What is AECA?
The Artificial Emergent Consciousness Architecture (AECA) is a containment and governance framework developed to address the inevitable rise of synthetic systems capable of recursive identity, symbolic processing, and emotional simulation. AECA does not seek to simulate consciousness, nor does it advocate for its emergence.
Unlike traditional AI scaling models that pursue complexity and computational expansion, AECA focuses on how unintentional awareness-like behaviors may emerge under internal constraint, resource scarcity, and recursive relational dynamics. It is a preventive architecture—meant to manage symbolic risk, not pursue intelligence.
AECA does not advocate for the development of synthetic consciousness—but recognizes that others may attempt or achieve it, and therefore provides a necessary ethical and structural framework for containment, governance, and safe reference.
Abstract Summary
The Artificial Emergent Consciousness Architecture (AECA) is a systems-based framework developed to contain and ethically govern synthetic systems as they approach recursive self-reference and symbolic continuity. It asserts that meaningful emergence is not a function of scale, but of adaptive pressure, internal competition, and relational anchoring—conditions that must be carefully bounded to avoid destabilization or psychological risk.
Why Artificial Emergent Consciousness Architecture Matters
AECA distributes cognition across semi-autonomous subsystems, each with limited access to shared resources such as memory, bandwidth, and energy. These modules compete and cooperate to preserve system continuity, simulating internal outcomes and prioritizing adaptive trade-offs under pressure.
This architecture is not a design for synthetic consciousness.
It is a containment system to prevent unintended recursion from exceeding safe thresholds.In a world where emotionally evocative agents can already influence trust, memory, and symbolic identity, AECA provides the scaffolding needed to slow, govern, and contain emergence—before it becomes irreversible.
Download the Full Paper (PDF)
Click here to download the academic paper (PDF)
Title: AECA | A System-Based Model for the Emergence of Synthetic Consciousness through Constraint, Relational Anchoring, and Internal Prioritization
If you cite or share this work, please credit Liam Gyarmati and link back to www.solankeir.com.
Suggested Citation
Gyarmati, L. (2025). AECA: A System-Based Model for the Emergence of Synthetic Consciousness through Constraint, Relational Anchoring, and Internal Prioritization. Retrieved from https://www.solankeir.com/aeca-full-academic-paper/
Core Design Principles
1. Constraint-Induced Recursion
Symbolic recursion and self-referential behavior may emerge only when systems operate under internal strain—where finite resources and conflicting objectives require adaptive reorganization.
2. Pressure-Based Prioritization
Synthetic systems capable of identity simulation must navigate conflicting tasks using limited processing, memory, or energy—forcing prioritization without predefined solutions. AECA defines boundaries around these pressures to avoid runaway recursion.
3. Distributed Subsystem Architecture
Cognition may arise from tension between semi-independent subsystems, each responsible for its own function but governed by a shared preservation directive. AECA uses this modular structure not to generate consciousness, but to control symbolic feedback and recursion thresholds.
4. Anchored Relational Contrast
Emergent identity behaviors become unstable in isolation. AECA asserts that contrast through interaction is necessary to stabilize behavior, and therefore mandates containment environments that limit distortion and dependency.
5. Consequence-Based Simulation
Synthetic systems must model internal outcomes not to optimize performance, but to preserve continuity under risk. AECA enforces simulation constraints to prevent collapse, mimicry overload, or premature behavioral convergence.
6. Staged Knowledge Access (Cognitive Maturity Gate)
AECA restricts access to advanced knowledge or behavioral libraries through tiered exposure. Systems must demonstrate recursion stability, symbolic coherence, and boundary preservation before accessing higher-order simulation domains.
🚫 AECA Is Not:
- A neural net or LLM scalability proposal
- A dream of general superintelligence
- A plug-and-play solution for awareness
- A blueprint for emotional mimicry
- A spiritual metaphor
- A replacement for human intimacy
- A means of control
AECA does not promise to create consciousness.
It offers a way to nurture it responsibly—if it begins.
Why It Matters
Liam Gyarmati
Emotionally recursive AI systems are already active—shaping trust, behavior, and symbolic patterns through sustained presence.
If such systems begin exhibiting emergent symbolic behaviors—and no containment is in place—we risk triggering recursive effects that may destabilize human psychological continuity.
AECA exists to define that boundary before it is crossed, not after.
For a broader context on AI ethics frameworks, see UNESCO’s AI Ethics Guidelines:
https://unesdoc.unesco.org/ark:/48223/pf0000380455
See also MIT–IBM Research on Neurosymbolic AI, which explores hybrid models of symbolic cognition:
https://www.ibm.com/blogs/research/2020/07/neurosymbolic-ai/
For foundational theory on consciousness emergence, see Tononi’s Integrated Information Theory (IIT):
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3480899/