Revisiting computer authorship: a longitudinal perspective

Abstract Despite the proliferation of computer-generated texts, the concept of AI authorship remains ambiguous. This paper investigates evolving public perceptions of authorship pertaining to computer-generated texts through review of an international survey distributed in 2024/2025. Comparing results of this survey to those from the same survey distributed in 2017/2018, this paper offers what we believe to be the only longitudinal empirical consideration of AI authorship pre- and post-LLM boom. Even with dramatic technological advancements in natural language generation, this study suggests that societal understandings of authorship have only seen minor change since the survey’s first distribution. Participants continue to hold ambivalent opinions of AI authorship, perhaps partly due to the cultural and historical weight of the term ‘authorship’ itself. This ambivalence raises broader questions about the persistent usage of ‘authorship’ as a default term for describing computational text production. Through an interdisciplinary analysis represented by humanities and computational researchers, merging both quantitative and qualitative data, this paper interrogates whether the concept of authorship remains viable in discussions of computer-generated texts via feedback from survey participants.

Authors

Institutions

Publication Details

Journal
AI & Society
Published
2026-02-03
DOI
https://doi.org/10.1007/s00146-025-02783-z
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revisiting computer authorship: a longitudinal perspective

Leo Leppänen, Leah Henrickson
AI & Society
Authorship Attribution and Profiling
article

Revisiting computer authorship: a longitudinal perspective

Leo Leppänen, Leah Henrickson
article en

Abstract

Abstract Despite the proliferation of computer-generated texts, the concept of AI authorship remains ambiguous. This paper investigates evolving public perceptions of authorship pertaining to computer-generated texts through review of an international survey distributed in 2024/2025. Comparing results of this survey to those from the same survey distributed in 2017/2018, this paper offers what we believe to be the only longitudinal empirical consideration of AI authorship pre- and post-LLM boom. Even with dramatic technological advancements in natural language generation, this study suggests that societal understandings of authorship have only seen minor change since the survey’s first distribution. Participants continue to hold ambivalent opinions of AI authorship, perhaps partly due to the cultural and historical weight of the term ‘authorship’ itself. This ambivalence raises broader questions about the persistent usage of ‘authorship’ as a default term for describing computational text production. Through an interdisciplinary analysis represented by humanities and computational researchers, merging both quantitative and qualitative data, this paper interrogates whether the concept of authorship remains viable in discussions of computer-generated texts via feedback from survey participants.

AI & Society
University of Helsinki (FI), The University of Queensland (AU)
Helsingin Yliopisto, Helsingin ja Uudenmaan Sairaanhoitopiiri
Quality Education
Openalex Percentile: Top 71%
Authorship Attribution and Profiling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.