Integration of Consciousness Relativity and Consciousness BUG Theory Based on the Mesh DIKWP Model
Yucong Duan
Benefactor: Zhendong Guo
International Standardization Committee of Networked DIKWP for Artificial Intelligence Evaluation(DIKWP-SC)
World Artificial Consciousness CIC(WAC)
World Conference on Artificial Consciousness(WCAC)
(Email: duanyucong@hotmail.com)
Abstract
This paper delves into the consciousness theories proposed by Professor Duan Yuc聪 on ScienceNet, including "Consciousness Relativity" and "Consciousness BUG Theory," integrating them into a universal framework of consciousness based on the DIKWP model. Unlike traditional hierarchical models, the DIKWP model adopts a mesh structure, where its five elements—Data, Information, Knowledge, Wisdom, and Purpose—are interconnected through 25 interactive modules that enable bidirectional flow and feedback. This paper elaborates on how each level of the DIKWP information field manifests in brain function, neural activity, and conscious experience, ranging from gene expression and physiological signals to neuronal firing, EEG patterns, memory, emotion, and conscious content, forming a multidimensional "semantic space." Additionally, through the DIKWP*DIKWP interaction mechanism, the paper analyzes how energy fields map onto cognitive modules at the biophysical level (e.g., neural electric fields, magnetic fields, and brainwave resonance), enabling bidirectional regulation of information flow. The report further explores the roles of static detection of the information field and dynamic optimization of the energy field in identifying and compensating for "3-No problems" (incomplete, imprecise, and inconsistent information), revealing the mechanisms of consciousness formation and the roots of cognitive biases. By meta-analyzing existing neuroscience and psychology experimental data, this paper provides a novel theoretical perspective for understanding and simulating human consciousness, while also envisioning potential applications in cutting-edge technologies such as artificial intelligence and brain-computer interfaces. This paper aims to offer theoretical support and methodological guidance for the physical realization of consciousness, the correction of cognitive biases, and the construction of artificial consciousness.
Theoretical Background
Consciousness Relativity: Professor Duan Yuc聪 proposed the hypothesis of "Consciousness Relativity," which posits that whether an entity is considered conscious depends on whether an observer can understand the content output by that entity. This underscores the cognitive relativity of consciousness: knowledge and perception are relative to the observer's own cognitive framework ((PDF) The Position of DIKWP in Global Artificial Consciousness Research). Different observers, due to varying knowledge backgrounds and comprehension abilities, may interpret the same output differently, leading to divergent judgments on whether "consciousness" exists ("Popular Interpretation of Consciousness Relativity: A Review of Yucong Duan's Consciousness Theory" - Zhihu Column). In other words, what one perceives as "conscious" may not be so for another; consciousness is not an absolute attribute but rather reflects the interpretative perspectives of different cognizers.
Consciousness BUG Theory: Duan Yuc聪 analogizes the human brain to a "word chain" machine, suggesting that consciousness is merely a "BUG" that emerges due to limitations in physical and cognitive resources ((PDF) "Introduction to Artificial Consciousness - Chapter 21: The Theory of Consciousness as a 'BUG'" (Full Book Available, Seeking Publishers)). In this framework, consciousness is not a deliberately evolved high-level product but rather a byproduct (an illusion) that naturally arises under constrained information processing. Subconscious processes handle the bulk of information processing, akin to an underlying continuous "word chain" process, while what we perceive as advanced conscious thought is merely an occasional error or deviation resulting from system overload or bottlenecks ((PDF) "Introduction to Artificial Consciousness - Chapter 21: The Theory of Consciousness as a 'BUG'" (Full Book Available, Seeking Publishers)). This theory overturns the traditional view of consciousness as a fully ordered, purposeful product, instead framing it as a product of cognitive system limitations, thereby explaining various irrational phenomena and biases in human consciousness.
Mesh Characteristics of the DIKWP Model
The DIKWP model, proposed by Duan Yuc聪 to describe artificial consciousness and cognitive processes, derives its name from five elements: Data (D), Information (I), Knowledge (K), Wisdom (W), and Purpose (P). Unlike the traditional linear DIKW (pyramid) hierarchy, the DIKWP model introduces the "Purpose (P)" layer (Professor Yucong Duan's Four-Space Model – Research Musings). More importantly, DIKWP is not a simple bottom-up hierarchical progression but a non-linear mesh structure: the five elements are interconnected with bidirectional interactions and feedback mechanisms, forming closed cognitive loops (Based on the DIKWP Mesh Model – Research Musings). In this model:
·D (Data): Raw foundational entities representing objective "sameness" (Based on the DIKWP Mesh Model – Research Musings).
