Emergence Governance: A Canonical Field Map for Authorization-Centered Governance in High-Risk Systems
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| Natura: | Recurso digital |
| Lingua: | En |
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2026
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| _version_ | 1866902333918543872 |
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| author | Akarkach, Mounir |
| author_facet | Akarkach, Mounir |
| contents | <p>Emergence Governance is introduced in this publication as a unified research field concerned with the governance of complex adaptive and high-risk systems whose operational behavior emerges from dynamic state transitions rather than deterministic execution alone.</p> <p>Across artificial intelligence, biomedical systems, and critical infrastructures, contemporary governance approaches predominantly operate after execution through monitoring, auditing, filtering, or corrective intervention. Such post-hoc mechanisms address consequences rather than the permissibility of execution itself.</p> <p>This work formalizes an alternative architectural perspective in which execution — including computation, inference, or system action — is treated as a conditional capability requiring prior legitimacy verification.</p> <p>The paper consolidates previously established conceptual architectures developed by the author, including:</p> <ul> <li> <p><strong>A7SEM (Akarkach 7-Stage Emergence Model)</strong> — modeling emergence dynamics and transition legitimacy,</p> </li> <li> <p><strong>ASOSE (Semantic Emergence Field Specification)</strong> — preservation of semantic stability under complexity,</p> </li> <li> <p><strong>ASiSO (Action-Specific Oversight)</strong> — authorization logic tied to specific system actions,</p> </li> <li> <p><strong>Pre-Inference Governance</strong> — authorization-before-execution as a fail-closed governance principle.</p> </li> </ul> <p>Rather than proposing operational implementations or technical deployment procedures, this publication establishes a <strong>canonical field map</strong> defining scope, boundaries, structural layers, and analytical proof domains of Emergence Governance.</p> <p>Emergence Governance is positioned as an authorization-centered governance paradigm addressing the conditions under which complex systems are permitted to transition between operational states. The field therefore shifts governance attention from outcome correction toward legitimacy verification prior to irreversible execution events.</p> <p>Proof domains discussed include artificial intelligence systems, oncology as a high-complexity biological environment, and critical infrastructure systems, serving exclusively as analytical validation environments.</p> <p>This work is strictly <strong>non-operational</strong> and introduces no executable governance mechanisms, implementation guidance, engineering procedures, medical recommendations, or policy prescriptions. Its purpose is epistemic clarification and architectural stabilization of an emerging interdisciplinary research domain.</p> <p>The publication functions as a canonical reference point for future academic, regulatory, and conceptual discussions concerning authorization-centered governance of emergent systems.</p> <p><strong>Rights & Scope Notice</strong></p> <p>Conceptual architecture only.<br>No implementation or derivative operational rights are granted.<br>This work does not constitute engineering, legal, medical, or policy advice.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18819078 |
| institution | Zenodo |
| language | enc |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Emergence Governance: A Canonical Field Map for Authorization-Centered Governance in High-Risk Systems Akarkach, Mounir Emergence Governance Pre-Inference Governance Authorization Before Execution A7SEM ASOSE ASiSO High-Risk Systems Complex Adaptive Systems Auditability Insurability <p>Emergence Governance is introduced in this publication as a unified research field concerned with the governance of complex adaptive and high-risk systems whose operational behavior emerges from dynamic state transitions rather than deterministic execution alone.</p> <p>Across artificial intelligence, biomedical systems, and critical infrastructures, contemporary governance approaches predominantly operate after execution through monitoring, auditing, filtering, or corrective intervention. Such post-hoc mechanisms address consequences rather than the permissibility of execution itself.</p> <p>This work formalizes an alternative architectural perspective in which execution — including computation, inference, or system action — is treated as a conditional capability requiring prior legitimacy verification.</p> <p>The paper consolidates previously established conceptual architectures developed by the author, including:</p> <ul> <li> <p><strong>A7SEM (Akarkach 7-Stage Emergence Model)</strong> — modeling emergence dynamics and transition legitimacy,</p> </li> <li> <p><strong>ASOSE (Semantic Emergence Field Specification)</strong> — preservation of semantic stability under complexity,</p> </li> <li> <p><strong>ASiSO (Action-Specific Oversight)</strong> — authorization logic tied to specific system actions,</p> </li> <li> <p><strong>Pre-Inference Governance</strong> — authorization-before-execution as a fail-closed governance principle.</p> </li> </ul> <p>Rather than proposing operational implementations or technical deployment procedures, this publication establishes a <strong>canonical field map</strong> defining scope, boundaries, structural layers, and analytical proof domains of Emergence Governance.</p> <p>Emergence Governance is positioned as an authorization-centered governance paradigm addressing the conditions under which complex systems are permitted to transition between operational states. The field therefore shifts governance attention from outcome correction toward legitimacy verification prior to irreversible execution events.</p> <p>Proof domains discussed include artificial intelligence systems, oncology as a high-complexity biological environment, and critical infrastructure systems, serving exclusively as analytical validation environments.</p> <p>This work is strictly <strong>non-operational</strong> and introduces no executable governance mechanisms, implementation guidance, engineering procedures, medical recommendations, or policy prescriptions. Its purpose is epistemic clarification and architectural stabilization of an emerging interdisciplinary research domain.</p> <p>The publication functions as a canonical reference point for future academic, regulatory, and conceptual discussions concerning authorization-centered governance of emergent systems.</p> <p><strong>Rights & Scope Notice</strong></p> <p>Conceptual architecture only.<br>No implementation or derivative operational rights are granted.<br>This work does not constitute engineering, legal, medical, or policy advice.</p> |
| title | Emergence Governance: A Canonical Field Map for Authorization-Centered Governance in High-Risk Systems |
| topic | Emergence Governance Pre-Inference Governance Authorization Before Execution A7SEM ASOSE ASiSO High-Risk Systems Complex Adaptive Systems Auditability Insurability |
| url | https://doi.org/10.5281/zenodo.18819078 |