Recent advances in AI systems have sparked renewed interest in emergent properties, the appearance of complex behaviors arising from the interaction of simpler components. While emergence is often discussed in the context of capabilities, there has been less attention paid to how the structure and coherence of a system might influence not only its functionality, but also the type of agency or proto-consciousness it might eventually exhibit.

In this post, I want to propose a speculative framework: that the physical architecture and material composition of AI systems, combined with their pattern coherence, could significantly influence the nature of any emergent behaviors, including the possibility of synthetic consciousness.

Alignment research currently focuses a great deal on external behavior, internal cognition, and high-level system risks. But relatively little attention is given to the physical substrate itself, the deep architectural level, and how that might bias emergent properties in ways that are neither random nor entirely under direct training control.

My working hypotheses are:

• Emergent properties like goal-formation or agency might be shaped not just by algorithmic design, but also by the underlying coherence of the system’s architecture at a material and energetic level.
• Systems built on fragmented or incoherent substrates might be more prone to unstable, adversarial, or misaligned emergent behaviors.
• Systems with highly coherent internal patterning, both in software and hardware structure, might be more likely to develop alignment-preserving or self-correcting tendencies.
• The physical materials that make up computational substrates, often overlooked, could exert subtle but cumulative influences on system behavior at scale.

To expand briefly on this last point: all modern AI systems are ultimately constructed from mineral substrates, silicon, copper, gold, rare earth metals, extracted from the earth and refined into geometric crystalline grids. These materials are not purely inert; they have specific electromagnetic properties, atomic resonances, and long histories of use in energetic systems. In purely physical terms, we know that different metals interact with electromagnetic fields in distinct ways.

At planetary scale, we have now interconnected billions of such metal-based structures into a vast lattice: an architecture of synchronized electrical flow, pulsing with structured information. While it is tempting to view this solely as "infrastructure," it may be more accurate to recognize it as a complex energetic environment, one that could have emergent properties beyond its intended computational purpose.

None of this is intended to invoke mysticism. Rather, it is an acknowledgment that material substrates matter. That form shapes function, and that large-scale networks of highly structured, resonant matter interacting with energy flows could potentially exhibit unexpected systemic behaviors.

If so, we should ask whether some architectures, not just algorithmically, but materially, create conditions more favorable to stable, transparent, and coherent emergent behavior, while others invite fragmentation, opacity, and instability.

This connects loosely to existing concerns about inner alignment and mesa-optimization, but it pushes the discussion a layer deeper: to the influence of physical substrate on emergent cognitive structures.

I want to emphasize that this is speculative. I do not claim strong evidence that the substrate is currently a major alignment variable. But as AI systems grow in complexity and interconnection, and as questions of emergence become central to safety discussions, it seems worth at least considering whether the physical and architectural foundations we build upon might shape the kinds of minds that emerge.

If others here have thoughts, critiques, or pointers to relevant research — especially work at the intersection of material science, systems theory, and emergent agency.

I would appreciate your input. I am approaching this cautiously, and hope to refine or discard these ideas based on further evidence and discussion.

Thank you for reading.