{"type":"ScholarlyArticle","title":"Even If Explanations: Prior Work, Desiderata & Benchmarks for Semi-Factual XAI","authors":[{"name":"Saugat Aryal","slug":"saugat-aryal","given":"Saugat","family":"Aryal","affiliation":"School of Computer Science , University College Dublin , Dublin , Ireland; Insight Centre for Data Analytics , Dublin , Ireland"},{"name":"Mark T. Keane","slug":"mark-t-keane","given":"Mark T.","family":"Keane","affiliation":"School of Computer Science , University College Dublin , Dublin , Ireland; Insight Centre for Data Analytics , Dublin , Ireland"}],"abstract":"Recently, eXplainable AI (XAI) research has focused on counterfactual explanations as post-hoc justifications for AI-system decisions (e.g., a customer refused a loan might be told “if you asked for a loan with a shorter term, it would have been approved”). Counterfactuals explain what changes to the input-features of an AI system change the output-decision. However, there is a sub-type of counterfactual, semi-factuals, that have received less attention in AI (though the Cognitive Sciences have studied them more). This paper surveys semi-factual explanation, summarising historical and recent work. It defines key desiderata for semi-factual XAI, reporting benchmark tests of historical algorithms (as well as a novel, naïve method) to provide a solid basis for future developments.","doi":"10.24963/ijcai.2023/732","url":"https://ijcai.org/proceedings/2023/732","pdf":"https://ijcai.org/proceedings/2023/0732.pdf","markdown":"https://ijcai.org/proceedings/2023/732.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/732","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Survey Track","track":"Survey Track","number":732,"pages":{"first":6526,"last":6535},"keywords":["Survey: AI Ethics, Trust, Fairness","Survey: Machine Learning","Survey: Humans and AI"],"videos":[],"references":[{"position":1,"raw":"[Adadi and Berrada, 2018] Amina Adadi and Mohammed Berrada. 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