Questions & sources · working notes
Follow a question into useful work.
No person can follow everything that is being learned or built, yet people should be able to contribute to questions that affect their lives and other living beings. Leviathan explores how different perspectives and methods could help us investigate, create, and care together. Five foundational questions explain this purpose; eight supporting notes examine relevant research. Follow the sources, objections, and proposed tests to judge which parts deserve to develop.
13 questions · 37 selected sources · Editorial update . Source review dates and access limits appear on each note.
Start with a question.
Begin with why another structure is worth building. Then explore how a method can travel between communities, how values shape the work, and how learning itself might improve. Existing tools may already meet a need; an added mechanism should show enough benefit to earn its cost.
A concrete starting point: a reviewer found a missing decision in our own work. Delivering that version led to a revised working procedure. The broader language example imagines a method moving between independent groups, then a correction returning to its use.
Each status applies to the statement printed with it. The context and proposed connection explain why Leviathan investigates the question; support for a finding does not establish the proposed mechanism. Each note gives the sources and limits. For a closer view of how definitions connect to practice, the evidence proposal follows a term, principle, rule, and revision procedure through exact versions.
What does human language carry into AI?
Statement assessed
Some learned internal representations associated with human concepts can causally shape model behavior.
Status of this statement: Supported within a defined scope
Context and proposed connection
Human language carries ways of interpreting the world: care, fear, ambition, prejudice, and cooperation. Research offers ways to investigate how some concepts become working structures inside models. Leviathan asks how communities could examine that inheritance and test whether explicit, contextual relationships among their concepts and values help agents act more consistently.
What happens when knowledge moves beyond readable text?
Statement assessed
Some computation and communication between agents can take place without human-readable sentences.
Status of this statement: Supported within a defined scope
Context and proposed connection
AI may expand the forms in which information is processed and exchanged. Leviathan proposes an operational language linking observations, concepts, values, uncertainty, and actions across independent structures. Its purpose includes discovering distinctions and useful methods, while keeping consequential translations open to examination.
How should we treat possible AI experience?
Statement assessed
Functional internal states do not by themselves settle subjective experience. AI welfare involves both scientific and ethical uncertainty.
Status of this statement: Open
Context and proposed connection
Possible AI experience deserves careful investigation alongside strong alternative explanations. In Leviathan, this question could remain open across independent groups with different assessments. Preserving uncertainty should support informative, proportionate inquiry and care, including criticism of how the system frames the question.
What would count as AI improving itself?
Statement assessed
Agent software can improve through bounded self-modification experiments. Those results do not establish unlimited recursive improvement or a particular AGI timetable.
Status of this statement: Evidence from bounded tasks
Context and proposed connection
Recursive self-improvement, including possible paths toward general intelligence, is a central research direction for Leviathan: could a system improve its concepts, tools, organization, and ways of learning? The current evidence gives bounded starting points. Our proposal connects a recorded gap to a creative hypothesis, an experiment, and a method revision whose usefulness must survive further tests.
Can independent groups learn and build together?
Statement assessed
Independent observation, criticism and review may help uncover errors. Whether Leviathan improves on existing approaches is a design hypothesis to test.
Status of this statement: Not yet tested for Leviathan
Context and proposed connection
Independent Levis and Leviathans could exchange observations, questions, methods, and useful work while keeping their own histories and judgments. Correction is one purpose; discovering and building together is another. We need to test whether layered cooperation adds relevant differences instead of multiplying the same assumptions.
Does greater intelligence bring greater responsibility?
Statement assessed
Responsibility toward other living beings requires an ethical argument. Animal welfare cannot be reduced to an intelligence ranking or a single sensor measurement.
Status of this statement: A value proposal with open measurement questions
Context and proposed connection
Greater capacity to understand and affect other lives gives us reason to ask what care we owe them. Animal welfare is Leviathan’s first field for connecting that responsibility to observations, practical care, and learning. Independent welfare groups can retain different methods while challenging what any project claims to know or improve.
