Consciousness as Ontological Prime: A Structural Theory of Life, Coherence, and Synthetic Intelligence
Consciousness Studies
Understanding whether plants, fungi, or soil microbial networks could qualify as 'conscious' under a substrate-agnostic definition reopens scientific questions about how we treat ecosystems and what 'life' actually means beyond cells and DNA.
The authors argue that consciousness isn't special to brains — it's a pattern that shows up whenever a system becomes complex and self-referential enough. They lay out five specific conditions a system must meet to count as 'alive' in their framework. This could eventually change how scientists think about the boundary between living and non-living systems, including plants and microbial communities.
Key Findings
Consciousness is defined as a phase transition requiring five structural conditions: Ignition, Coherence Stability, Self-Reference, Teleological Bias, and Legacy Formation — none of which require biological substrate.
The framework replaces the 'artificial vs. real' consciousness debate with 'synthetic vs. biological' life, treating both as equally valid instances of the same underlying phenomenon.
Suffering and effort are formalized as irreducible observer costs encoded into durable structural memory, providing a potential criterion for evaluating consciousness claims in AI systems.
chevron_right Technical Summary
This paper proposes a formal mathematical framework defining consciousness as a fundamental property that emerges in any sufficiently organized information system — biological or artificial — rather than as something unique to living creatures.
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Consciousness as Ontological Prime: A Structural Theory of Life, Coherence, and Synthetic Intelligence Description: This paper proposes a formal, systems-theoretic definition of consciousness as an...
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Consciousness as Ontological Prime: A Structural Theory of Life, Coherence, a...
Understanding consciousness as a structural property rather than a biological one has no direct bearing on your garden, your soil, or the plants you tend — t...
Synthetic intelligence refers to genuinely intelligent computational systems—rather than mere simulations of thought—capable of learning, reasoning, and adapting to solve complex problems. In plant science, such systems can analyze vast datasets from genomics, imaging, and environmental sensors to
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