The Quest for Reliable Metrics of Responsible AI

The Quest for Reliable Metrics of Responsible AI | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 2 December 2025 V1 Latest version Share on The Quest for Reliable Metrics of Responsible AI Authors : Theresia Veronika Rampisela 0009-0006-1261-5848 [email protected] , Maria Maistro , Tuukka Ruotsalo , and Christina Lioma Authors Info & Affiliations https://doi.org/10.22541/au.176463779.91679966/v1 115 views 101 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The development of Artificial Intelligence (AI), including AI in Science (AIS), should be done following the principles of responsible AI. Progress in responsible AI is often quantified through evaluation metrics, yet there has been less work on assessing the robustness and reliability of the metrics themselves. We reflect on prior work that examines the robustness of fairness metrics for recommender systems as a type of AI application and summarise their key takeaways into a set of non-exhaustive guidelines for developing reliable metrics of responsible AI. Our guidelines apply to a broad spectrum of AI applications, including AIS. Supplementary Material File (manuscript1.pdf) Download 488.60 KB Information & Authors Information Version history V1 Version 1 02 December 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords fairness evaluation group fairness metrics metric robustness recommender systems responsible ai Authors Affiliations Theresia Veronika Rampisela 0009-0006-1261-5848 [email protected] University of Copenhagen View all articles by this author Maria Maistro University of Copenhagen View all articles by this author Tuukka Ruotsalo University of Copenhagen, LUT University View all articles by this author Christina Lioma University of Copenhagen View all articles by this author Metrics & Citations Metrics Article Usage 115 views 101 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo, et al. The Quest for Reliable Metrics of Responsible AI. Authorea . 02 December 2025. DOI: https://doi.org/10.22541/au.176463779.91679966/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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