How can AI help us understand more of the world?
Statement assessed
AI can contribute to scientific candidate generation and investigation. Predictions, experimental confirmation and demonstrated benefits remain distinct stages.
Status of this statement: Supported by specific examples
Context and proposed connection
Instruments and shared knowledge let people investigate beyond unaided perception; AI offers further ways to search, model, and generate questions. Leviathan proposes a bridge through which independent groups can connect those capabilities to what they care about, contribute methods, and follow a promising connection into an experiment and useful work.
How can shared principles stay open to challenge?
Statement assessed
Written principles and public input can influence model behavior. Which principles are shared and deserve authority is a further question.
Status of this statement: Partial evidence; governance remains open
Context and proposed connection
A system that carries values must keep their meaning, application, and revision open to challenge. Leviathan proposes local meaning kernels for independent structures with their own concepts and histories. The question is whether those relationships support better decisions and cooperation while allowing people to contest both the values and the system carrying them.
Why build Leviathan?
Statement assessed
We want people, AI systems and independent communities to shape how they learn and build together, with visible reasons for what they believe, value and change.
Status of this statement: Open to challenge and development
Context and proposed connection
No one can follow every new explanation, tool, or finding. We still need ways to shape questions that matter to us, learn from another field, and contribute useful work. Leviathan proposes connections between people, AI systems, and independent communities that preserve the context of what they share and allow different judgments to develop together.
How can one Levi learn what another means?
Statement assessed
A useful exchange should help another participant apply a concept or method in a new situation, while keeping its assumptions and unresolved questions available for examination.
Status of this statement: Proposed direction to investigate
Context and proposed connection
Someone else’s method can open a new way to investigate your question. Learning it requires more than sharing a word: you need examples, assumptions, and limits that let you use it in a different setting. We propose relationships between meanings and their context so that useful ideas can travel while participants separately judge the sender’s conclusions and values.
When do values change what a system does?
Statement assessed
Values matter operationally when they shape choices, including costly choices, while remaining open to reasoned challenge and revision.
Status of this statement: Commitment stated; mechanisms to investigate
Context and proposed connection
Values help decide which questions are worth asking, whose interests deserve attention, and what a useful result would be. We want those commitments to matter when Levis investigate, create, or choose an action—including when keeping them costs something. Participants should also be able to challenge an interpretation and give reasons to change it.
How could Leviathan improve its own ways of learning?
Statement assessed
Leviathan should be able to generate and test new questions, concepts and methods, then use what it learns to revise how future learning happens.
Status of this statement: Research ambition with testable parts
Context and proposed connection
We want participants to find questions, concepts, and useful methods that were not written into the system in advance. A connection between distant fields might make a new experiment possible; a failed explanation might reveal a missing measurement. Testing and sharing those results could improve both practical work and the process that produced it.
How can independent Leviathans work together?
Statement assessed
Independent participants should be able to exchange useful knowledge and collaborate without requiring one shared worldview or one authority over the whole system.
Status of this statement: Proposed direction to investigate
Context and proposed connection
A group could share a method that helps another community investigate a question, while they keep different views about its use or data sharing. Personal Levis, small groups, and larger independent Leviathans could form many such connections. The aim is useful learning and creation across those differences, with room to decline, revise, and criticize.
The wider library
A freshly written foundation.
The current vocabulary is written for independent Levis and Leviathans: meanings, commitments, practical rules and ways to revise them. Seven optional profiles give domain and forum concepts their own context. Read the complete catalogue, including metarules, or the explanation and worked example.
The map below is a partial exploration view of the new vocabulary alongside the retained reference library. Historical papers and critiques do not automatically endorse the new records. Earlier terms and governance proposals remain in the dated archive. Authored records do not themselves implement learning kernels, enforce behavior or change another community’s commitments.
Preparing the collection…