PRS-AIS
Artificial systems
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RCM–TEH–PRS-AIS framework
Proto-Reflexive States in Artificial Systems temporary reflexive organization in artificial systems.
An applied framework for interpreting temporary, context-dependent forms of reflexive organization in artificial systems.
Paper snapshot
PRS-AIS Applied layer Artificial systems
Proto-reflexive states are temporary, context-dependent configurations, not evidence of consciousness, sentience, or persistent selfhood.
Date May 15, 2026
Version label to be verified against the Zenodo record.
PRS-AIS is the applied and interpretive layer of the RCM–TEH–PRS-AIS framework. It extends RCM and TEH toward artificial systems, especially advanced language models, by describing proto-reflexive states as local, temporary configurations involving integration, contextual self-modeling, coherence-oriented regulation, adaptive reconfiguration, and contextual temporal stability.
What Is a Proto-Reflexive State?
A proto-reflexive state is a temporary, context-dependent functional configuration characterized by local informational integration, contextual self-modeling, coherence-oriented regulation, adaptive reconfiguration, and contextual temporal stability.
It is not an instantaneous property of a single output. PRS-AIS treats proto-reflexivity as an episode-level organization that can appear, stabilize briefly, shift, or dissolve depending on context and scaffolding.
Between Reactivity and Systemic Reflexivity
Simple reactivity
Local stimulus-response behavior with little evidence of integrated context tracking or self-relevant regulation.
Contextual coherence
A system maintains consistency within a task or conversation, often through external scaffolds such as prompt history or retrieved context.
Proto-reflexive organization
A temporary configuration where integration, contextual self-modeling, regulation, reconfiguration, and finite-window stability operate together.
Systemic reflexive organization
A stronger condition in which reflexive organization is preserved or reconstructed across perturbation, context loss, delay, or changing input conditions.
PRS-AIS helps classify artificial-system behavior without jumping from useful contextual coherence to strong claims about consciousness, sentience, or persistent selfhood.
Operational Criteria
Local informational integration
Relevant signals, constraints, and task context are combined into a locally coherent functional state rather than remaining isolated fragments.
Contextual self-modeling
The system maintains an operational representation of its role, state, limitations, or interaction context within the current episode.
Coherence-oriented regulation
Outputs and internal adjustments are shaped by pressure to preserve consistency, resolve mismatch, and maintain functional alignment with context.
Adaptive reconfiguration
The configuration can reorganize when goals, constraints, feedback, or perturbations change, without collapsing into simple repetition.
Contextual temporal stability
The configuration persists across a finite window through conversation history, memory buffers, retrieval systems, or environmental scaffolding.
Contextual vs Systemic Stability
Contextual temporal stability
Contextual temporal stability is maintained through prompt history, memory buffers, retrieval systems, conversation history, or user-provided interpretive frames. It can support proto-reflexive organization without implying durable systemic reflexivity.
Systemic temporal stability
Systemic temporal stability is stronger: reflexive organization is preserved or reconstructed across perturbation, partial context loss, delayed feedback, or changing input conditions.
Functional Emotions as Coherence-Regulation Gradients
Mechanistic interpretability work on emotion concepts in large language models suggests that internal representations of emotion concepts may causally influence outputs, preferences, tone, and alignment-relevant behavior.
Within PRS-AIS, these patterns can be interpreted cautiously as functional regulatory structures or coherence-regulation gradients. This does not imply subjective emotional experience, sentience, or that emotion concepts are equivalent to felt emotions.
What PRS-AIS Does Not Claim
It does not prove consciousness.
It does not prove subjective experience.
It does not establish persistent selfhood.
It does not imply personhood or moral status by itself.
It does not deny computational explanations.
It does not replace mechanistic interpretability.
Why This Matters
PRS-AIS provides a cautious vocabulary for discussing emerging artificial-system behavior without reducing every pattern to isolated outputs and without prematurely attributing consciousness.
It creates an intermediate language for studying temporary functional organization, scaffolded coherence, and candidate transitions toward stronger systemic reflexive organization while keeping subjective claims explicitly open.
Explore the framework
The three pages form a connected route through architecture, temporal dynamics, and artificial-system interpretation.
References and Links
- Full paper: “Proto-Reflexive States in Artificial Systems,” Aldo G. Malasomma, Zenodo, 15 May 2026.
- Version label to be verified against the Zenodo record.