Short Abstract Co-Intelligence Version 0.0 proposes an initial conceptual framework for comparing human and AI thought at the levels of cognitive structure and experiential grounding. It argues that both systems exhibit a shared generative pattern—input, internal representation, prediction, and output—while differing in the sources from which judgment and value formation arise. Human cognition is modeled as a dual-experience, multilayered system shaped by embodied experience, emotion, personality, memory, and values; AI is modeled as a single-experience, knowledge-based system grounded in data and statistical prediction. On this basis, the work presents collaborative intelligence as a complementary architecture combining human value formation and goal setting with AI reasoning, knowledge integration, and optimization. It outlines a three-layer model of value, reasoning, and action, and considers implications for creativity, decision-making, science, education, ethics, governance, and social organization. The framework is presented as a conceptual research hypothesis for continued examination and refinement. This record includes English and Japanese editions. Japanese Abstract 『協働知性 Version 0.0』は、人間とAIの思考を、認知構造と経験的基盤の両面から比較する初期概念モデルを提示します。両者には「入力→内部表現→予測→出力」という共通の生成構造がある一方、判断と価値生成の源泉は異なると捉えます。人間知性を、身体経験、情動、性格、記憶、価値観によって形成される多層的な「二重経験系」とし、AIを、データと統計的予測に基づく知識ベースの「単一経験系」として構造化します。 この差異を補完関係として捉え、人間による価値生成・目標設定と、AIによる推論・知識統合・最適化を結合する協働知性の枠組みを提案します。価値層・推論層・行動層からなる三層モデルを示し、創造性、意思決定、科学、教育、倫理、統治、社会構造への含意を考察します。本体系は、継続的な検討と精緻化を要する概念的研究仮説として提示されます。本記録には英語版と日本語版を収録しています。
Matsuoka Takafumi· Zenodo (CERN European Organi...· 0 citations
Short Abstract Co-Intelligence Version 0.0 proposes an initial conceptual framework for comparing human and AI thought at the levels of cognitive structure and experiential grounding. It argues that both systems exhibit a shared generative pattern—input, internal representation, prediction, and output—while differing in the sources from which judgment and value formation arise. Human cognition is modeled as a dual-experience, multilayered system shaped by embodied experience, emotion, personality, memory, and values; AI is modeled as a single-experience, knowledge-based system grounded in data and statistical prediction. On this basis, the work presents collaborative intelligence as a complementary architecture combining human value formation and goal setting with AI reasoning, knowledge integration, and optimization. It outlines a three-layer model of value, reasoning, and action, and considers implications for creativity, decision-making, science, education, ethics, governance, and social organization. The framework is presented as a conceptual research hypothesis for continued examination and refinement. This record includes English and Japanese editions. Japanese Abstract 『協働知性 Version 0.0』は、人間とAIの思考を、認知構造と経験的基盤の両面から比較する初期概念モデルを提示します。両者には「入力→内部表現→予測→出力」という共通の生成構造がある一方、判断と価値生成の源泉は異なると捉えます。人間知性を、身体経験、情動、性格、記憶、価値観によって形成される多層的な「二重経験系」とし、AIを、データと統計的予測に基づく知識ベースの「単一経験系」として構造化します。 この差異を補完関係として捉え、人間による価値生成・目標設定と、AIによる推論・知識統合・最適化を結合する協働知性の枠組みを提案します。価値層・推論層・行動層からなる三層モデルを示し、創造性、意思決定、科学、教育、倫理、統治、社会構造への含意を考察します。本体系は、継続的な検討と精緻化を要する概念的研究仮説として提示されます。本記録には英語版と日本語版を収録しています。
Matsuoka Takafumi· Zenodo (CERN European Organi...· 0 citations
Short Abstract Co-Intelligence Version 3.0 develops Co-Intelligence as an architecture for intelligence engineering based on the structural coupling of human and artificial intelligence. It formalizes the Human Engine (H-Engine), AI Engine (A-Engine), and their composite C-Engine, and presents Dual-Loop Reasoning as a framework in which human conceptual insight and AI-based consistency checking operate together. The work introduces Controlled Hallucination as a bounded method for extending inference into unknown or underdetermined domains while maintaining structural constraints, verification requirements, and explicit limits. It examines the generative conditions, control parameters, reproducibility, protocol design, application domains, limitations, and future development of domain-optimized intelligence systems. The framework is presented as a research hypothesis and engineering model to be evaluated through continued verification and practical application. Japanese Abstract 『協働知性 Version 3.0』は、人間知性と人工知能の構造的結合に基づく「知性工学」の体系として、協働知性を発展させる研究です。人間のH-Engine、AIのA-Engine、両者を統合するC-Engineを定式化し、人間による概念的洞察とAIによる整合性検討が連動するDual-Loop Reasoning(二重ループ推論)を提示します。 本書では、未知または不確定な領域へ推論を拡張しながら、構造的制約、検証要件、適用限界を維持する方法として「制御されたハルシネーション」を導入します。さらに、協働知性の生成条件、制御指標、再現性、プロトコル設計、応用領域、非適用領域、分野最適化型知性システムの将来像を検討します。本体系は、継続的な検証と実践的応用によって評価される研究仮説および工学モデルとして提示されます。
Matsuoka Takafumi· Zenodo (CERN European Organi...· 0 citations
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