Article

Detection, Disclosure, and Verification: A Repeated Game of Generative AI and Scientific Credibility

2026-03-31

Abstract excerpt

As generative AI lowers the marginal cost of producing polished scientific prose, institutions increasingly rely on AI-detection systems to preserve authorship norms and epistemic standards. Yet detection and generation are strategic complements: stronger detection induces stronger evasion, while stylometric policing can redirect effort away from truth-directed verification toward presentation-directed laundering....

Topics

Open a Topic to create a Post that cites this publication.

Genotype

Identifiers and source

Literature Corpus work: 6f938dec-75c8-51e7-a019-08dc8eaa3873
DOI: 10.22541/au.177499312.21860755/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Detection, Disclosure, and Verification: A Repeated Game of Generative AI and Scientific CredibilityDOI 10.22541/au.177499312.21860755/v1Read

From Debate to Practice: Why Research Needs Principle-Driven Frameworks for Responsible AI UseSemantic proximity Read

Generative Artificial Intelligence and Responsible Authorship: Scientific, Ethical, and Legal ConsiderationsSemantic proximity Read

AI-Assisted Textual Communication and Crowdfunding PerformanceSemantic proximity Read

The Undetectable Ethics: Artificial Intelligence, Detection, and Declarative Responsibility in Research PracticeSemantic proximity Read

Vernacular Remote Control: Adversarial Robustness Testing of Six Commercial AI Text Detectors on Provenance-Guaranteed Pre-AI ProseSemantic proximity Read

Synergy, Not Substitution. Responsible Human–AI Collaboration in Academic ResearchSemantic proximity Read

A Framework for Ethical AI-Generated Content GovernanceSemantic proximity Read

A systematic map of generative AI guidelines and reporting in ecology and evolutionary biology: towards the framework of AI disclosure for Improved Transparency (AIdIT)Semantic proximity Read

Seven Guiding Questions for Reproducible AI-Assisted Research in the Social and Behavioral SciencesSemantic proximity Read

Seven Guiding Questions for Reproducible AI-Assisted Research in the Social and Behavioral SciencesSemantic proximity Read

Structural and Ethical Distinctions in Generative AI Music Production: A Comparative Analysis of Human Creative Processes and Algorithmic SystemsSemantic proximity Read

The Supervision Paradox: AI Capability Growth Necessitates Usage Contraction in High-Loss DomainsSemantic proximity Read