The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing

Andrea Agiollo*, Luciano Cavalcante Siebert, Pradeep Kumar Murukannaiah, Andrea Omicini

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Although popular and effective, large language models (LLM) are characterised by a performance vs. transparency trade-off that hinders their applicability to sensitive scenarios. This is the main reason behind many approaches focusing on local post-hoc explanations recently proposed by the XAI community. However, to the best of our knowledge, a thorough comparison among available explainability techniques is currently missing, mainly for the lack of a general metric to measure their benefits. We compare state-of-the-art local post-hoc explanation mechanisms for models trained over moral value classification tasks based on a measure of correlation. By relying on a novel framework for comparing global impact scores, our experiments show how most local post-hoc explainers are loosely correlated, and highlight huge discrepancies in their results—their “quarrel” about explanations. Finally, we compare the impact scores distribution obtained from each local post-hoc explainer with human-made dictionaries, and point out that there is no correlation between explanation outputs and the concepts humans consider as salient.

Original languageEnglish
Title of host publicationExplainable and Transparent AI and Multi-Agent Systems - 5th International Workshop, EXTRAAMAS 2023, Revised Selected Papers
EditorsDavide Calvaresi, Amro Najjar, Andrea Omicini, Rachele Carli, Giovanni Ciatto, Reyhan Aydogan, Yazan Mualla, Kary Främling
PublisherSpringer
Pages97-115
Number of pages19
ISBN (Print)9783031408779
DOIs
Publication statusPublished - 2023
EventProceedings of the 5th International Workshop on EXTRAAMAS 2023 - London, United Kingdom
Duration: 29 May 202329 May 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14127 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceProceedings of the 5th International Workshop on EXTRAAMAS 2023
Country/TerritoryUnited Kingdom
CityLondon
Period29/05/2329/05/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • eXplainable Artificial Intelligence
  • Local Post-hoc Explanations
  • Moral Values Classification
  • Natural Language Processing

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