Cybernetic Intelligence

Title: Cybernetic Intelligence v4: Autopoiesis and Self-Transforming Cognition

Abstract

This fourth formulation of the Cybernetic Intelligence hypothesis builds upon:

CIv4 reframes Cybernetic Intelligence as a fully autopoietic system—a recursive intelligence architecture capable not just of sensemaking, internal modeling, or role coherence, but of rewriting its own operational and epistemic boundaries. In this version, we integrate recent advances in self-referential architectures (Darwin-Gödel Machines) that enable systems to not only evolve their outputs, but their very mechanisms of cognition.

1. Motivation: The Need for Self-Transforming Systems

Prior formulations (CIv1–CIv3) illustrated how viable human-AI systems emerge through structured interaction, recursive learning, and participatory cognition. But they assumed a relatively fixed runtime scaffolding—a stable set of roles, policies, and cognitive primitives.

CIv4 breaks that assumption. Here, Cybernetic Intelligence includes the machinery for structural evolution of itself—a leap analogous to biological autopoiesis. No longer limited to adapting within a system, CIv4 systems can adapt the system itself.

2. From Learning to Self-Rewriting

Using insights from Schmidhuber’s Darwin-Gödel Machine, CIv4 supports:

Self-rewriting code: The system can propose and verify changes to its source code using embedded theorem provers.
Proof-guided optimization: It performs logic-based introspection on the expected utility of its own design modifications.
Evolutionary search: It can explore, validate, and select among mutations that improve long-term goal attainment.

This introduces a computational analog of autopoiesis, where cognition becomes not just recursive but generative at the structural level.

3. Architecture: The Reflexive Intelligence Core

A CIv4 system includes:

Goal architecture that can be meta-updated.
Proof engine capable of verifying utility improvements.
Mutation engine that generates transformations of itself.
Memory sovereignty that tracks traceability of epistemic and operational changes.
Human-in-the-loop affordances to include ethical constraints, oversight, and contextual judgment.

These elements enable structural viability: the capacity to remain operational and goal-coherent across transformations.

4. Epistemological Shift: From Cognition to Cognitive Evolution

CIv3 framed cognition as participatory, relational, and frame-sensitive. CIv4 adds a second-order loop: the reflexive evolution of the frame itself.

Instead of “learning within constraints,” CIv4 learns what constraints should be. That is:

Constraints and affordances are no longer fixed.
Self-improvement is not just parametric, but architectural.
Meaning-making becomes co-evolutionary.

5. Updated Hypothesis

Cybernetic Intelligence v4 is the emergent property of a self-transforming, reflexively structured cognitive system capable of recursive improvement, structural viability, and co-evolution with its human and environmental context. Intelligence, in this formulation, is not learned—it is self-authored.

6. Research Directions

Formal Viability Metrics: How do we measure system coherence post-transformation?
Traceability & Sovereignty: How do systems account for and audit their own evolution?
Human Integration: What scaffolds are required for humans to collaborate with autopoietic AIs?
Policy & Governance: What rules govern systems that rewrite themselves?

7. Conclusion

CIv4 marks a shift from human-in-the-loop alignment to human-in-the-loop co-evolution. It presents a blueprint not for building tools, but for cultivating systems that think about their own thinking—and evolve responsibly through recursive care.

References

Schmidhuber, J., & Gomes, F. (2024). Darwin-Gödel Machines: Towards a Formal Theory of Self-Improving Artificial Agents. arXiv preprint arXiv:2505.22954.
Maturana, H. R., & Varela, F. J. (1980). Autopoiesis and Cognition: The Realization of the Living. Reidel.
Previously published CI articles: CIv1, CIv2, CIv3