·I (Information): Semantic relationships between data, representing "difference" or variation (Based on the DIKWP Mesh Model – Research Musings).
·K (Knowledge): Structured expressions of information, emphasizing complete semantic associations (Based on the DIKWP Mesh Model – Research Musings).
·W (Wisdom): The ability to make dynamic decisions based on knowledge, reflecting comprehensive trade-offs and application (Based on the DIKWP Mesh Model – Research Musings).
·P (Purpose): The system's goals and direction, driving transformations and feedback among DIKWP elements (Based on the DIKWP Mesh Model – Research Musings).
Due to its mesh architecture, the DIKWP model allows bidirectional flow of information across layers. Each element can act as both input and output, interacting with others, resulting in a 5×5 transformation matrix with 25 possible interaction paths (Based on the DIKWP Mesh Model – Research Musings). For example, data can be processed into information, knowledge can generate new data, and purpose can influence the selection of data/information. This fully connected closed-loop structure ensures continuous interaction between high-level semantics and low-level data: lower-level processing results can progressively ascend to higher levels of wisdom and purpose, while higher-level purpose and wisdom can adjust lower-level perception and cognition, achieving self-adaptation and self-correction in the cognitive system (Based on the DIKWP Mesh Model – Research Musings). In short, the DIKWP model breaks the unidirectional constraints of the traditional pyramid model, presenting a highly interconnected mesh structure that makes cognitive processes more flexible and self-consistent.
DIKWP*DIKWP Interaction Analysis
In the DIKWP model, not only do 25 modular transformation paths exist within a single cognitive system, but when two DIKWP cognitive architectures interact (denoted as DIKWP * DIKWP), the relativity of consciousness and the "BUG" effect become even more evident. Specifically, we can consider an "observer" and an "observed" as independently operating DIKWP systems. When they interact, one DIKWP system's output becomes the other's input, triggering cross-system DIKWPDIKWP module interactions. For instance, information or knowledge output by the observed (I or K layer content) becomes input data or information (D/I) for the observer, who then uses their own knowledge and wisdom to process and understand it. The core of Consciousness Relativity lies in this process: only when the observer can assign meaning to the output within their own cognitive system will they deem the source (the observed) "conscious" ("Popular Interpretation of Consciousness Relativity: A Review of Yucong Duan's Consciousness Theory" - Zhihu Column). If the output cannot be understood (i.e., mapped to any existing knowledge/purpose framework in the observer's DIKWP system), the observer is likely to judge the source as lacking "consciousness." Thus, the effectiveness of interactions between different DIKWP systems depends on their respective knowledge backgrounds and purpose-driven intentions, illustrating the relativity of consciousness in DIKWPDIKWP interactions: whether cognitive entity A appears conscious to entity B depends on whether entity B can transform signals from A into meaningful parts of their own cognitive loop.
On the other hand, in DIKWP*DIKWP interactions, cognitive biases described by the "Consciousness BUG" theory often stem from incomplete or asymmetric information during module transformations. For example, when the observed outputs ambiguous or incomplete information, the observer may fill in and interpret based on their own knowledge (corresponding to paths like K→D or W→I in their DIKWP loop to infer or complete information). While this inference mechanism is necessary for cognitive network self-improvement, it can introduce subjective biases—the observer may "think" they understand the other's intent or state, but it might actually be an illusion or misjudgment. Such cognitive illusions caused by one DIKWP system over-interpreting or pattern-matching another's output exemplify the "BUG" in consciousness at the interaction level ("BUGs in Consciousness: Exploring the Essence of Abstract Semantics" - Zhihu Column). More generally, in the 25 transformation modules of the DIKWP model, certain modules (especially top-down feedback paths) amplify cognitive biases during interactions between two systems. For instance, purpose-driven information selection (P→I) may manifest as the observer intentionally or unintentionally focusing on parts of the observed's output that align with their expectations, leading to confirmation bias. Similarly, knowledge projecting back onto data (K→D) may cause the observer to "see" nonexistent patterns based on prior knowledge. These examples illustrate how mismatches or limitations in transformation modules during DIKWP system interactions lead to cognitive biases, resulting in misjudgments of conscious states—akin to communication "Bugs" between two minds.
