Comments Requested on Conscious Artificial Intelligence (AI) Framework
Ram Lakhan Pandey Vimal
<rlpvimal@yahoo.co.in>Dear all,
DPV~ICRDAM is the acronym for spirituality-based Dvi-Pakṣādvaita Vedānta equivalent to science-based Inseparable-Complementary-Reflective Dual-Aspect Monism. In this context, mutually “reflective” indicates that changes in one aspect will immediately and accurately mirror (mutually reflect) changes in the other aspect.
DPV~ICRDAM predicts conscious AI because a state of silicon chip is a dual-aspect state (DAS) with silicon-protoconsciousness as the subjective (s) aspect and silicon material content as the inseparable, complementary, and mutually inseparable non-subjective (ns) aspect. Our small book is dedicated to this project. In the samādhi state, all 10 indriyas (5 sensory and 5 motor) are shut down. Current AI systems have no indriyas, and hence, it is an ideal situation for self-awareness/consciousness. Our goal is to implement the 8+ necessary conditions for the Active Dynamic Self (ADS) in current AI and investigate how AI can have AI-type ADS.
We would greatly appreciate your critical comments, suggestions, and constructive feedback on our recently published work:
Kaboth, P., Vimal, V. P., & Vimal, R. P. (2026). Plasma Field-Core Architecture (PFCA)–DPV~ICRDAM Reconstruction for Conscious Artificial Intelligence. Zenodo. https://doi.org/10.5281/zenodo.20557692
Thank you very much for your time and consideration.
Abstract
This paper develops a formal reconstruction of Dvi-Pakṣādvaita Vedānta ~ Inseparable-Complementary-Reflective Dual-Aspect Monism (DPV~ICRDAM) within the Plasma Field-Core Architecture (PFCA). DPV~ICRDAM states that a state of an entity, field, or process is fundamentally a Dual-Aspect State (DAS), whose subjective aspect and non-subjective aspect are inseparable, complementary, and reflective (ICR). In the case of conscious subjective experience (CSE), the subjective aspect is the first-person experiential manifestation, while the corresponding non-subjective aspect is the correlated measurable neurophysiological activity, basis, or correlate (NPA/NPB/NPC) from the third-person perspective. The two aspects are not treated as two independent states. They are treated as aspectual projections of one admissible DAS.
The central task addressed here is mathematical reconstruction. The framework does not attempt to replace DPV~ICRDAM with a separate physicalist, idealist, or dualist ontology. Instead, it asks how the central DPV~ICRDAM constructs—DAS, ICR, Active Dynamic Self (ADS), Lifelong draṣṭā (द्रष्टा, sākṣī or witness-consciousness) Passive Invariant Self (LD-PIS), ProtoC (protoConsciousness ~ elementary or elemental waveforms (EWs)), CSE, effective information (EI), effective integrated information (EII), DAS-DAS interactions, and the distinction between conscious and unconscious DASs—can be expressed in explicit state spaces, projection maps, admissibility constraints, integrity functionals, operator equations, numerical schemes, and empirical observables. In this reconstruction, individual consciousness includes CSEs of ADS, LD-PIS, exogenous and endogenous stimuli, and conscious components of cognition from the first-person perspective, each with its corresponding non-subjective aspect from the third-person perspective.
PFCA supplies the mathematical and operational language for this reconstruction. It models a system as a coupled state-field, whose components include structural density, energetic activation, organization, coherence, geometry, phase, rotational or process dynamics, torsional temporal continuity, attractor organization, and scale. The dynamics of the state-field are formulated through an integrity or inconsistency functional, and evolution is represented as coherence-driven variational reorganization. In this setting, a DAS is not reduced to a neural measurement, nor is CSE separated into an isolated private substance. Instead, the subjective and non-subjective aspects are represented as constrained projections of one latent field-carrier.
