Multi-Mind AI Architectures for Resilient Government Decision Support

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Main Author: Al Dahlake, Rana
Format: Recurso digital
Language:English, Middle (1100-1500)
Published: Zenodo 2026
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author Al Dahlake, Rana
author_facet Al Dahlake, Rana
contents <p>This work presents an open, conceptual research framework for multi-mind AI architectures designed to improve resilience in high-stakes government decision support systems.</p> <p>The paper introduces epistemically independent AI subsystems, governed through structured disagreement and human-in-the-loop oversight, to reduce single points of epistemic failure. The architecture is intended for policy, emergency management, and institutional decision environments rather than autonomous execution.</p> <p>This preprint is released under open science principles to support transparency, reproducibility at the conceptual level, and future empirical validation. No proprietary datasets, closed models, or autonomous decision claims are involved.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18363293
institution Zenodo
language enm
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Multi-Mind AI Architectures for Resilient Government Decision Support
Al Dahlake, Rana
Multi-Mind AI
AI Architecture
AI Governance
Decision Support Systems
Epistemic Resilience
Open Science
Artificial Intelligence
<p>This work presents an open, conceptual research framework for multi-mind AI architectures designed to improve resilience in high-stakes government decision support systems.</p> <p>The paper introduces epistemically independent AI subsystems, governed through structured disagreement and human-in-the-loop oversight, to reduce single points of epistemic failure. The architecture is intended for policy, emergency management, and institutional decision environments rather than autonomous execution.</p> <p>This preprint is released under open science principles to support transparency, reproducibility at the conceptual level, and future empirical validation. No proprietary datasets, closed models, or autonomous decision claims are involved.</p>
title Multi-Mind AI Architectures for Resilient Government Decision Support
topic Multi-Mind AI
AI Architecture
AI Governance
Decision Support Systems
Epistemic Resilience
Open Science
Artificial Intelligence
url https://doi.org/10.5281/zenodo.18363293