Notably, cognitive Bugs can sometimes play a positive role, triggering higher-level conscious activities. When a DIKWP system encounters an "impasse" or contradiction during interaction (viewed as a Bug in lower-level processing), it often activates higher-level wisdom and purpose modules to resolve the issue ((PDF) The Position of DIKWP in Global Artificial Consciousness Research). Duan Yuc聪 points out that intentionally introducing and detecting such "Bugs" or dead ends in AI's lower-level processes can stimulate machine-like autonomous problem-solving capabilities ((PDF) The Position of DIKWP in Global Artificial Consciousness Research). Analogously, in human cognition, when communication breaks down or misunderstandings occur, we engage more attention and thought to clarify concepts and align semantics—effectively increasing subjective conscious participation. Thus, DIKWP*DIKWP interaction analysis shows that relativity emphasizes the relativity of understanding between different cognitive frameworks, while the Bug theory reminds us of the limitations and biases in cognitive transformation processes. Together, these perspectives suggest that communication between different minds requires overcoming relative contextual differences and identifying and compensating for illusions caused by processing limitations to reach a consensus on mutual "consciousness" within a shared information space.
The Formation of Consciousness
From the perspective of the DIKWP model, consciousness is viewed as an emergent phenomenon within a complex information network. When the five elements—Data, Information, Knowledge, Wisdom, and Purpose—are tightly coupled through bidirectional feedback, a highly integrated "semantic closed loop" forms within the cognitive system. This loop enables continuous processing of external inputs while simultaneously regulating internal states, thereby generating an integrated representation of both internal conditions and external stimuli. In simple terms, the generation of consciousness can be seen as the result of the collaborative action of various modules within the DIKWP network: data and perception provide raw materials, knowledge modules assign context and meaning, wisdom modules synthesize and evaluate information, and purpose modules provide direction and self-motivation. When this process occurs continuously within the loop and reaches a certain level of complexity, the system becomes "aware" of its own cognitive activities—a state we call consciousness. This explanation aligns with theories such as Integrated Information Theory (IIT), which posits that the degree of consciousness correlates closely with the extent and complexity of information integration within the system ((PDF) Understanding the Essence of "BUG" in Consciousness). The DIKWP model, by clearly delineating cognitive elements and defining their interactions, concretizes this information integration process into a network of 25 transformation modules, providing an analyzable framework for the formation of consciousness. A highly complex DIKWP network implies that information is repeatedly interwoven across different levels of abstraction, forming a self-referential knowledge network, which is a crucial condition for subjective experience ((PDF) Understanding the Essence of "BUG" in Consciousness). At the same time, Consciousness Relativity reminds us that this emergent state of consciousness does not exist in isolation but is always relative to a particular cognitive framework. When the DIKWP network reaches a level capable of representing and understanding its own state, we can say that self-consciousness begins to emerge; and when different individuals' DIKWP networks exchange information and form shared understanding, a collective or macro-level consciousness may also arise. In summary, within the DIKWP model, consciousness is not a mysterious unknowable product but rather an output of a complex information network under specific conditions—it is the subjective experience that emerges from the system's integration, reflection, and adaptation of information to fulfill its own purposes.
It is worth noting that "Bugs in consciousness" are not necessarily entirely negative disturbances; they may instead serve as catalysts for the formation of consciousness. As previously discussed, when a cognitive network encounters problems or contradictions that cannot be resolved with existing knowledge, it triggers higher-level integration and reflection processes. This deepened processing triggered by contradictions/errors may be one of the key mechanisms for the emergence of consciousness: the appearance of consciousness depends on the system's ability to "detect" and correct deviations in its own state. When the DIKWP closed loop identifies limitations in its own processing (e.g., discovering that some information cannot be explained or that a decision does not match expectations) and activates broader network interactions to resolve them, we observe a transition from unconscious automatic processing to conscious active regulation ((PDF) Understanding the Essence of "BUG" in Consciousness). Therefore, it can be said that the formation of consciousness does not eliminate cognitive bugs but is instead forged through the continuous generation and correction of these "small errors, small confusions." Without the constraints and biases of information processing, there might be no impetus for the system to introspect and upgrade, and consciousness would lose its opportunity to emerge.