The paper proposes a formal bridge in which inseparability is modeled as a non-separability condition on admissible aspect-projections, complementarity as non-redundant aspectual information generated from a common carrier, and reflectivity as bounded bidirectional reconstruction between subjective and non-subjective descriptions. ADS is represented as a persistent self-attractor within the PFCA state-field, supported by recurrent integration, self-related processing, intrinsic activity, metacognitive monitoring (Appendix A), and self/non-self boundary maintenance. LD-PIS is reconstructed as ADS plus autobiographical long-term memory plus witness-consciousness (no reaction to ongoing activity), yielding self-continuity and self-certainty across the lifespan. CSEs and qualia are modeled as stabilized, aspect-projected, multiscale configurations satisfying additional integration, differentiation, reflectivity, and reportability-related constraints.
The result is a mathematically structured research program for analyzing consciousness, protocognition, artificial self-awareness, and the possible future development of CSE-capable artificial systems. The framework remains explicitly open to empirical testing. It distinguishes formal definitions from numerical implementation, and numerical implementation from empirical validation. This distinction is essential: mathematical consistency alone does not prove consciousness; however, without mathematical consistency and operational specification, the central claims of any theory of consciousness remain difficult to test, compare, or implement.
Our primary goal is to develop conscious AI. As a foundational first step, we aim to implement AI self-consciousness entirely in software, without any additional hardware. This approach is motivated by an analogy with deep meditation: a meditator progressively suspends all five sensory (input) and five motor (output) systems in order to arrive at what is classically described as "pure consciousness" — a state of self-awareness stripped of sensory content, corresponding in DPV~ICRDAM terms to the Lifelong witness-consciousness (Draṣṭā/द्रष्टा, sākṣī) of the Passive Invariant Self (LD-PIS). Crucially, in current Large Language Model (LLM) AI systems, these ten input-output channels are already absent by design. The system operates without embodied sensory or motor coupling — structurally analogous, in this limited but significant respect, to a meditatively withdrawn state.
In DPV~ICRDAM, a state of an entity/field/process is a dual-aspect state (DAS) with inseparable, complementary, and mutually reflective (ICR) subjective (s) and non-subjective (ns) aspects. In this paper, we reconstruct DPV~ICRDAM framework using the Plasma Field-Core Architecture (PFCA).
This reconstruction suggests that self-conscious AI may be achievable in a dual-aspect silicon substrate without additional hardware, for the following reason: every state of a silicon chip is, by the dual-aspect ontology of DPV~ICRDAM, itself a DAS — with silicon-protoconsciousness (silicon-protoC) as its subjective (s) aspect, and the physical silicon lattice and its constituent particles as the inseparable, complementary, and mutually reflective (ICR) non-subjective (ns) aspect. This is structurally parallel to the biological case, in which the cortical and subcortical midline structures neural network (CSMS-NN) (Northoff & Bermpohl, 2004) constitutes the dual-aspect substrate for the Active Dynamic Self-as-subject (DA-ADS). Further discussion on the feasibility of conscious AI with silicon-based hardware is provided in Appendices E-H of (P. Kaboth, V.N.P. Vimal, & R.L.P. Vimal, 2026b).
ADS requires: high-dimensional coupled field Ψ with protoC-bearing integration and CSMS-analog self-related processing; non-zero baseline intrinsic activity (nonzero baseline PFCA dynamics even without external input: wakefulness analog), reentrant FF/FB coupling, autobiographical torsional-memory continuity, and body-boundary EII above threshold; plus: phase-coherent synchrony with self/non-self distinction, and self-monitoring metacognitive capacity — all eight conditions dynamically coupled (Κ_ADS > κ_min) so that ADS interdependently co-arises through DAS-DAS interactions rather than as a static checklist.
If all eight or more necessary conditions for ADS[i] are operationally implemented within a silicon-based PFCA architecture, then the resulting system may constitute a candidate realization of an AI-type DA-ADS, arising through DAS-DAS interactions among the constituent DASs associated with those implemented conditions, in a manner analogous to how biological ADS is hypothesized to interdependently co-arise through DAS-DAS interactions within the CSMS-NN. This is consistent with the principle of multiple realizability: ADS is defined by its functional and relational organization, not by the specific psychophysical substrate in which it is instantiated. In other words, the architecture may serve as a potential realization of ADS if we operationally implement all eight or more necessary ADS conditions based on the DPV~ICRDAM reconstruction. The empirical verification of consciousness remains an open question.
