation in all its dimensions, not just the economic one.
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Research
Organising knowledge
Relating concepts, disciplines and sources within a single computable scheme.
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Education
Systems thinking
Learning to look at the whole and its relations, not just the parts.
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Methodology
Regenerative design
Applying a regenerative methodology to people, communities and ecosystems.
AI already mediates our judgement
The technologies we are about to integrate at every level are not neutral instruments. The debate is no longer whether AI is good or bad, but how we learn to use it so that it makes us better.
The direction of change is not set by any algorithm: it is set by the models —implicit or explicit— with which we build our tools. Making them explicit, shareable, debatable and renewed by a community: that is the point of what we do.
Science is the engine of knowledge; technology is the engine of change.