Intellectual humility has attracted attention in both philosophy and psychology. Philosophers have clarified the nature of intellectual humility as an epistemic virtue; and psychologists have developed scales for measuring people’s intellectual humility. Much less attention has been paid to the potential effects of intellectual humility on people’s negative attitudes and to its relationship with prejudice-based epistemic vices. Here we fill these gaps by focusing on the relationship between intellectual humility and prejudice. To clarify this relationship, we conducted four empirical studies. (...) The results of these studies show three things. First, people are systematically prejudiced towards members of groups perceived as dissimilar. Second, intellectual humility weakens the association between perceived dissimilarity and prejudice. Third, more intellectual humility is associated withmoreprejudice overall. We show that this apparently paradoxical pattern of results is consistent with the idea that it is both psychologically and rationally plausible that one person is at the same time intellectually humble, epistemically virtuous and strongly prejudiced. (shrink)

Through a critical analysis of recent developments in the theory and practice of data science, including nascent feminist approaches to data collection and analysis, this commentary aims to signal the need for a transnational feminist orientation towards data science. I argue that while much needed in the context of persistent algorithmic oppression, a Western feminist lens limits the scope of problems, and thus—solutions, critical data scholars, and scientists can consider. A resolutely transnational feminist approach on the other hand, can provide (...) data theorists and practitioners with the hermeneutic tools necessary to identify and disrupt instances of injustice in a more inclusive and comprehensive manner. A transnational feminist orientation to data science can pay particular attention to the communities rendered most vulnerable by algorithmic oppression, such as women of color and populations in non-Western countries. I present five ways in which transnational feminism can be leveraged as an intervention into the current data science canon. (shrink)