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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorBagheri, Ayoub
dc.contributor.authorPapadopoulou, Evi
dc.date.accessioned2024-08-26T23:04:16Z
dc.date.available2024-08-26T23:04:16Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/47391
dc.description.abstractPrior research has demonstrated that language models can, to a limited extent, represent moral norms in a variety of cultural contexts. This thesis aims to replicate these findings and further explore their validity, concentrating on issues like 'homosexuality' and 'divorce'. This study evaluates the effectiveness of these models using information from two surveys, the WVS and the PEW, that encompass moral perspectives from over 40 countries. The results show that biases exist in both monolingual and multilingual models, and they typically fall short of accurately capturing the moral intricacies of diverse cultures. However, the BLOOM model shows the best performance, exhibiting some positive correlations, but still does not achieve a comprehensive moral understanding. This research underscores the limitations of current PLMs in processing cross-cultural differences in values and highlights the importance of developing culturally aware AI systems that better align with universal human values.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectLarge Language Models as Mirrors of Societal Moral Standards
dc.titleLarge Language Models as Mirrors of Societal Moral Standards
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuApplied Data Science
dc.thesis.id38020


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