Decision Without Deciders: AI Governance and the Infrastructuralization of Accountability

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Authors: H. Tamba
Cited by: 0

Abstract

This preprint develops a structural theory of AI governance centered on the concept of "decision without deciders." Rather than treating AI accountability as a problem of regulatory design, policy implementation, or institutional responsibility, the paper analyzes how accountability itself is being infrastructuralized across contemporary socio-technical systems. It argues that responsibility is no longer located in identifiable human actors, institutions, or decision-makers, but is increasingly embedded in distributed architectures of automation, prediction, and delegation. The paper constructs a conceptual framework for understanding AI governance as a transformation of accountability structures, not as a governance failure, but as a systemic reconfiguration of decision-making itself. --- Full text (HTML): https://hirokitamba-ops.github.io/paper1.html --- Part of the TLIM Research Program (Tri-Layer Integrated Model).For foundational definition see:https://doi.org/10.5281/zenodo.18667835 Version v2: Added references for indexing and citation network integration.

Fields of Study & Subjects

Ethics and Social Impacts of AI Digitalization Law and Regulation E-Government and Public Services

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026
Language
EN
Document type
Preprint