Can You Fool AI by Doing a 180? $\unicode{x2013}$ A Case Study on Authorship Analysis of Texts by Arata Osada
Jagna Nieuwazny, Karol Nowakowski, Michal Ptaszynski, Fumito Masui

TL;DR
This study investigates whether authorship analysis systems can correctly attribute texts from the same author who undergoes significant psychological and ethical changes over time, revealing potential vulnerabilities in authorship attribution methods.
Contribution
It demonstrates that major ethical and psychological transformations in an author can significantly reduce authorship classification accuracy, highlighting limitations of current models.
Findings
Classification accuracy drops over long time spans for the same author.
Confidence scores remain stable despite lower accuracy, indicating potential for deception.
Historical and ethical changes influence authorship attribution results.
Abstract
This paper is our attempt at answering a twofold question covering the areas of ethics and authorship analysis. Firstly, since the methods used for performing authorship analysis imply that an author can be recognized by the content he or she creates, we were interested in finding out whether it would be possible for an author identification system to correctly attribute works to authors if in the course of years they have undergone a major psychological transition. Secondly, and from the point of view of the evolution of an author's ethical values, we checked what it would mean if the authorship attribution system encounters difficulties in detecting single authorship. We set out to answer those questions through performing a binary authorship analysis task using a text classifier based on a pre-trained transformer model and a baseline method relying on conventional similarity metrics.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsTest
