AI evidence extraction

The Apt Curation Model: An Epistemic Virtue Theory of AI-Assisted Authorship

Tiegue Vieira Rodrigues · Philosophy & Technology · 2026

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

9/10

Relevance

0/4

Quality (LMQS)

Evidence

Citations

110.33

FWCI

Top 10%

Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1007/s13347-026-01038-z

Methodology & findings

Study design

Philosophical analysis employing conceptual argumentation, the Socratic method, and application of Ernest Sosa's virtue epistemology framework (accuracy-adroitness-aptness model).

Main result

The paper establishes that traditional authorship models fail when applied to AI-assisted distant writing because they create an impossible dilemma: "The AAA model, applied to the compositional act of distant writing, suggests that either the human is not the author in the proper sense (Horn 1), or their authorship fails to constitute a reliable epistemic achievement (Horn 2)." The Apt Curation Model resolves this by relocating authorial competence to four curatorial virtues: "According to this account, a text produced through distant writing is a genuine epistemic achievement worthy of the human author if its success is due to the author's adroit exercise of a set of higher-order curatorial virtues. These virtues are not monolithic, but rather a set of distinct but interconnected competencies that, successfully exercised, form the core of responsible and effective authorship." These virtues are architectural, dialogical, evaluative, and integrative.

Research paradigm

Normative epistemology; virtue epistemology framework

Author conclusions

The authors conclude: "The Apt Curation Model enables humans to maintain their authority in knowledge creation when AI systems achieve higher levels of performance. The model enables users to learn proper AI usage techniques while developing new educational standards for behavior and defining essential teaching objectives for digital competence development." They further assert: "The human curator controls the generative process through their work in architectural planning, their expertise in dialogue, their ability to evaluate, and integrate information. The author achieves their primary contribution through proper AI tool implementation rather than working to block their adoption." The model successfully demonstrates that "The author maintains their role as the main knowledge creator who works independently from the writing process" through curatorial competence.

Limitations

The paper acknowledges that "this paper focuses primarily on epistemic authorship: contexts where texts make knowledge claims, advance arguments, or contribute to systematic inquiry" and that "while aesthetic authorship in experimental literature may indeed operate under different norms where architectural and integrative virtues can carry more weight, we do not claim that the Apt Curation Model applies uniformly across all textual genres." Additionally, the authors note: "A comprehensive account of aesthetic value in AI-assisted writing would need to address several unresolved questions." The model does not fully address collective human-AI authorship, dynamic technological change effects, or complete pedagogical and legal implications, as the authors state: "These pedagogical and legal applications merit dedicated research that can build on the epistemological foundation established here."

Open questions raised

The authors identify multiple gaps: (1) The relationship between epistemic and aesthetic authorship remains unresolved; (2) A complete account of aesthetic value in AI-assisted writing requires addressing questions about AI's capacity to develop stylistic elements; (3) The extension of the model to aesthetic authorship in poetry and experimental literature requires integration with aesthetic theory and philosophy of art; (4) Questions about collective human-AI authorship and distributed epistemic agency merit dedicated treatment; (5) Pedagogical implementation requires research on assessment methods, academic integrity maintenance, and preventing learning gaps; (6) Legal frameworks for copyright protection of curatorial work need development; (7) The impact of technological advancement on which curatorial virtues become more or less important requires investigation.
The authors identify multiple gaps: (1) Whether analogous models can be developed for aesthetic authorship beyond epistemic contexts; (2) The unresolved relationship between curatorial expertise for knowledge management and artistic value; (3) How collective human-AI competence should be distributed when multiple humans collaborate with AI; (4) How advancing AI capabilities will alter the relative importance of the four curatorial virtues; (5) How educational curricula should be reformed to teach curatorial virtues; (6) How intellectual property law should protect AI-assisted authorship; and (7) The need for comprehensive accounts integrating aesthetic theory, literary theory, and philosophy of art with the epistemological framework.
The paper identifies multiple future research directions: (1) Development of aesthetic authorship theory combining epistemological framework with aesthetic and literary theory; (2) Comprehensive account of aesthetic value in AI-assisted writing addressing stylistic elements and reader responses; (3) Collective authorship questions in multi-human AI collaborations; (4) Dynamic development implications as AI capabilities change; (5) Pedagogical curriculum reform; (6) Legal frameworks for intellectual property protection in AI-assisted authorship; (7) Investigation of how curatorial virtues apply across different technological capabilities and domains.

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