Intellectual humility can be broadly construed as being conscious of the limits of one’s existing knowledge and capable of acquiring more knowledge, which makes it a key virtue of the information age. However, the claim “I am (intellectually) humble” seems paradoxical in that someone who has the disposition in question would not typically volunteer it. Therefore, measuring intellectual humility via self-report may be methodologically unsound. As a consequence, we suggest analyzing intellectual humility semantically, using a psycholexical approach that focuses on both synonyms and antonyms of ‘intellectual humility’. We present a thesaurus-based methodology to map the semantic space of intellectual humility and the vices it opposes as a heuristic to support analysis and diagnosis of this disposition. We performed the mapping both in English and German in order to test for possible cultural differences in the understanding of intellectual humility. In both languages, we find basically the same three semantic dimensions of intellectual humility (sensibility, unpretentiousness, and knowledge dimensions) as well as three dimensions of its related vices (self-overrating, other-underrating and dogmatism dimensions). The resulting semantic clusters were validated in an empirical study with English (n = 276) and German (n = 406) participants. We find medium-to-high correlations (0.54–0.72) between thesaurus similarity and perceived similarity, and we can validate the three dimensions identified in the study. But we also find limitations of the thesaurus methodology in terms of cluster plausibility. We conclude by discussing the importance of these findings for constructing psychometric measures of intellectual humility via self-report vs. computer models.

Original languageEnglish
Pages (from-to)785-801
Number of pages17
JournalAI and Society
Volume34
Issue number4
DOIs
Publication statusPublished - 1 Dec 2019

    Research areas

  • Antonymy, Intellectual humility, Psycholexical analysis, Semantics, Synonymy, Thesaurus databases

ID: 62634296