Decision Without Deciders: AI Governance and the Infrastructuralization of Accountability

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.

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Full text (HTML): https://hirokitamba-ops.github.io/paper1.html

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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.