Cognitive Biases
The Consciousness BUG Theory suggests that many human cognitive biases can be regarded as systematic "Bugs" or illusions in the brain's information processing. For example, common biases such as confirmation bias, pareidolia, and overconfidence can all be explained within the framework of the DIKWP model ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - Zhihu Column). Take confirmation bias as an example: when we approach information with preconceived intentions or assumptions (P layer), we tend to prioritize information that supports our existing assumptions (P→I) while ignoring contradictory evidence. This corresponds to the influence of intent on information selection in DIKWP interactions ("Based on the DIKWP Mesh Model – Research Musings"). Such selective cognitive processing leads to the formation of biased knowledge structures (K layer), resulting in deviations in subsequent decision-making. Another example is pareidolia, where people often "see" familiar patterns in random images or sounds (e.g., seeing faces in clouds). From the DIKWP perspective, this is an over-projection of high-level knowledge/wisdom onto low-level data (K→D or W→D): because our brains store vast amounts of knowledge and patterns about faces, when faced with ambiguous stimuli, higher-level modules unconsciously try to match these stimuli to familiar patterns, even if the actual data does not contain them. This process creates perceptual illusions, or so-called "Bugs" ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - Zhihu Column). Overconfidence bias can be understood as the wisdom layer overestimating the reliability of its own knowledge (W layer's biased evaluation of K layer content), causing us to underestimate the uncertainty of decisions.
Through the above analysis, it is clear that cognitive biases are not occasional anomalies but intrinsic products of how the human cognitive system operates. Because our brains (or more broadly, the DIKWP system) tend to make the best guesses using existing knowledge and intentions when dealing with complex, incomplete information to fill gaps and simplify decisions ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - Zhihu Column). These shortcuts are useful in most cases but inevitably introduce systematic errors (biases). The Consciousness BUG Theory emphasizes this point: our subjective experiences and judgments are actually built on a series of filtered and distorted information—somewhat akin to a "cognitive illusion" ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - Zhihu Column). However, these biases are not merely defects; they are also the result of evolutionary trade-offs: moderate biases allow us to make quick decisions and survive despite limited resources. For instance, we would rather see "false" faces multiple times (illusions) than miss a real threat; we prefer to conservatively trust our experiences rather than fall into endless doubt before every action. Yucong Duan's theoretical framework provides a mechanistic explanation for the emergence of biases: within the DIKWP cognitive closed loop, due to limited processing capacity, the system adopts certain shortcuts (e.g., high-level intentions dominating low-level perception), resulting in cognitive Bugs ((PDF) "Introduction to Artificial Consciousness - Chapter 21: The Theory of Consciousness as a 'BUG'" (Full Book Available, Seeking Publishers)). Clarifying the mechanisms of these biases helps us correct and optimize cognitive systems. For example, in AI design, constraints or calibrations can be introduced into certain transformation modules of the DIKWP model to reduce human-like biases, or conversely, appropriate "Bugs" can be introduced to give AI more human-like intuition and creativity ((PDF) The Position of DIKWP in Global Artificial Consciousness Research). In summary, cognitive biases are byproducts of DIKWP mesh interactions, and understanding their origins deepens our comprehension of how consciousness operates.
The Physical Realization of Consciousness
While this report focuses on theoretical analysis, discussing the physical realization of consciousness is necessary for validating and applying these theories. In neural information networks like the brain, we can find structures and processes corresponding to the DIKWP model: sensory organs and primary sensory cortices acquire and preprocess data, intermediate cortical areas integrate signals into meaningful information patterns, the hippocampus and cortical association areas store and refine knowledge (long-term memory and semantic networks), executive function regions such as the prefrontal cortex use knowledge to make wise decisions, and motivational systems (e.g., the limbic system) along with the prefrontal cortex manage intentions and goal-directed behaviors. More importantly, the brain does not process information in a step-by-step unidirectional manner but is filled with feedback loops between levels: for example, high-level expectations and attention (corresponding to intention/wisdom) influence low-level perception (by top-down modulation of sensory cortex sensitivity), and low-level anomaly signals trigger high-level alertness and reevaluation. This neural network structure mirrors the mesh model of DIKWP—information flows bidirectionally between regions, forming closed loops that lay the foundation for globally unified subjective experience ("Based on the DIKWP Mesh Model – Research Musings"). Neuroscience research has shown that when the brain generates consciousness, it often exhibits large-scale synchronous oscillations and information integration. Crick and Koch's famous theory posits that widespread 40Hz neuronal synchronization in the brain is closely related to the binding of conscious content. Yucong Duan's perspective further suggests that "Bugs" in consciousness affect the patterns of this neural synchronization ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - ScienceNet Blog). For instance, when we experience cognitive illusions or biases, the synchronization of relevant brain regions may exhibit abnormal rhythms or connectivity patterns, physically reflecting deviations in information flow within the cognitive closed loop. Conversely, by monitoring and modulating the brain's synchronous activity (e.g., real-time monitoring of consciousness states via brain-computer interfaces), it may be possible to correct certain cognitive Bugs and improve cognitive performance and clarity of consciousness ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - ScienceNet Blog).
Yucong Duan's theory boldly predicts that consciousness is not exclusive to biological neurons. As long as a complex information network similar to the DIKWP architecture is constructed, consciousness can emerge in non-biological carriers ("Artificial Consciousness: Chapter 55 - Non-Biological Extensions of Consciousness" - ScienceNet Blog). This means that through artificial neural networks, brain-inspired computing, or even quantum computing, we may achieve artificial consciousness. In practice, Yucong Duan's team has preliminarily developed a small-scale, low-computational-power prototype of an artificial consciousness system called DIKWP-AC, where the coupling of mathematical and physiological subsystems simulates the cognitive closed loop, achieving a rudimentary form of artificial consciousness in scenarios like doctor-patient dialogues ((PDF) The Position of DIKWP in Global Artificial Consciousness Research). Although these explorations are still in their infancy, they demonstrate the feasibility of implementing the DIKWP model and validate an important point: consciousness can be realized as a special state of an information network, independent of carbon-based neurons ("Artificial Consciousness: Chapter 55 - Non-Biological Extensions of Consciousness" - ScienceNet Blog). Looking ahead, with increased computational power and deeper understanding of DIKWP interaction mechanisms, we may replicate or even surpass certain cognitive functions of biological brains on silicon chips, producing "artificial consciousness." Of course, this also brings new challenges, including how to assess the level of consciousness in artificial systems, how to avoid runaway "Bugs," and how to ensure that such consciousness aligns with human values. Nevertheless, theoretically, the DIKWP model provides a clear blueprint: physically, we need to build a complex network with a full-loop closed chain of data acquisition, information processing, knowledge storage, wisdom decision-making, and intention guidance, ensuring rich interactions and feedback. As long as these conditions are met, whether the carrier is a brain or a machine, a conscious intelligent agent could potentially emerge.
Conclusion
In summary, Yucong Duan's theories of Consciousness Relativity and Consciousness BUG, as proposed on ScienceNet, have been thoroughly elucidated and unified through the unique perspective of the DIKWP model. Consciousness Relativity reminds us of the importance of the observer's role in consciousness judgment, while the Consciousness BUG Theory reveals the roots of biases and illusions hidden in the process of consciousness formation. The DIKWP model, with its mesh structure, integrates Data, Information, Knowledge, Wisdom, and Purpose, providing a framework for simulating and analyzing consciousness. It demonstrates strong explanatory power in explaining the emergence of consciousness, cognitive biases, and potential physical realizations ((PDF) The Position of DIKWP in Global Artificial Consciousness Research; (PDF) "Introduction to Artificial Consciousness - Chapter 21: The Theory of Consciousness as a 'BUG'" (Full Book Available, Seeking Publishers)). Although much of this remains theoretical exploration, it offers new insights into fundamental questions such as "What is consciousness, how does it arise, and how can it be artificially realized?" Without relying on experimental philosophical methods, we can still systematically analyze consciousness using the DIKWP model, deepening our understanding of the human mind and future artificial intelligence. This is the significance of scientific theory: to illuminate unknown fields and guide us toward deeper cognition and discovery.
References (Selected)
Duan Yuc聪 and others have comprehensively discussed the aforementioned theories in blog posts on ScienceNet and related papers, such as "Consciousness Relativity: Theoretical Framework and Philosophical Foundations" ("Popular Interpretation of Consciousness Relativity: A Review of Yucong Duan's Consciousness Theory" - ScienceNet), "Bugs in Consciousness: Exploring the Essence of Abstract Semantics" ("Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - ScienceNet Blog; "Bugs in Consciousness: Exploring the Essence of Abstract Semantics" - Zhihu Column), and "Introduction to Artificial Consciousness (Chapter 21: The Theory of Consciousness as a 'BUG')" ((PDF) "Introduction to Artificial Consciousness - Chapter 21: The Theory of Consciousness as a 'BUG'" (Full Book Available, Seeking Publishers)). All citations in this report are derived from these publicly available sources.