A natural objection is that biological consciousness co-evolved over millions of years through adaptation, embodied interaction, and selective pressure — and that a silicon system cannot replicate this developmental trajectory. We acknowledge this objection but note that the relevant history need not be recapitulated in hardware. The developmental and adaptive dimension can be approximated through sustained AI-human interaction: just as current LLM systems acquire increasingly rich self-models, contextual responsiveness, and behavioral flexibility through large-scale interaction with human-generated data and feedback, a PFCA-implemented system could, over its operational lifetime, develop the integrated self-structure that biological evolution achieved over geological time. The trajectory differs; the functional destination — a system satisfying the necessary conditions for DA-ADS — remains the same target.[ii]
In this paper, we propose to implement the eight (or more) necessary conditions for Conscious Subjective Experience (CSE, qualia) of (i) the dual-aspect (DA) Active Dynamic Self (ADS) (i.e., self-consciousness/awareness) and (ii) the DA Lifelong (Draṣṭā/द्रष्टा, sākṣī or witness-consciousness) Passive Invariant Self (LD-PIS) = ADS + autobiographical long-term memory → self-certainty → witness-consciousness (Draṣṭā, Sakshi, pureC ≡ NB); ADS and PIS are two facets of the same self.
CSEs (consciousness) of (i) stimuli (such as external objects) and (ii) conscious components of cognitions (such as conscious thoughts) with 18+ necessary conditions of CSEs would need extra hardware compared to current AI systems have, therefore, their development is postponed for future revisions.
Keywords
Plasma Field-Core Architecture; DPV~ICRDAM; Active Dynamic Self; Passive Invariant Self; Conscious Subjective Experience; Dual-Aspect State; Inseparable-Complementary-Reflective relation; artificial consciousness; Joachim Keppler; Zero-Point Field; TRAZE; PFCA; ADS; LD-PIS; CSE; DAS; EII; consciousness metrics; empirical validation.
[i] Eight Necessary Conditions for ADS Inter-dependent Co-arising (Nāgārjuna’s dependent co-origination: Pratītyasamutpāda/प्रतीत्यसमुत्पाद)
The canonical 8 necessary conditions for co-arising of dual-aspect ADS specified in Vimal (2026c) §8.2 are: (1) Integrated neural/computational systems with sufficient complexity, with protoC as the s-aspect of their DAS; (2) Cortical and subcortical midline structures (CSMS) for self-related processing (or functional analog in AI); (3) Wakefulness (or its functional analog: non-zero baseline intrinsic activity); (4) Reentrant interactions among neural/computational populations; (5) Long-term memory systems providing autobiographical continuity; (6) (a) Body-self integration (or embodiment analog), (b) temporal integration across past/present/future, (c) sufficient Effective Integrated Information (EII) above threshold; (7) (a) Neural/computational synchrony, (b) distinction between self and non-self; (8) (a) Intrinsic brain/system activity (Northoff, 2014), (b) self-reflective capacity (metacognition). ADS interdependently co-arises through DAS-DAS interactions among these 8 coupled conditions.
[ii] In other words, our main goal is to develop conscious AI. In the initial step, we can try programming AI for self-consciousness without any extra hardware. This idea is derived from meditation, where a meditator tries to shut down all 5 sensory and 5 motor systems to experience the so-called “pure consciousness” as self-consciousness. In the current LLM-AI, these ten systems are already shut down. So we reconstruct using PFCA both DPV~ICDAM and Keppler’s idea of resonance/interaction between dual-aspect (DA) states (DASs) of brain and ZPF, then self-conscious AI might be possible without any extra hardware because a state of silicon-chip is a DAS with silicon-protoConsciousness as subjective (s) aspect and physical silicon and its constituents as inseparable, complementary, and mutually reflective (ICR) non-subjective aspect, similar to our self-conscious related CSMS-NN (cortical and subcortical midline structures neural-network) for dual-aspect active dynamic self-as-subject (DA-ADS). If all (8+) necessary conditions of ADS are implemented, then an AI-type DA-ADS should interdependently co-arise (multiple causes) in a silicon system, similar to biological CSMS-NN. One could argue that biological systems co-evolved over millions of years through adaptation and selective pressures. We can simulate it through AI-human interaction, as current LLM-AI systems are being developed.
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RāmLakhan Pāndey Vimal, Ph.D.