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2026
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| Online Access: | https://doi.org/10.5281/zenodo.19891960 |
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| author | Ari Hayashi |
| author_facet | Ari Hayashi |
| contents | <p>Decomposition of the "Crossing of Goods" Based on v13 Theory and a Seven-Layer Observation Model for AI</p> <p>Abstract</p> <p>This document proposes a structured observation framework for analyzing human and AI decision-making processes based on the conceptual foundation of the 'v13' constraint model. Within this framework, value judgments such as 'good' and 'bad' are treated as dynamic and context-dependent rather than fixed or absolute. When multiple goal functions, each perceived as valid, intersect or conflict, decision-making coherence may degrade, leading to loss of directional clarity. We refer to this phenomenon as the 'Crossing of Goods.' To address this, we introduce the Seven-Layer Observation Model, which separates physical facts, biological responses, relational structures, and semantic interpretations into distinct analytical layers. We suggest that the conflation of these layers ('layer violation') is a significant contributing factor to misinterpretation and instability in both human reasoning and AI-generated outputs. This model does not attempt to define correct behavior. Instead, it provides a structural framework for identifying inconsistencies, reducing ambiguity, and improving interpretability in complex human-AI interaction environments.</p> <p>The Seven-Layer Observation Model</p> <p>The Seven-Layer Observation Model is a structured framework for decomposing complex human and AI-related phenomena into separable analytical layers. Inspired by layered system architectures, the model organizes observations from low-level physical constraints to high-level semantic interpretations.</p> <p>L1: Physical / Facts Layer<br>Definition: Objective, externally constrained conditions that are difficult to change. Characteristics: Value-neutral, acts as structural constraints. Examples: Organizational policies, contractual terms, measurable data, time, physical limitations.</p> <p>L2: Biological / Response Layer<br>Definition: Physiological and neurological responses of the human system. Characteristics: Independent from conscious control, directly affects cognition. Examples: Stress, fatigue, fear responses, sleep deprivation.</p> <p>L3: Relational / Roles Layer<br>Definition: Structural relationships and roles within systems or organizations. Characteristics: Defines communication paths and responsibility flows. Examples: Manager-subordinate relationships, customer-support structures.</p> <p>L4: Identity / Ego Layer<br>Definition: Psychological boundaries related to self-perception and personal value. Characteristics: Triggers defensive or reactive behavior when threatened. Examples: Need for recognition, avoidance of humiliation, maintenance of personal dignity.</p> <p>L5: Context / History Layer<br>Definition: Accumulated past experiences and relational memory. Characteristics: Introduces bias and affects interpretation of current events. Examples: Previous conflicts, trust history, prior expectations.</p> <p>L6: Presentation / Social Norms Layer<br>Definition: Socially acceptable forms of expression and communication. Characteristics: Encodes internal states into externally acceptable formats. Examples: Formal communication, politeness, business language.</p> <p>L7: Meaning / Philosophy Layer<br>Definition: Abstract interpretation, values, and conceptual meaning. Characteristics: Highest level of abstraction; may reinterpret lower-layer signals. Examples: Ethics, justice, ideology, personal beliefs.</p> <p>Usage Note<br>Human inputs are often expressed at higher layers (L6–L7), while root causes are frequently located in lower layers (L1–L4). This model is intended for structural observation and analysis, not for prescribing normative or ethical conclusions.</p> <p>Contact<br>For structural or research-related discussions only. LinkedIn: https://www.linkedin.com/in/a-hayashi-a763a4358/</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19891960 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Decomposition of the "Crossing of Goods" Based on v13 Theory and a Seven-Layer Observation Model for AI Ari Hayashi <p>Decomposition of the "Crossing of Goods" Based on v13 Theory and a Seven-Layer Observation Model for AI</p> <p>Abstract</p> <p>This document proposes a structured observation framework for analyzing human and AI decision-making processes based on the conceptual foundation of the 'v13' constraint model. Within this framework, value judgments such as 'good' and 'bad' are treated as dynamic and context-dependent rather than fixed or absolute. When multiple goal functions, each perceived as valid, intersect or conflict, decision-making coherence may degrade, leading to loss of directional clarity. We refer to this phenomenon as the 'Crossing of Goods.' To address this, we introduce the Seven-Layer Observation Model, which separates physical facts, biological responses, relational structures, and semantic interpretations into distinct analytical layers. We suggest that the conflation of these layers ('layer violation') is a significant contributing factor to misinterpretation and instability in both human reasoning and AI-generated outputs. This model does not attempt to define correct behavior. Instead, it provides a structural framework for identifying inconsistencies, reducing ambiguity, and improving interpretability in complex human-AI interaction environments.</p> <p>The Seven-Layer Observation Model</p> <p>The Seven-Layer Observation Model is a structured framework for decomposing complex human and AI-related phenomena into separable analytical layers. Inspired by layered system architectures, the model organizes observations from low-level physical constraints to high-level semantic interpretations.</p> <p>L1: Physical / Facts Layer<br>Definition: Objective, externally constrained conditions that are difficult to change. Characteristics: Value-neutral, acts as structural constraints. Examples: Organizational policies, contractual terms, measurable data, time, physical limitations.</p> <p>L2: Biological / Response Layer<br>Definition: Physiological and neurological responses of the human system. Characteristics: Independent from conscious control, directly affects cognition. Examples: Stress, fatigue, fear responses, sleep deprivation.</p> <p>L3: Relational / Roles Layer<br>Definition: Structural relationships and roles within systems or organizations. Characteristics: Defines communication paths and responsibility flows. Examples: Manager-subordinate relationships, customer-support structures.</p> <p>L4: Identity / Ego Layer<br>Definition: Psychological boundaries related to self-perception and personal value. Characteristics: Triggers defensive or reactive behavior when threatened. Examples: Need for recognition, avoidance of humiliation, maintenance of personal dignity.</p> <p>L5: Context / History Layer<br>Definition: Accumulated past experiences and relational memory. Characteristics: Introduces bias and affects interpretation of current events. Examples: Previous conflicts, trust history, prior expectations.</p> <p>L6: Presentation / Social Norms Layer<br>Definition: Socially acceptable forms of expression and communication. Characteristics: Encodes internal states into externally acceptable formats. Examples: Formal communication, politeness, business language.</p> <p>L7: Meaning / Philosophy Layer<br>Definition: Abstract interpretation, values, and conceptual meaning. Characteristics: Highest level of abstraction; may reinterpret lower-layer signals. Examples: Ethics, justice, ideology, personal beliefs.</p> <p>Usage Note<br>Human inputs are often expressed at higher layers (L6–L7), while root causes are frequently located in lower layers (L1–L4). This model is intended for structural observation and analysis, not for prescribing normative or ethical conclusions.</p> <p>Contact<br>For structural or research-related discussions only. LinkedIn: https://www.linkedin.com/in/a-hayashi-a763a4358/</p> |
| title | Decomposition of the "Crossing of Goods" Based on v13 Theory and a Seven-Layer Observation Model for AI |
| url | https://doi.org/10.5281/zenodo.19891960 |