Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective

• URL: http://arxiv.org/abs/2311.02237v1
• Date: Fri, 3 Nov 2023 20:51:15 GMT
• Title: Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective
• Authors: Mattia Setzu and Silvia Corbara and Anna Monreale and Alejandro Moreo and Fabrizio Sebastiani
• Abstract summary: We explore the applicability of existing general-purpose eXplainable Artificial Intelligence (XAI) techniques to AId. In particular, we assess the relative merits of three different types of XAI techniques on three different AId tasks. Our analysis shows that, while these techniques make important first steps towards explainable Authorship Identification, more work remains to be done.
• Score: 48.031678295495574
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: While a substantial amount of work has recently been devoted to enhance the performance of computational Authorship Identification (AId) systems, little to no attention has been paid to endowing AId systems with the ability to explain the reasons behind their predictions. This lacking substantially hinders the practical employment of AId methodologies, since the predictions returned by such systems are hardly useful unless they are supported with suitable explanations. In this paper, we explore the applicability of existing general-purpose eXplainable Artificial Intelligence (XAI) techniques to AId, with a special focus on explanations addressed to scholars working in cultural heritage. In particular, we assess the relative merits of three different types of XAI techniques (feature ranking, probing, factuals and counterfactual selection) on three different AId tasks (authorship attribution, authorship verification, same-authorship verification) by running experiments on real AId data. Our analysis shows that, while these techniques make important first steps towards explainable Authorship Identification, more work remains to be done in order to provide tools that can be profitably integrated in the workflows of scholars.

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