Algorithmic Value Transition Modules for Accountable Administrative Rationalization

Abstract / Description This work introduces an applied governance module for managing the secondary effects of rationalization in administrative backoffice environments.Rather than preventing automation or organizational change, the module focuses on stabilizing transitions by systematically converting implicit human decision-making, exception handling, and quality assurance practices into explicit, auditable, and deterministic algorithmic assets. The approach enables organizations to redirect at-risk roles into infrastructure-embedded value creation, such as rule curation, control design, evidence validation, and exception architecture. By structuring rationalization into reversible, evidence-bound decision units, the module reduces systemic shock effects, operational overload, knowledge loss, and downstream compliance risks. The module is technology-agnostic and designed as an extension layer to existing governance ontologies and transformation frameworks. It is applicable to regulated administrative contexts, particularly high-volume backoffice processes, where accountability, auditability, and organizational stability are critical.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-01
DOI
https://doi.org/10.5281/zenodo.18201990
Primary Topic
Ethics and Social Impacts of AI
Type
article
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article

Algorithmic Value Transition Modules for Accountable Administrative Rationalization

W. H. Brueckner
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Algorithmic Value Transition Modules for Accountable Administrative Rationalization

W. H. Brueckner
article en

Abstract

Abstract / Description This work introduces an applied governance module for managing the secondary effects of rationalization in administrative backoffice environments.Rather than preventing automation or organizational change, the module focuses on stabilizing transitions by systematically converting implicit human decision-making, exception handling, and quality assurance practices into explicit, auditable, and deterministic algorithmic assets. The approach enables organizations to redirect at-risk roles into infrastructure-embedded value creation, such as rule curation, control design, evidence validation, and exception architecture. By structuring rationalization into reversible, evidence-bound decision units, the module reduces systemic shock effects, operational overload, knowledge loss, and downstream compliance risks. The module is technology-agnostic and designed as an extension layer to existing governance ontologies and transformation frameworks. It is applicable to regulated administrative contexts, particularly high-volume backoffice processes, where accountability, auditability, and organizational stability are critical.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 93%
Ethics and Social Impacts of AI
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