Published 2025-12-31 | Version v0.1
White BookOpenPublished

Survivor Governance Risk Index (SGRI): Conceptual and Methodological White Book

Description

This white book introduces the Survivor Governance Risk Index (SGRI), a conceptual and methodological framework for assessing structural political risk under AI-driven automation. It defines Survivor Governance, develops a three-dimensional indicator architecture, explains composite index construction and risk bands, provides an illustrative calculation, and outlines data sources, typologies, limitations, and future empirical upgrade pathways.

Abstract

The Survivor Governance Risk Index (SGRI) White Book develops a structural early-warning framework for assessing whether AI-driven automation may erode the socio-economic population base required for inclusive and effective political participation. Rather than measuring democratic quality, regime type, or national AI capability, SGRI evaluates whether political influence is becoming concentrated among structurally non-displaceable groups while automation-exposed populations retain formal rights but lose effective political agency. The framework operationalizes this risk through three dimensions: Material Survivorship, Political Participation Skew, and Corrective Capacity. It defines nine core indicators, specifies normalization and aggregation procedures, proposes a composite formula, introduces qualitative risk bands, and presents ideal-type risk configurations for comparative analysis. The white book emphasizes profile-based diagnosis rather than country ranking and positions SGRI as a modular risk layer for future global AI governance, digital transformation, sustainability, and competitiveness index systems.

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Keywords

  • Survivor Governance Risk Index
  • SGRI
  • Survivor Governance
  • AI governance
  • AI-driven automation
  • structural political risk
  • political agency
  • effective political participation
  • automation displacement
  • material survivorship
  • political participation skew
  • corrective capacity
  • economic membership
  • democratic binding of AI decisions
  • algorithmic accountability
  • structural non-displaceability
  • AI and labor markets
  • AI policy
  • composite indicators
  • early-warning index
  • global AI governance
  • EPINOVA

Subjects

  • Artificial intelligence governance
  • Public policy
  • Political science
  • Political economy
  • Labor market transformation
  • Automation and society
  • Democratic governance
  • Composite indicator methodology
  • Systemic risk
  • Technology governance

Recommended citation

Wu, S.-Y. (2025). Survivor Governance Risk Index (SGRI): Conceptual and methodological White Book (IWP–25–01, v0.1). EPINOVA LLC. https://doi.org/10.5281/zenodo.18050662. DOI: To be assigned after Crossref membership approval.

APA citation

Wu, S.-Y. (2025). Survivor Governance Risk Index (SGRI): Conceptual and methodological White Book (IWP–25–01, v0.1). EPINOVA LLC. https://doi.org/10.5281/zenodo.18050662. DOI: To be assigned after Crossref membership approval.

Alternate identifiers

SchemeIdentifierDescription
EPINOVA internal publication numberIWP–25–01Internal EPINOVA Index White Book identifier
URLhttps://epinova.org/iwp2501Official EPINOVA publication page
DOIhttps://doi.org/10.5281/zenodo.18050662Zenodo/DataCite DOI landing page

Related works

RelationIdentifierTypeDescription
IsSupplementedByhttps://github.com/EPINOVALLC/EPINOVA-ResearchRepositorySupplementary EPINOVA research repository and structural archive
Referenceshttps://epinova.org/publications/f/survivor-governanceConceptual articleOriginal concept reference for Survivor Governance: Authority Concentration under AI-Driven State Contraction
IsIdenticalTohttps://doi.org/10.5281/zenodo.18050662White BookZenodo/DataCite DOI record for the SGRI White Book

References

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