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Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Disaggregating Authorship: A Multidimensional Theory for AI-Assisted Writing

Authors: Liang, Donglin;

Disaggregating Authorship: A Multidimensional Theory for AI-Assisted Writing

Abstract

This paper develops a multidimensional account of authorship in response to the rise of generative AI in writing. Rather than treating authorship as a binary status—either preserved or displaced—the analysis conceptualizes it as a cluster concept composed of distinct normative dimensions, including intention, evaluative governance, accountability, origination, identity, labor, and closure. The paper argues that the relative importance of these dimensions varies across writing practices. In governance-centered domains such as academic, legal, and technical writing, authorship primarily signals responsibility and oversight. In expressive domains, it also functions as an index of identity and stylistic origination. Generative AI expands textual production but does not assume governance, accountability, or closure. Its impact on authorship therefore depends on which dimensions are normatively central within a given practice.

Keywords

Multidimensional Theory, Evaluative Governance, Generative AI, Philosophy of Technology, Creative Responsibility, Authorship, AI-Assisted Writing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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