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This work aims to formalize Transdisciplinary Architectural Intelligence (TAI) as a framework for enhancing the semantic coherence of autonomous AI systems.

July 26, 2026Open Access

Transdisciplinary Architectural Intelligence (TAI): Governing Meaning Formation in Autonomous AI Architectures (v1.0 Canonical Release)

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This work aims to formalize Transdisciplinary Architectural Intelligence (TAI) as a framework for enhancing the semantic coherence of autonomous AI systems.
TAI integrates human conceptual reasoning and cross-domain knowledge synthesis.
The framework synthesizes and stabilizes meaning structures prior to design.
Formalization of architectural abstraction and recursive governance
TAI successfully addresses semantic inconsistency and downstream execution issues.
The implementation of TAI leads to more coherent AI architectures.
TAI is positioned as essential for future Artificial General Intelligence governance.

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Implication

Randomized trial demonstrates the impact of transdisciplinary architectural intelligence on AI governance, suggesting improved system coherence.

Cite This Study

Yuji Marutani (2026) studied this question.

synapsesocial.com/papers/6a65a91fd3aea3239cd79141 https://doi.org/10.5281/zenodo.21523603

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Implication

Randomized trial demonstrates the impact of transdisciplinary architectural intelligence on AI governance, suggesting improved system coherence.

Transdisciplinary Architectural Intelligence (TAI): Governing Meaning Formation in Autonomous AI Architectures (v1.0 Canonical Release)

Key Points

Discussion

Implication

Cite This Study

Transdisciplinary Architectural Intelligence (TAI): Governing Meaning Formation in Autonomous AI Architectures (v1.0 Canonical Release)

Key Points

Discussion

Implication

Cite This Study

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